allow ListObject to have TVar item_type

fixup! fixup! core/ndstrides: implement np_array()
fix binop +
2024-08-24 12:37:25 +08:00 · 2024-08-23 16:35:43 +08:00 · 2024-08-23 16:27:49 +08:00 · 2024-08-23 16:24:18 +08:00 · 2024-08-23 16:23:16 +08:00 · 2024-08-23 15:34:26 +08:00
112 changed files with 9753 additions and 9293 deletions
--- a/.clang-format
+++ b/.clang-format
@ -1,32 +1,3 @@
-BasedOnStyle: LLVM
-
-Language: Cpp
-Standard: Cpp11
-
-AccessModifierOffset: -1
-AlignEscapedNewlines: Left
-AlwaysBreakAfterReturnType: None
-AlwaysBreakTemplateDeclarations: Yes
-AllowAllParametersOfDeclarationOnNextLine: false
-AllowShortFunctionsOnASingleLine: Inline
-BinPackParameters: false
-BreakBeforeBinaryOperators: NonAssignment
-BreakBeforeTernaryOperators: true
-BreakConstructorInitializers: AfterColon
-BreakInheritanceList: AfterColon
-ColumnLimit: 120
-ConstructorInitializerAllOnOneLineOrOnePerLine: true
-ContinuationIndentWidth: 4
-DerivePointerAlignment: false
-IndentCaseLabels: true
-IndentPPDirectives: None
+BasedOnStyle: Microsoft
 IndentWidth: 4
-MaxEmptyLinesToKeep: 1
-PointerAlignment: Left
-ReflowComments: true
-SortIncludes: false
-SortUsingDeclarations: true
-SpaceAfterTemplateKeyword: false
-SpacesBeforeTrailingComments: 2
-TabWidth: 4
-UseTab: Never
+ReflowComments: false
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@ -8,17 +8,17 @@ repos:
    hooks:
      - id: nac3-cargo-fmt
        name: nac3 cargo format
-        entry: nix
+        entry: cargo
        language: system
        types: [file, rust]
        pass_filenames: false
        description: Runs cargo fmt on the codebase.
-        args: [develop, -c, cargo, fmt, --all]
+        args: [fmt]
      - id: nac3-cargo-clippy
        name: nac3 cargo clippy
-        entry: nix
+        entry: cargo
        language: system
        types: [file, rust]
        pass_filenames: false
        description: Runs cargo clippy on the codebase.
-        args: [develop, -c, cargo, clippy, --tests]
+        args: [clippy, --tests]
--- a/Cargo.lock
+++ b/Cargo.lock
@ -26,9 +26,9 @@ dependencies = [

 [[package]]
 name = "anstream"
-version = "0.6.17"
+version = "0.6.15"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "23a1e53f0f5d86382dafe1cf314783b2044280f406e7e1506368220ad11b1338"
+checksum = "64e15c1ab1f89faffbf04a634d5e1962e9074f2741eef6d97f3c4e322426d526"
 dependencies = [
 "anstyle",
 "anstyle-parse",
@ -41,67 +41,67 @@ dependencies = [

 [[package]]
 name = "anstyle"
-version = "1.0.9"
+version = "1.0.8"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8365de52b16c035ff4fcafe0092ba9390540e3e352870ac09933bebcaa2c8c56"
+checksum = "1bec1de6f59aedf83baf9ff929c98f2ad654b97c9510f4e70cf6f661d49fd5b1"

 [[package]]
 name = "anstyle-parse"
-version = "0.2.6"
+version = "0.2.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3b2d16507662817a6a20a9ea92df6652ee4f94f914589377d69f3b21bc5798a9"
+checksum = "eb47de1e80c2b463c735db5b217a0ddc39d612e7ac9e2e96a5aed1f57616c1cb"
 dependencies = [
 "utf8parse",
 ]

 [[package]]
 name = "anstyle-query"
-version = "1.1.2"
+version = "1.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "79947af37f4177cfead1110013d678905c37501914fba0efea834c3fe9a8d60c"
+checksum = "6d36fc52c7f6c869915e99412912f22093507da8d9e942ceaf66fe4b7c14422a"
 dependencies = [
- "windows-sys 0.59.0",
+ "windows-sys 0.52.0",
 ]

 [[package]]
 name = "anstyle-wincon"
-version = "3.0.6"
+version = "3.0.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2109dbce0e72be3ec00bed26e6a7479ca384ad226efdd66db8fa2e3a38c83125"
+checksum = "5bf74e1b6e971609db8ca7a9ce79fd5768ab6ae46441c572e46cf596f59e57f8"
 dependencies = [
 "anstyle",
- "windows-sys 0.59.0",
+ "windows-sys 0.52.0",
 ]

 [[package]]
 name = "ascii-canvas"
-version = "4.0.0"
+version = "3.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ef1e3e699d84ab1b0911a1010c5c106aa34ae89aeac103be5ce0c3859db1e891"
+checksum = "8824ecca2e851cec16968d54a01dd372ef8f95b244fb84b84e70128be347c3c6"
 dependencies = [
 "term",
 ]

 [[package]]
 name = "autocfg"
-version = "1.4.0"
+version = "1.3.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ace50bade8e6234aa140d9a2f552bbee1db4d353f69b8217bc503490fc1a9f26"
+checksum = "0c4b4d0bd25bd0b74681c0ad21497610ce1b7c91b1022cd21c80c6fbdd9476b0"

 [[package]]
 name = "bit-set"
-version = "0.8.0"
+version = "0.5.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "08807e080ed7f9d5433fa9b275196cfc35414f66a0c79d864dc51a0d825231a3"
+checksum = "0700ddab506f33b20a03b13996eccd309a48e5ff77d0d95926aa0210fb4e95f1"
 dependencies = [
 "bit-vec",
 ]

 [[package]]
 name = "bit-vec"
-version = "0.8.0"
+version = "0.6.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5e764a1d40d510daf35e07be9eb06e75770908c27d411ee6c92109c9840eaaf7"
+checksum = "349f9b6a179ed607305526ca489b34ad0a41aed5f7980fa90eb03160b69598fb"

 [[package]]
 name = "bitflags"
@ -109,15 +109,6 @@ version = "2.6.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b048fb63fd8b5923fc5aa7b340d8e156aec7ec02f0c78fa8a6ddc2613f6f71de"

-[[package]]
-name = "block-buffer"
-version = "0.10.4"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3078c7629b62d3f0439517fa394996acacc5cbc91c5a20d8c658e77abd503a71"
-dependencies = [
- "generic-array",
-]
-
 [[package]]
 name = "byteorder"
 version = "1.5.0"
@ -126,9 +117,9 @@ checksum = "1fd0f2584146f6f2ef48085050886acf353beff7305ebd1ae69500e27c67f64b"

 [[package]]
 name = "cc"
-version = "1.1.31"
+version = "1.1.13"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c2e7962b54006dcfcc61cb72735f4d89bb97061dd6a7ed882ec6b8ee53714c6f"
+checksum = "72db2f7947ecee9b03b510377e8bb9077afa27176fdbff55c51027e976fdcc48"
 dependencies = [
 "shlex",
 ]
@ -141,9 +132,9 @@ checksum = "baf1de4339761588bc0619e3cbc0120ee582ebb74b53b4efbf79117bd2da40fd"

 [[package]]
 name = "clap"
-version = "4.5.20"
+version = "4.5.16"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b97f376d85a664d5837dbae44bf546e6477a679ff6610010f17276f686d867e8"
+checksum = "ed6719fffa43d0d87e5fd8caeab59be1554fb028cd30edc88fc4369b17971019"
 dependencies = [
 "clap_builder",
 "clap_derive",
@ -151,9 +142,9 @@ dependencies = [

 [[package]]
 name = "clap_builder"
-version = "4.5.20"
+version = "4.5.15"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "19bc80abd44e4bed93ca373a0704ccbd1b710dc5749406201bb018272808dc54"
+checksum = "216aec2b177652e3846684cbfe25c9964d18ec45234f0f5da5157b207ed1aab6"
 dependencies = [
 "anstream",
 "anstyle",
@ -163,14 +154,14 @@ dependencies = [

 [[package]]
 name = "clap_derive"
-version = "4.5.18"
+version = "4.5.13"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4ac6a0c7b1a9e9a5186361f67dfa1b88213572f427fb9ab038efb2bd8c582dab"
+checksum = "501d359d5f3dcaf6ecdeee48833ae73ec6e42723a1e52419c79abf9507eec0a0"
 dependencies = [
 "heck 0.5.0",
 "proc-macro2",
 "quote",
- "syn 2.0.85",
+ "syn 2.0.75",
 ]

 [[package]]
@ -181,9 +172,9 @@ checksum = "1462739cb27611015575c0c11df5df7601141071f07518d56fcc1be504cbec97"

 [[package]]
 name = "colorchoice"
-version = "1.0.3"
+version = "1.0.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5b63caa9aa9397e2d9480a9b13673856c78d8ac123288526c37d7839f2a86990"
+checksum = "d3fd119d74b830634cea2a0f58bbd0d54540518a14397557951e79340abc28c0"

 [[package]]
 name = "console"
@ -197,15 +188,6 @@ dependencies = [
 "windows-sys 0.52.0",
 ]

-[[package]]
-name = "cpufeatures"
-version = "0.2.14"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "608697df725056feaccfa42cffdaeeec3fccc4ffc38358ecd19b243e716a78e0"
-dependencies = [
- "libc",
-]
-
 [[package]]
 name = "crossbeam"
 version = "0.8.4"
@ -263,23 +245,30 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "22ec99545bb0ed0ea7bb9b8e1e9122ea386ff8a48c0922e43f36d45ab09e0e80"

 [[package]]
-name = "crypto-common"
-version = "0.1.6"
+name = "crunchy"
+version = "0.2.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1bfb12502f3fc46cca1bb51ac28df9d618d813cdc3d2f25b9fe775a34af26bb3"
+checksum = "7a81dae078cea95a014a339291cec439d2f232ebe854a9d672b796c6afafa9b7"
+
+[[package]]
+name = "dirs-next"
+version = "2.0.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "b98cf8ebf19c3d1b223e151f99a4f9f0690dca41414773390fc824184ac833e1"
 dependencies = [
- "generic-array",
- "typenum",
+ "cfg-if",
+ "dirs-sys-next",
 ]

 [[package]]
-name = "digest"
-version = "0.10.7"
+name = "dirs-sys-next"
+version = "0.1.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9ed9a281f7bc9b7576e61468ba615a66a5c8cfdff42420a70aa82701a3b1e292"
+checksum = "4ebda144c4fe02d1f7ea1a7d9641b6fc6b580adcfa024ae48797ecdeb6825b4d"
 dependencies = [
- "block-buffer",
- "crypto-common",
+ "libc",
+ "redox_users",
+ "winapi",
 ]

 [[package]]
@ -321,9 +310,9 @@ dependencies = [

 [[package]]
 name = "fastrand"
-version = "2.1.1"
+version = "2.1.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e8c02a5121d4ea3eb16a80748c74f5549a5665e4c21333c6098f283870fbdea6"
+checksum = "9fc0510504f03c51ada170672ac806f1f105a88aa97a5281117e1ddc3368e51a"

 [[package]]
 name = "fixedbitset"
@ -340,16 +329,6 @@ dependencies = [
 "byteorder",
 ]

-[[package]]
-name = "generic-array"
-version = "0.14.7"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "85649ca51fd72272d7821adaf274ad91c288277713d9c18820d8499a7ff69e9a"
-dependencies = [
- "typenum",
- "version_check",
-]
-
 [[package]]
 name = "getopts"
 version = "0.2.21"
@ -385,12 +364,6 @@ dependencies = [
 "ahash",
 ]

-[[package]]
-name = "hashbrown"
-version = "0.15.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1e087f84d4f86bf4b218b927129862374b72199ae7d8657835f1e89000eea4fb"
-
 [[package]]
 name = "heck"
 version = "0.4.1"
@ -403,15 +376,6 @@ version = "0.5.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "2304e00983f87ffb38b55b444b5e3b60a884b5d30c0fca7d82fe33449bbe55ea"

-[[package]]
-name = "home"
-version = "0.5.9"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e3d1354bf6b7235cb4a0576c2619fd4ed18183f689b12b006a0ee7329eeff9a5"
-dependencies = [
- "windows-sys 0.52.0",
-]
-
 [[package]]
 name = "indexmap"
 version = "1.9.3"
@ -424,12 +388,12 @@ dependencies = [

 [[package]]
 name = "indexmap"
-version = "2.6.0"
+version = "2.4.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "707907fe3c25f5424cce2cb7e1cbcafee6bdbe735ca90ef77c29e84591e5b9da"
+checksum = "93ead53efc7ea8ed3cfb0c79fc8023fbb782a5432b52830b6518941cebe6505c"
 dependencies = [
 "equivalent",
- "hashbrown 0.15.0",
+ "hashbrown 0.14.5",
 ]

 [[package]]
@ -440,9 +404,9 @@ checksum = "b248f5224d1d606005e02c97f5aa4e88eeb230488bcc03bc9ca4d7991399f2b5"

 [[package]]
 name = "inkwell"
-version = "0.5.0"
+version = "0.4.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "40fb405537710d51f6bdbc8471365ddd4cd6d3a3c3ad6e0c8291691031ba94b2"
+checksum = "b597a7b2cdf279aeef6d7149071e35e4bc87c2cf05a5b7f2d731300bffe587ea"
 dependencies = [
 "either",
 "inkwell_internals",
@ -454,13 +418,13 @@ dependencies = [

 [[package]]
 name = "inkwell_internals"
-version = "0.10.0"
+version = "0.9.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9dd28cfd4cfba665d47d31c08a6ba637eed16770abca2eccbbc3ca831fef1e44"
+checksum = "4fa4d8d74483041a882adaa9a29f633253a66dde85055f0495c121620ac484b2"
 dependencies = [
 "proc-macro2",
 "quote",
- "syn 2.0.85",
+ "syn 2.0.75",
 ]

 [[package]]
@ -483,6 +447,15 @@ version = "1.70.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "7943c866cc5cd64cbc25b2e01621d07fa8eb2a1a23160ee81ce38704e97b8ecf"

+[[package]]
+name = "itertools"
+version = "0.11.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "b1c173a5686ce8bfa551b3563d0c2170bf24ca44da99c7ca4bfdab5418c3fe57"
+dependencies = [
+ "either",
+]
+
 [[package]]
 name = "itertools"
 version = "0.13.0"
@ -498,45 +471,35 @@ version = "1.0.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "49f1f14873335454500d59611f1cf4a4b0f786f9ac11f4312a78e4cf2566695b"

-[[package]]
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-version = "0.1.5"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ecc2af9a1119c51f12a14607e783cb977bde58bc069ff0c3da1095e635d70654"
-dependencies = [
- "cpufeatures",
-]
-
 [[package]]
 name = "lalrpop"
-version = "0.22.0"
+version = "0.20.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "06093b57658c723a21da679530e061a8c25340fa5a6f98e313b542268c7e2a1f"
+checksum = "55cb077ad656299f160924eb2912aa147d7339ea7d69e1b5517326fdcec3c1ca"
 dependencies = [
 "ascii-canvas",
 "bit-set",
 "ena",
- "itertools",
+ "itertools 0.11.0",
 "lalrpop-util",
 "petgraph",
 "pico-args",
 "regex",
 "regex-syntax",
- "sha3",
 "string_cache",
 "term",
+ "tiny-keccak",
 "unicode-xid",
 "walkdir",
 ]

 [[package]]
 name = "lalrpop-util"
-version = "0.22.0"
+version = "0.20.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "feee752d43abd0f4807a921958ab4131f692a44d4d599733d4419c5d586176ce"
+checksum = "507460a910eb7b32ee961886ff48539633b788a36b65692b95f225b844c82553"
 dependencies = [
 "regex-automata",
- "rustversion",
 ]

 [[package]]
@ -547,9 +510,9 @@ checksum = "bbd2bcb4c963f2ddae06a2efc7e9f3591312473c50c6685e1f298068316e66fe"

 [[package]]
 name = "libc"
-version = "0.2.161"
+version = "0.2.157"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8e9489c2807c139ffd9c1794f4af0ebe86a828db53ecdc7fea2111d0fed085d1"
+checksum = "374af5f94e54fa97cf75e945cce8a6b201e88a1a07e688b47dfd2a59c66dbd86"

 [[package]]
 name = "libloading"
@ -561,6 +524,16 @@ dependencies = [
 "windows-targets",
 ]

+[[package]]
+name = "libredox"
+version = "0.1.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "c0ff37bd590ca25063e35af745c343cb7a0271906fb7b37e4813e8f79f00268d"
+dependencies = [
+ "bitflags",
+ "libc",
+]
+
 [[package]]
 name = "linked-hash-map"
 version = "0.5.6"
@ -621,9 +594,11 @@ dependencies = [
 name = "nac3artiq"
 version = "0.1.0"
 dependencies = [
- "itertools",
+ "inkwell",
+ "itertools 0.13.0",
 "nac3core",
 "nac3ld",
+ "nac3parser",
 "parking_lot",
 "pyo3",
 "tempfile",
@ -634,6 +609,7 @@ name = "nac3ast"
 version = "0.1.0"
 dependencies = [
 "fxhash",
+ "lazy_static",
 "parking_lot",
 "string-interner",
 ]
@ -643,11 +619,11 @@ name = "nac3core"
 version = "0.1.0"
 dependencies = [
 "crossbeam",
- "indexmap 2.6.0",
+ "indexmap 2.4.0",
 "indoc",
 "inkwell",
 "insta",
- "itertools",
+ "itertools 0.13.0",
 "nac3parser",
 "parking_lot",
 "rayon",
@ -685,7 +661,9 @@ name = "nac3standalone"
 version = "0.1.0"
 dependencies = [
 "clap",
+ "inkwell",
 "nac3core",
+ "nac3parser",
 "parking_lot",
 ]

@ -697,9 +675,9 @@ checksum = "650eef8c711430f1a879fdd01d4745a7deea475becfb90269c06775983bbf086"

 [[package]]
 name = "once_cell"
-version = "1.20.2"
+version = "1.19.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1261fe7e33c73b354eab43b1273a57c8f967d0391e80353e51f764ac02cf6775"
+checksum = "3fdb12b2476b595f9358c5161aa467c2438859caa136dec86c26fdd2efe17b92"

 [[package]]
 name = "parking_lot"
@ -731,7 +709,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b4c5cc86750666a3ed20bdaf5ca2a0344f9c67674cae0515bec2da16fbaa47db"
 dependencies = [
 "fixedbitset",
- "indexmap 2.6.0",
+ "indexmap 2.4.0",
 ]

 [[package]]
@ -774,7 +752,7 @@ dependencies = [
 "phf_shared 0.11.2",
 "proc-macro2",
 "quote",
- "syn 2.0.85",
+ "syn 2.0.75",
 ]

 [[package]]
@ -803,9 +781,9 @@ checksum = "5be167a7af36ee22fe3115051bc51f6e6c7054c9348e28deb4f49bd6f705a315"

 [[package]]
 name = "portable-atomic"
-version = "1.9.0"
+version = "1.7.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "cc9c68a3f6da06753e9335d63e27f6b9754dd1920d941135b7ea8224f141adb2"
+checksum = "da544ee218f0d287a911e9c99a39a8c9bc8fcad3cb8db5959940044ecfc67265"

 [[package]]
 name = "ppv-lite86"
@ -824,9 +802,9 @@ checksum = "925383efa346730478fb4838dbe9137d2a47675ad789c546d150a6e1dd4ab31c"

 [[package]]
 name = "proc-macro2"
-version = "1.0.89"
+version = "1.0.86"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f139b0662de085916d1fb67d2b4169d1addddda1919e696f3252b740b629986e"
+checksum = "5e719e8df665df0d1c8fbfd238015744736151d4445ec0836b8e628aae103b77"
 dependencies = [
 "unicode-ident",
 ]
@ -878,7 +856,7 @@ dependencies = [
 "proc-macro2",
 "pyo3-macros-backend",
 "quote",
- "syn 2.0.85",
+ "syn 2.0.75",
 ]

 [[package]]
@ -891,14 +869,14 @@ dependencies = [
 "proc-macro2",
 "pyo3-build-config",
 "quote",
- "syn 2.0.85",
+ "syn 2.0.75",
 ]

 [[package]]
 name = "quote"
-version = "1.0.37"
+version = "1.0.36"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b5b9d34b8991d19d98081b46eacdd8eb58c6f2b201139f7c5f643cc155a633af"
+checksum = "0fa76aaf39101c457836aec0ce2316dbdc3ab723cdda1c6bd4e6ad4208acaca7"
 dependencies = [
 "proc-macro2",
 ]
@ -955,18 +933,29 @@ dependencies = [

 [[package]]
 name = "redox_syscall"
-version = "0.5.7"
+version = "0.5.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9b6dfecf2c74bce2466cabf93f6664d6998a69eb21e39f4207930065b27b771f"
+checksum = "2a908a6e00f1fdd0dfd9c0eb08ce85126f6d8bbda50017e74bc4a4b7d4a926a4"
 dependencies = [
 "bitflags",
 ]

 [[package]]
-name = "regex"
-version = "1.11.1"
+name = "redox_users"
+version = "0.4.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b544ef1b4eac5dc2db33ea63606ae9ffcfac26c1416a2806ae0bf5f56b201191"
+checksum = "bd283d9651eeda4b2a83a43c1c91b266c40fd76ecd39a50a8c630ae69dc72891"
+dependencies = [
+ "getrandom",
+ "libredox",
+ "thiserror",
+]
+
+[[package]]
+name = "regex"
+version = "1.10.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "4219d74c6b67a3654a9fbebc4b419e22126d13d2f3c4a07ee0cb61ff79a79619"
 dependencies = [
 "aho-corasick",
 "memchr",
@ -976,9 +965,9 @@ dependencies = [

 [[package]]
 name = "regex-automata"
-version = "0.4.8"
+version = "0.4.7"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "368758f23274712b504848e9d5a6f010445cc8b87a7cdb4d7cbee666c1288da3"
+checksum = "38caf58cc5ef2fed281f89292ef23f6365465ed9a41b7a7754eb4e26496c92df"
 dependencies = [
 "aho-corasick",
 "memchr",
@ -987,9 +976,9 @@ dependencies = [

 [[package]]
 name = "regex-syntax"
-version = "0.8.5"
+version = "0.8.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2b15c43186be67a4fd63bee50d0303afffcef381492ebe2c5d87f324e1b8815c"
+checksum = "7a66a03ae7c801facd77a29370b4faec201768915ac14a721ba36f20bc9c209b"

 [[package]]
 name = "runkernel"
@ -1000,9 +989,9 @@ dependencies = [

 [[package]]
 name = "rustix"
-version = "0.38.38"
+version = "0.38.34"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "aa260229e6538e52293eeb577aabd09945a09d6d9cc0fc550ed7529056c2e32a"
+checksum = "70dc5ec042f7a43c4a73241207cecc9873a06d45debb38b329f8541d85c2730f"
 dependencies = [
 "bitflags",
 "errno",
@ -1013,9 +1002,9 @@ dependencies = [

 [[package]]
 name = "rustversion"
-version = "1.0.18"
+version = "1.0.17"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0e819f2bc632f285be6d7cd36e25940d45b2391dd6d9b939e79de557f7014248"
+checksum = "955d28af4278de8121b7ebeb796b6a45735dc01436d898801014aced2773a3d6"

 [[package]]
 name = "ryu"
@ -1046,29 +1035,29 @@ checksum = "61697e0a1c7e512e84a621326239844a24d8207b4669b41bc18b32ea5cbf988b"

 [[package]]
 name = "serde"
-version = "1.0.214"
+version = "1.0.208"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f55c3193aca71c12ad7890f1785d2b73e1b9f63a0bbc353c08ef26fe03fc56b5"
+checksum = "cff085d2cb684faa248efb494c39b68e522822ac0de72ccf08109abde717cfb2"
 dependencies = [
 "serde_derive",
 ]

 [[package]]
 name = "serde_derive"
-version = "1.0.214"
+version = "1.0.208"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "de523f781f095e28fa605cdce0f8307e451cc0fd14e2eb4cd2e98a355b147766"
+checksum = "24008e81ff7613ed8e5ba0cfaf24e2c2f1e5b8a0495711e44fcd4882fca62bcf"
 dependencies = [
 "proc-macro2",
 "quote",
- "syn 2.0.85",
+ "syn 2.0.75",
 ]

 [[package]]
 name = "serde_json"
-version = "1.0.132"
+version = "1.0.125"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d726bfaff4b320266d395898905d0eba0345aae23b54aee3a737e260fd46db03"
+checksum = "83c8e735a073ccf5be70aa8066aa984eaf2fa000db6c8d0100ae605b366d31ed"
 dependencies = [
 "itoa",
 "memchr",
@ -1088,16 +1077,6 @@ dependencies = [
 "yaml-rust",
 ]

-[[package]]
-name = "sha3"
-version = "0.10.8"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "75872d278a8f37ef87fa0ddbda7802605cb18344497949862c0d4dcb291eba60"
-dependencies = [
- "digest",
- "keccak",
-]
-
 [[package]]
 name = "shlex"
 version = "1.3.0"
@ -1168,7 +1147,7 @@ dependencies = [
 "proc-macro2",
 "quote",
 "rustversion",
- "syn 2.0.85",
+ "syn 2.0.75",
 ]

 [[package]]
@ -1184,9 +1163,9 @@ dependencies = [

 [[package]]
 name = "syn"
-version = "2.0.85"
+version = "2.0.75"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5023162dfcd14ef8f32034d8bcd4cc5ddc61ef7a247c024a33e24e1f24d21b56"
+checksum = "f6af063034fc1935ede7be0122941bafa9bacb949334d090b77ca98b5817c7d9"
 dependencies = [
 "proc-macro2",
 "quote",
@ -1201,9 +1180,9 @@ checksum = "61c41af27dd6d1e27b1b16b489db798443478cef1f06a660c96db617ba5de3b1"

 [[package]]
 name = "tempfile"
-version = "3.13.0"
+version = "3.12.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f0f2c9fc62d0beef6951ccffd757e241266a2c833136efbe35af6cd2567dca5b"
+checksum = "04cbcdd0c794ebb0d4cf35e88edd2f7d2c4c3e9a5a6dab322839b321c6a87a64"
 dependencies = [
 "cfg-if",
 "fastrand",
@ -1214,12 +1193,13 @@ dependencies = [

 [[package]]
 name = "term"
-version = "1.0.0"
+version = "0.7.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4df4175de05129f31b80458c6df371a15e7fc3fd367272e6bf938e5c351c7ea0"
+checksum = "c59df8ac95d96ff9bede18eb7300b0fda5e5d8d90960e76f8e14ae765eedbf1f"
 dependencies = [
- "home",
- "windows-sys 0.52.0",
+ "dirs-next",
+ "rustversion",
+ "winapi",
 ]

 [[package]]
@ -1237,29 +1217,32 @@ dependencies = [

 [[package]]
 name = "thiserror"
-version = "1.0.65"
+version = "1.0.63"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5d11abd9594d9b38965ef50805c5e469ca9cc6f197f883f717e0269a3057b3d5"
+checksum = "c0342370b38b6a11b6cc11d6a805569958d54cfa061a29969c3b5ce2ea405724"
 dependencies = [
 "thiserror-impl",
 ]

 [[package]]
 name = "thiserror-impl"
-version = "1.0.65"
+version = "1.0.63"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ae71770322cbd277e69d762a16c444af02aa0575ac0d174f0b9562d3b37f8602"
+checksum = "a4558b58466b9ad7ca0f102865eccc95938dca1a74a856f2b57b6629050da261"
 dependencies = [
 "proc-macro2",
 "quote",
- "syn 2.0.85",
+ "syn 2.0.75",
 ]

 [[package]]
-name = "typenum"
-version = "1.17.0"
+name = "tiny-keccak"
+version = "2.0.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "42ff0bf0c66b8238c6f3b578df37d0b7848e55df8577b3f74f92a69acceeb825"
+checksum = "2c9d3793400a45f954c52e73d068316d76b6f4e36977e3fcebb13a2721e80237"
+dependencies = [
+ "crunchy",
+]

 [[package]]
 name = "unic-char-property"
@ -1315,27 +1298,27 @@ dependencies = [

 [[package]]
 name = "unicode-ident"
-version = "1.0.13"
+version = "1.0.12"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e91b56cd4cadaeb79bbf1a5645f6b4f8dc5bde8834ad5894a8db35fda9efa1fe"
+checksum = "3354b9ac3fae1ff6755cb6db53683adb661634f67557942dea4facebec0fee4b"

 [[package]]
 name = "unicode-width"
-version = "0.1.14"
+version = "0.1.13"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7dd6e30e90baa6f72411720665d41d89b9a3d039dc45b8faea1ddd07f617f6af"
+checksum = "0336d538f7abc86d282a4189614dfaa90810dfc2c6f6427eaf88e16311dd225d"

 [[package]]
 name = "unicode-xid"
-version = "0.2.6"
+version = "0.2.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ebc1c04c71510c7f702b52b7c350734c9ff1295c464a03335b00bb84fc54f853"
+checksum = "f962df74c8c05a667b5ee8bcf162993134c104e96440b663c8daa176dc772d8c"

 [[package]]
 name = "unicode_names2"
-version = "1.3.0"
+version = "1.2.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d1673eca9782c84de5f81b82e4109dcfb3611c8ba0d52930ec4a9478f547b2dd"
+checksum = "addeebf294df7922a1164f729fb27ebbbcea99cc32b3bf08afab62757f707677"
 dependencies = [
 "phf",
 "unicode_names2_generator",
@ -1343,9 +1326,9 @@ dependencies = [

 [[package]]
 name = "unicode_names2_generator"
-version = "1.3.0"
+version = "1.2.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b91e5b84611016120197efd7dc93ef76774f4e084cd73c9fb3ea4a86c570c56e"
+checksum = "f444b8bba042fe3c1251ffaca35c603f2dc2ccc08d595c65a8c4f76f3e8426c0"
 dependencies = [
 "getopts",
 "log",
@ -1387,6 +1370,22 @@ version = "0.11.0+wasi-snapshot-preview1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "9c8d87e72b64a3b4db28d11ce29237c246188f4f51057d65a7eab63b7987e423"

+[[package]]
+name = "winapi"
+version = "0.3.9"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "5c839a674fcd7a98952e593242ea400abe93992746761e38641405d28b00f419"
+dependencies = [
+ "winapi-i686-pc-windows-gnu",
+ "winapi-x86_64-pc-windows-gnu",
+]
+
+[[package]]
+name = "winapi-i686-pc-windows-gnu"
+version = "0.4.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "ac3b87c63620426dd9b991e5ce0329eff545bccbbb34f3be09ff6fb6ab51b7b6"
+
 [[package]]
 name = "winapi-util"
 version = "0.1.9"
@ -1396,6 +1395,12 @@ dependencies = [
 "windows-sys 0.59.0",
 ]

+[[package]]
+name = "winapi-x86_64-pc-windows-gnu"
+version = "0.4.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "712e227841d057c1ee1cd2fb22fa7e5a5461ae8e48fa2ca79ec42cfc1931183f"
+
 [[package]]
 name = "windows-sys"
 version = "0.52.0"
@ -1505,5 +1510,5 @@ checksum = "fa4f8080344d4671fb4e831a13ad1e68092748387dfc4f55e356242fae12ce3e"
 dependencies = [
 "proc-macro2",
 "quote",
- "syn 2.0.85",
+ "syn 2.0.75",
 ]
--- a/flake.lock
+++ b/flake.lock
@ -2,11 +2,11 @@
  "nodes": {
    "nixpkgs": {
      "locked": {
-        "lastModified": 1727348695,
-        "narHash": "sha256-J+PeFKSDV+pHL7ukkfpVzCOO7mBSrrpJ3svwBFABbhI=",
+        "lastModified": 1723637854,
+        "narHash": "sha256-med8+5DSWa2UnOqtdICndjDAEjxr5D7zaIiK4pn0Q7c=",
        "owner": "NixOS",
        "repo": "nixpkgs",
-        "rev": "1925c603f17fc89f4c8f6bf6f631a802ad85d784",
+        "rev": "c3aa7b8938b17aebd2deecf7be0636000d62a2b9",
        "type": "github"
      },
      "original": {
--- a/nac3artiq/Cargo.toml
+++ b/nac3artiq/Cargo.toml
@ -12,10 +12,16 @@ crate-type = ["cdylib"]
 itertools = "0.13"
 pyo3 = { version = "0.21", features = ["extension-module", "gil-refs"] }
 parking_lot = "0.12"
-tempfile = "3.13"
+tempfile = "3.10"
+nac3parser = { path = "../nac3parser" }
 nac3core = { path = "../nac3core" }
 nac3ld = { path = "../nac3ld" }

+[dependencies.inkwell]
+version = "0.4"
+default-features = false
+features = ["llvm14-0", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]
+
 [features]
 init-llvm-profile = []
 no-escape-analysis = ["nac3core/no-escape-analysis"]
--- a/nac3artiq/demo/min_artiq.py
+++ b/nac3artiq/demo/min_artiq.py
@ -112,15 +112,10 @@ def extern(function):
    register_function(function)
    return function

-
-def rpc(arg=None, flags={}):
-    """Decorates a function or method to be executed on the host interpreter."""
-    if arg is None:
-        def inner_decorator(function):
-            return rpc(function, flags)
-        return inner_decorator
-    register_function(arg)
-    return arg
+def rpc(function):
+    """Decorates a function declaration defined by the core device runtime."""
+    register_function(function)
+    return function

 def kernel(function_or_method):
    """Decorates a function or method to be executed on the core device."""
--- a/nac3artiq/src/codegen.rs
+++ b/nac3artiq/src/codegen.rs
@ -1,3 +1,35 @@
+use nac3core::{
+    codegen::{
+        expr::gen_call,
+        llvm_intrinsics::{call_int_smax, call_stackrestore, call_stacksave},
+        model::*,
+        object::{any::AnyObject, list::ListObject, ndarray::NDArrayObject, range::RangeObject},
+        stmt::{gen_block, gen_for_callback_incrementing, gen_if_callback, gen_with},
+        CodeGenContext, CodeGenerator,
+    },
+    symbol_resolver::ValueEnum,
+    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId, GenCall},
+    typecheck::typedef::{iter_type_vars, FunSignature, FuncArg, Type, TypeEnum, VarMap},
+};
+
+use nac3parser::ast::{Expr, ExprKind, Located, Stmt, StmtKind, StrRef};
+
+use inkwell::{
+    context::Context,
+    module::Linkage,
+    types::IntType,
+    values::{BasicValueEnum, PointerValue, StructValue},
+    AddressSpace, IntPredicate,
+};
+
+use pyo3::{
+    types::{PyDict, PyList},
+    PyObject, PyResult, Python,
+};
+
+use crate::{symbol_resolver::InnerResolver, timeline::TimeFns};
+
+use itertools::Itertools;
 use std::{
    collections::{hash_map::DefaultHasher, HashMap},
    hash::{Hash, Hasher},
@ -6,39 +38,6 @@ use std::{
    sync::Arc,
 };

-use itertools::Itertools;
-use pyo3::{
-    types::{PyDict, PyList},
-    PyObject, PyResult, Python,
-};
-
-use nac3core::{
-    codegen::{
-        classes::{
-            ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayType,
-            NDArrayValue, ProxyType, ProxyValue, RangeValue, UntypedArrayLikeAccessor,
-        },
-        expr::{destructure_range, gen_call},
-        irrt::call_ndarray_calc_size,
-        llvm_intrinsics::{call_int_smax, call_memcpy_generic, call_stackrestore, call_stacksave},
-        stmt::{gen_block, gen_for_callback_incrementing, gen_if_callback, gen_with},
-        CodeGenContext, CodeGenerator,
-    },
-    inkwell::{
-        context::Context,
-        module::Linkage,
-        types::{BasicType, IntType},
-        values::{BasicValueEnum, IntValue, PointerValue, StructValue},
-        AddressSpace, IntPredicate, OptimizationLevel,
-    },
-    nac3parser::ast::{Expr, ExprKind, Located, Stmt, StmtKind, StrRef},
-    symbol_resolver::ValueEnum,
-    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId, GenCall},
-    typecheck::typedef::{iter_type_vars, FunSignature, FuncArg, Type, TypeEnum, VarMap},
-};
-
-use super::{symbol_resolver::InnerResolver, timeline::TimeFns};
-
 /// The parallelism mode within a block.
 #[derive(Copy, Clone, Eq, PartialEq)]
 enum ParallelMode {
@ -454,55 +453,41 @@ fn format_rpc_arg<'ctx>(
            // NAC3: NDArray = { usize, usize*, T* }
            // libproto_artiq: NDArray = [data[..], dim_sz[..]]

-            let llvm_i1 = ctx.ctx.bool_type();
-            let llvm_usize = generator.get_size_type(ctx.ctx);
+            let ndarray = AnyObject { ty: arg_ty, value: arg };
+            let ndarray = NDArrayObject::from_object(generator, ctx, ndarray);

-            let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, arg_ty);
-            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-            let llvm_arg_ty = NDArrayType::new(generator, ctx.ctx, llvm_elem_ty);
-            let llvm_arg = NDArrayValue::from_ptr_val(arg.into_pointer_value(), llvm_usize, None);
+            let dtype = ctx.get_llvm_type(generator, ndarray.dtype);
+            let ndims = ndarray.ndims_llvm(generator, ctx.ctx);

-            let llvm_usize_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(llvm_arg_ty.size_type().size_of(), llvm_usize, "")
-                .unwrap();
-            let llvm_pdata_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(
-                    llvm_elem_ty.ptr_type(AddressSpace::default()).size_of(),
-                    llvm_usize,
-                    "",
-                )
-                .unwrap();
+            // `ndarray.data` is possibly not contiguous. We need to force it to be continuous,
+            // and we might have to copy the whole ndarray.
+            let carray = ndarray.make_contiguous_ndarray(generator, ctx, Any(dtype));

-            let dims_buf_sz =
-                ctx.builder.build_int_mul(llvm_arg.load_ndims(ctx), llvm_usize_sizeof, "").unwrap();
+            let sizeof_sizet = Int(SizeT).sizeof(generator, ctx.ctx);
+            let sizeof_sizet = Int(SizeT).truncate_or_bit_cast(generator, ctx, sizeof_sizet);

-            let buffer_size =
-                ctx.builder.build_int_add(dims_buf_sz, llvm_pdata_sizeof, "").unwrap();
+            let sizeof_pdata = Ptr(Any(dtype)).sizeof(generator, ctx.ctx);
+            let sizeof_pdata = Int(SizeT).truncate_or_bit_cast(generator, ctx, sizeof_pdata);

-            let buffer = ctx.builder.build_array_alloca(llvm_i8, buffer_size, "rpc.arg").unwrap();
-            let buffer = ArraySliceValue::from_ptr_val(buffer, buffer_size, Some("rpc.arg"));
+            let sizeof_buf_shape = sizeof_sizet.mul(ctx, ndims);
+            let sizeof_buf = sizeof_buf_shape.add(ctx, sizeof_pdata);

-            call_memcpy_generic(
-                ctx,
-                buffer.base_ptr(ctx, generator),
-                llvm_arg.ptr_to_data(ctx),
-                llvm_pdata_sizeof,
-                llvm_i1.const_zero(),
-            );
+            // buf = { data: void*, shape: [size_t; ndims]; }
+            let buf = Int(Byte).array_alloca(generator, ctx, sizeof_buf.value);
+            let buf_data = buf;
+            let buf_shape = buf_data.offset(ctx, sizeof_pdata.value);

-            let pbuffer_dims_begin =
-                unsafe { buffer.ptr_offset_unchecked(ctx, generator, &llvm_pdata_sizeof, None) };
-            call_memcpy_generic(
-                ctx,
-                pbuffer_dims_begin,
-                llvm_arg.dim_sizes().base_ptr(ctx, generator),
-                dims_buf_sz,
-                llvm_i1.const_zero(),
-            );
+            // Write to `buf->data`
+            let carray_data = carray.get(generator, ctx, |f| f.data); // has type Ptr<Any>
+            let carray_data = carray_data.pointer_cast(generator, ctx, Int(Byte));
+            buf_data.copy_from(generator, ctx, carray_data, sizeof_pdata.value);

-            buffer.base_ptr(ctx, generator)
+            // Write to `buf->shape`
+            let carray_shape = ndarray.instance.get(generator, ctx, |f| f.shape);
+            let carray_shape_i8 = carray_shape.pointer_cast(generator, ctx, Int(Byte));
+            buf_shape.copy_from(generator, ctx, carray_shape_i8, sizeof_buf_shape.value);
+
+            buf.value
        }

        _ => {
@ -512,7 +497,7 @@ fn format_rpc_arg<'ctx>(
            ctx.builder.build_store(arg_slot, arg).unwrap();

            ctx.builder
-                .build_bit_cast(arg_slot, llvm_pi8, "rpc.arg")
+                .build_bitcast(arg_slot, llvm_pi8, "rpc.arg")
                .map(BasicValueEnum::into_pointer_value)
                .unwrap()
        }
@ -523,305 +508,12 @@ fn format_rpc_arg<'ctx>(
    arg_slot
 }

-/// Formats an RPC return value to conform to the expected format required by NAC3.
-fn format_rpc_ret<'ctx>(
-    generator: &mut dyn CodeGenerator,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    ret_ty: Type,
-) -> Option<BasicValueEnum<'ctx>> {
-    // -- receive value:
-    // T result = {
-    //   void *ret_ptr = alloca(sizeof(T));
-    //   void *ptr = ret_ptr;
-    //   loop: int size = rpc_recv(ptr);
-    //   // Non-zero: Provide `size` bytes of extra storage for variable-length data.
-    //   if(size) { ptr = alloca(size); goto loop; }
-    //   else *(T*)ret_ptr
-    // }
-
-    let llvm_i8 = ctx.ctx.i8_type();
-    let llvm_i32 = ctx.ctx.i32_type();
-    let llvm_i8_8 = ctx.ctx.struct_type(&[llvm_i8.array_type(8).into()], false);
-    let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
-
-    let rpc_recv = ctx.module.get_function("rpc_recv").unwrap_or_else(|| {
-        ctx.module.add_function("rpc_recv", llvm_i32.fn_type(&[llvm_pi8.into()], false), None)
-    });
-
-    if ctx.unifier.unioned(ret_ty, ctx.primitives.none) {
-        ctx.build_call_or_invoke(rpc_recv, &[llvm_pi8.const_null().into()], "rpc_recv");
-        return None;
-    }
-
-    let prehead_bb = ctx.builder.get_insert_block().unwrap();
-    let current_function = prehead_bb.get_parent().unwrap();
-    let head_bb = ctx.ctx.append_basic_block(current_function, "rpc.head");
-    let alloc_bb = ctx.ctx.append_basic_block(current_function, "rpc.continue");
-    let tail_bb = ctx.ctx.append_basic_block(current_function, "rpc.tail");
-
-    let llvm_ret_ty = ctx.get_llvm_abi_type(generator, ret_ty);
-
-    let result = match &*ctx.unifier.get_ty_immutable(ret_ty) {
-        TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-            let llvm_i1 = ctx.ctx.bool_type();
-            let llvm_usize = generator.get_size_type(ctx.ctx);
-
-            // Round `val` up to its modulo `power_of_two`
-            let round_up = |ctx: &mut CodeGenContext<'ctx, '_>,
-                            val: IntValue<'ctx>,
-                            power_of_two: IntValue<'ctx>| {
-                debug_assert_eq!(
-                    val.get_type().get_bit_width(),
-                    power_of_two.get_type().get_bit_width()
-                );
-
-                let llvm_val_t = val.get_type();
-
-                let max_rem = ctx
-                    .builder
-                    .build_int_sub(power_of_two, llvm_val_t.const_int(1, false), "")
-                    .unwrap();
-                ctx.builder
-                    .build_and(
-                        ctx.builder.build_int_add(val, max_rem, "").unwrap(),
-                        ctx.builder.build_not(max_rem, "").unwrap(),
-                        "",
-                    )
-                    .unwrap()
-            };
-
-            // Setup types
-            let (elem_ty, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, ret_ty);
-            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-            let llvm_ret_ty = NDArrayType::new(generator, ctx.ctx, llvm_elem_ty);
-
-            // Allocate the resulting ndarray
-            // A condition after format_rpc_ret ensures this will not be popped this off.
-            let ndarray = llvm_ret_ty.new_value(generator, ctx, Some("rpc.result"));
-
-            // Setup ndims
-            let ndims =
-                if let TypeEnum::TLiteral { values, .. } = &*ctx.unifier.get_ty_immutable(ndims) {
-                    assert_eq!(values.len(), 1);
-
-                    u64::try_from(values[0].clone()).unwrap()
-                } else {
-                    unreachable!();
-                };
-            // Set `ndarray.ndims`
-            ndarray.store_ndims(ctx, generator, llvm_usize.const_int(ndims, false));
-            // Allocate `ndarray.shape` [size_t; ndims]
-            ndarray.create_dim_sizes(ctx, llvm_usize, ndarray.load_ndims(ctx));
-
-            /*
-                ndarray now:
-                  - .ndims: initialized
-                  - .shape: allocated but uninitialized .shape
-                  - .data: uninitialized
-            */
-
-            let llvm_usize_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(llvm_usize.size_of(), llvm_usize, "")
-                .unwrap();
-            let llvm_pdata_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(
-                    llvm_elem_ty.ptr_type(AddressSpace::default()).size_of(),
-                    llvm_usize,
-                    "",
-                )
-                .unwrap();
-            let llvm_elem_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(llvm_elem_ty.size_of().unwrap(), llvm_usize, "")
-                .unwrap();
-
-            // Allocates a buffer for the initial RPC'ed object, which is guaranteed to be
-            // (4 + 4 * ndims) bytes with 8-byte alignment
-            let sizeof_dims =
-                ctx.builder.build_int_mul(ndarray.load_ndims(ctx), llvm_usize_sizeof, "").unwrap();
-            let unaligned_buffer_size =
-                ctx.builder.build_int_add(sizeof_dims, llvm_pdata_sizeof, "").unwrap();
-            let buffer_size = round_up(ctx, unaligned_buffer_size, llvm_usize.const_int(8, false));
-
-            let stackptr = call_stacksave(ctx, None);
-            // Just to be absolutely sure, alloca in [i8 x 8] slices to force 8-byte alignment
-            let buffer = ctx
-                .builder
-                .build_array_alloca(
-                    llvm_i8_8,
-                    ctx.builder
-                        .build_int_unsigned_div(buffer_size, llvm_usize.const_int(8, false), "")
-                        .unwrap(),
-                    "rpc.buffer",
-                )
-                .unwrap();
-            let buffer = ctx
-                .builder
-                .build_bit_cast(buffer, llvm_pi8, "")
-                .map(BasicValueEnum::into_pointer_value)
-                .unwrap();
-            let buffer = ArraySliceValue::from_ptr_val(buffer, buffer_size, None);
-
-            // The first call to `rpc_recv` reads the top-level ndarray object: [pdata, shape]
-            //
-            // The returned value is the number of bytes for `ndarray.data`.
-            let ndarray_nbytes = ctx
-                .build_call_or_invoke(
-                    rpc_recv,
-                    &[buffer.base_ptr(ctx, generator).into()], // Reads [usize; ndims]. NOTE: We are allocated [size_t; ndims].
-                    "rpc.size.next",
-                )
-                .map(BasicValueEnum::into_int_value)
-                .unwrap();
-
-            // debug_assert(ndarray_nbytes > 0)
-            if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
-                ctx.make_assert(
-                    generator,
-                    ctx.builder
-                        .build_int_compare(
-                            IntPredicate::UGT,
-                            ndarray_nbytes,
-                            ndarray_nbytes.get_type().const_zero(),
-                            "",
-                        )
-                        .unwrap(),
-                    "0:AssertionError",
-                    "Unexpected RPC termination for ndarray - Expected data buffer next",
-                    [None, None, None],
-                    ctx.current_loc,
-                );
-            }
-
-            // Copy shape from the buffer to `ndarray.shape`.
-            let pbuffer_dims =
-                unsafe { buffer.ptr_offset_unchecked(ctx, generator, &llvm_pdata_sizeof, None) };
-
-            call_memcpy_generic(
-                ctx,
-                ndarray.dim_sizes().base_ptr(ctx, generator),
-                pbuffer_dims,
-                sizeof_dims,
-                llvm_i1.const_zero(),
-            );
-            // Restore stack from before allocation of buffer
-            call_stackrestore(ctx, stackptr);
-
-            // Allocate `ndarray.data`.
-            // `ndarray.shape` must be initialized beforehand in this implementation
-            //   (for ndarray.create_data() to know how many elements to allocate)
-            let num_elements =
-                call_ndarray_calc_size(generator, ctx, &ndarray.dim_sizes(), (None, None));
-
-            // debug_assert(nelems * sizeof(T) >= ndarray_nbytes)
-            if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
-                let sizeof_data =
-                    ctx.builder.build_int_mul(num_elements, llvm_elem_sizeof, "").unwrap();
-
-                ctx.make_assert(
-                    generator,
-                    ctx.builder.build_int_compare(IntPredicate::UGE,
-                        sizeof_data,
-                        ndarray_nbytes,
-                        "",
-                    ).unwrap(),
-                    "0:AssertionError",
-                    "Unexpected allocation size request for ndarray data - Expected up to {0} bytes, got {1} bytes",
-                    [Some(sizeof_data), Some(ndarray_nbytes), None],
-                    ctx.current_loc,
-                );
-            }
-
-            ndarray.create_data(ctx, llvm_elem_ty, num_elements);
-
-            let ndarray_data = ndarray.data().base_ptr(ctx, generator);
-            let ndarray_data_i8 =
-                ctx.builder.build_pointer_cast(ndarray_data, llvm_pi8, "").unwrap();
-
-            // NOTE: Currently on `prehead_bb`
-            ctx.builder.build_unconditional_branch(head_bb).unwrap();
-
-            // Inserting into `head_bb`. Do `rpc_recv` for `data` recursively.
-            ctx.builder.position_at_end(head_bb);
-
-            let phi = ctx.builder.build_phi(llvm_pi8, "rpc.ptr").unwrap();
-            phi.add_incoming(&[(&ndarray_data_i8, prehead_bb)]);
-
-            let alloc_size = ctx
-                .build_call_or_invoke(rpc_recv, &[phi.as_basic_value()], "rpc.size.next")
-                .map(BasicValueEnum::into_int_value)
-                .unwrap();
-
-            let is_done = ctx
-                .builder
-                .build_int_compare(IntPredicate::EQ, llvm_i32.const_zero(), alloc_size, "rpc.done")
-                .unwrap();
-            ctx.builder.build_conditional_branch(is_done, tail_bb, alloc_bb).unwrap();
-
-            ctx.builder.position_at_end(alloc_bb);
-            // Align the allocation to sizeof(T)
-            let alloc_size = round_up(ctx, alloc_size, llvm_elem_sizeof);
-            let alloc_ptr = ctx
-                .builder
-                .build_array_alloca(
-                    llvm_elem_ty,
-                    ctx.builder.build_int_unsigned_div(alloc_size, llvm_elem_sizeof, "").unwrap(),
-                    "rpc.alloc",
-                )
-                .unwrap();
-            let alloc_ptr =
-                ctx.builder.build_pointer_cast(alloc_ptr, llvm_pi8, "rpc.alloc.ptr").unwrap();
-            phi.add_incoming(&[(&alloc_ptr, alloc_bb)]);
-            ctx.builder.build_unconditional_branch(head_bb).unwrap();
-
-            ctx.builder.position_at_end(tail_bb);
-            ndarray.as_base_value().into()
-        }
-
-        _ => {
-            let slot = ctx.builder.build_alloca(llvm_ret_ty, "rpc.ret.slot").unwrap();
-            let slotgen = ctx.builder.build_bit_cast(slot, llvm_pi8, "rpc.ret.ptr").unwrap();
-            ctx.builder.build_unconditional_branch(head_bb).unwrap();
-            ctx.builder.position_at_end(head_bb);
-
-            let phi = ctx.builder.build_phi(llvm_pi8, "rpc.ptr").unwrap();
-            phi.add_incoming(&[(&slotgen, prehead_bb)]);
-            let alloc_size = ctx
-                .build_call_or_invoke(rpc_recv, &[phi.as_basic_value()], "rpc.size.next")
-                .unwrap()
-                .into_int_value();
-            let is_done = ctx
-                .builder
-                .build_int_compare(IntPredicate::EQ, llvm_i32.const_zero(), alloc_size, "rpc.done")
-                .unwrap();
-
-            ctx.builder.build_conditional_branch(is_done, tail_bb, alloc_bb).unwrap();
-            ctx.builder.position_at_end(alloc_bb);
-
-            let alloc_ptr =
-                ctx.builder.build_array_alloca(llvm_pi8, alloc_size, "rpc.alloc").unwrap();
-            let alloc_ptr =
-                ctx.builder.build_bit_cast(alloc_ptr, llvm_pi8, "rpc.alloc.ptr").unwrap();
-            phi.add_incoming(&[(&alloc_ptr, alloc_bb)]);
-            ctx.builder.build_unconditional_branch(head_bb).unwrap();
-
-            ctx.builder.position_at_end(tail_bb);
-            ctx.builder.build_load(slot, "rpc.result").unwrap()
-        }
-    };
-
-    Some(result)
-}
-
 fn rpc_codegen_callback_fn<'ctx>(
    ctx: &mut CodeGenContext<'ctx, '_>,
    obj: Option<(Type, ValueEnum<'ctx>)>,
    fun: (&FunSignature, DefinitionId),
    args: Vec<(Option<StrRef>, ValueEnum<'ctx>)>,
    generator: &mut dyn CodeGenerator,
-    is_async: bool,
 ) -> Result<Option<BasicValueEnum<'ctx>>, String> {
    let int8 = ctx.ctx.i8_type();
    let int32 = ctx.ctx.i32_type();
@ -930,64 +622,84 @@ fn rpc_codegen_callback_fn<'ctx>(
    }

    // call
-    if is_async {
-        let rpc_send_async = ctx.module.get_function("rpc_send_async").unwrap_or_else(|| {
-            ctx.module.add_function(
-                "rpc_send_async",
-                ctx.ctx.void_type().fn_type(
-                    &[
-                        int32.into(),
-                        tag_ptr_type.ptr_type(AddressSpace::default()).into(),
-                        ptr_type.ptr_type(AddressSpace::default()).into(),
-                    ],
-                    false,
-                ),
-                None,
-            )
-        });
-        ctx.builder
-            .build_call(
-                rpc_send_async,
-                &[service_id.into(), tag_ptr.into(), args_ptr.into()],
-                "rpc.send",
-            )
-            .unwrap();
-    } else {
-        let rpc_send = ctx.module.get_function("rpc_send").unwrap_or_else(|| {
-            ctx.module.add_function(
-                "rpc_send",
-                ctx.ctx.void_type().fn_type(
-                    &[
-                        int32.into(),
-                        tag_ptr_type.ptr_type(AddressSpace::default()).into(),
-                        ptr_type.ptr_type(AddressSpace::default()).into(),
-                    ],
-                    false,
-                ),
-                None,
-            )
-        });
-        ctx.builder
-            .build_call(rpc_send, &[service_id.into(), tag_ptr.into(), args_ptr.into()], "rpc.send")
-            .unwrap();
-    }
+    let rpc_send = ctx.module.get_function("rpc_send").unwrap_or_else(|| {
+        ctx.module.add_function(
+            "rpc_send",
+            ctx.ctx.void_type().fn_type(
+                &[
+                    int32.into(),
+                    tag_ptr_type.ptr_type(AddressSpace::default()).into(),
+                    ptr_type.ptr_type(AddressSpace::default()).into(),
+                ],
+                false,
+            ),
+            None,
+        )
+    });
+    ctx.builder
+        .build_call(rpc_send, &[service_id.into(), tag_ptr.into(), args_ptr.into()], "rpc.send")
+        .unwrap();

    // reclaim stack space used by arguments
    call_stackrestore(ctx, stackptr);

-    if is_async {
-        // async RPCs do not return any values
-        Ok(None)
-    } else {
-        let result = format_rpc_ret(generator, ctx, fun.0.ret);
+    // -- receive value:
+    // T result = {
+    //   void *ret_ptr = alloca(sizeof(T));
+    //   void *ptr = ret_ptr;
+    //   loop: int size = rpc_recv(ptr);
+    //   // Non-zero: Provide `size` bytes of extra storage for variable-length data.
+    //   if(size) { ptr = alloca(size); goto loop; }
+    //   else *(T*)ret_ptr
+    // }
+    let rpc_recv = ctx.module.get_function("rpc_recv").unwrap_or_else(|| {
+        ctx.module.add_function("rpc_recv", int32.fn_type(&[ptr_type.into()], false), None)
+    });

-        if !result.is_some_and(|res| res.get_type().is_pointer_type()) {
-            // An RPC returning an NDArray would not touch here.
-            call_stackrestore(ctx, stackptr);
-        }
-
-        Ok(result)
+    if ctx.unifier.unioned(fun.0.ret, ctx.primitives.none) {
+        ctx.build_call_or_invoke(rpc_recv, &[ptr_type.const_null().into()], "rpc_recv");
+        return Ok(None);
    }
+
+    let prehead_bb = ctx.builder.get_insert_block().unwrap();
+    let current_function = prehead_bb.get_parent().unwrap();
+    let head_bb = ctx.ctx.append_basic_block(current_function, "rpc.head");
+    let alloc_bb = ctx.ctx.append_basic_block(current_function, "rpc.continue");
+    let tail_bb = ctx.ctx.append_basic_block(current_function, "rpc.tail");
+
+    let ret_ty = ctx.get_llvm_abi_type(generator, fun.0.ret);
+    let need_load = !ret_ty.is_pointer_type();
+    let slot = ctx.builder.build_alloca(ret_ty, "rpc.ret.slot").unwrap();
+    let slotgen = ctx.builder.build_bitcast(slot, ptr_type, "rpc.ret.ptr").unwrap();
+    ctx.builder.build_unconditional_branch(head_bb).unwrap();
+    ctx.builder.position_at_end(head_bb);
+
+    let phi = ctx.builder.build_phi(ptr_type, "rpc.ptr").unwrap();
+    phi.add_incoming(&[(&slotgen, prehead_bb)]);
+    let alloc_size = ctx
+        .build_call_or_invoke(rpc_recv, &[phi.as_basic_value()], "rpc.size.next")
+        .unwrap()
+        .into_int_value();
+    let is_done = ctx
+        .builder
+        .build_int_compare(inkwell::IntPredicate::EQ, int32.const_zero(), alloc_size, "rpc.done")
+        .unwrap();
+
+    ctx.builder.build_conditional_branch(is_done, tail_bb, alloc_bb).unwrap();
+    ctx.builder.position_at_end(alloc_bb);
+
+    let alloc_ptr = ctx.builder.build_array_alloca(ptr_type, alloc_size, "rpc.alloc").unwrap();
+    let alloc_ptr = ctx.builder.build_bitcast(alloc_ptr, ptr_type, "rpc.alloc.ptr").unwrap();
+    phi.add_incoming(&[(&alloc_ptr, alloc_bb)]);
+    ctx.builder.build_unconditional_branch(head_bb).unwrap();
+
+    ctx.builder.position_at_end(tail_bb);
+
+    let result = ctx.builder.build_load(slot, "rpc.result").unwrap();
+    if need_load {
+        call_stackrestore(ctx, stackptr);
+    }
+    Ok(Some(result))
 }

 pub fn attributes_writeback(
@ -1082,7 +794,7 @@ pub fn attributes_writeback(
        let args: Vec<_> =
            values.into_iter().map(|(_, val)| (None, ValueEnum::Dynamic(val))).collect();
        if let Err(e) =
-            rpc_codegen_callback_fn(ctx, None, (&fun, PrimDef::Int32.id()), args, generator, false)
+            rpc_codegen_callback_fn(ctx, None, (&fun, PrimDef::Int32.id()), args, generator)
        {
            return Ok(Err(e));
        }
@ -1092,9 +804,9 @@ pub fn attributes_writeback(
    Ok(())
 }

-pub fn rpc_codegen_callback(is_async: bool) -> Arc<GenCall> {
-    Arc::new(GenCall::new(Box::new(move |ctx, obj, fun, args, generator| {
-        rpc_codegen_callback_fn(ctx, obj, fun, args, generator, is_async)
+pub fn rpc_codegen_callback() -> Arc<GenCall> {
+    Arc::new(GenCall::new(Box::new(|ctx, obj, fun, args, generator| {
+        rpc_codegen_callback_fn(ctx, obj, fun, args, generator)
    })))
 }

@ -1302,14 +1014,16 @@ fn polymorphic_print<'ctx>(
                args.extend(&[str_len.into(), str_data.into()]);
            }

-            TypeEnum::TObj { obj_id, params, .. } if *obj_id == PrimDef::List.id() => {
-                let elem_ty = *params.iter().next().unwrap().1;
-
+            TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::List.id() => {
                fmt.push('[');
                flush(ctx, generator, &mut fmt, &mut args);

-                let val = ListValue::from_ptr_val(value.into_pointer_value(), llvm_usize, None);
-                let len = val.load_size(ctx, None);
+                let list = AnyObject { ty, value };
+                let list = ListObject::from_object(generator, ctx, list);
+
+                let items = list.instance.get(generator, ctx, |f| f.items);
+
+                let len = list.instance.get(generator, ctx, |f| f.len).value;
                let last =
                    ctx.builder.build_int_sub(len, llvm_usize.const_int(1, false), "").unwrap();

@ -1320,12 +1034,12 @@ fn polymorphic_print<'ctx>(
                    llvm_usize.const_zero(),
                    (len, false),
                    |generator, ctx, _, i| {
-                        let elem = unsafe { val.data().get_unchecked(ctx, generator, &i, None) };
+                        let item = items.get_index(generator, ctx, i).value;

                        polymorphic_print(
                            ctx,
                            generator,
-                            &[(elem_ty, elem.into())],
+                            &[(list.item_type, item.into())],
                            "",
                            None,
                            true,
@ -1359,56 +1073,46 @@ fn polymorphic_print<'ctx>(
            }

            TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-                let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
-
                fmt.push_str("array([");
                flush(ctx, generator, &mut fmt, &mut args);

-                let val = NDArrayValue::from_ptr_val(value.into_pointer_value(), llvm_usize, None);
-                let len = call_ndarray_calc_size(generator, ctx, &val.dim_sizes(), (None, None));
-                let last =
-                    ctx.builder.build_int_sub(len, llvm_usize.const_int(1, false), "").unwrap();
+                let ndarray = AnyObject { ty, value };
+                let ndarray = NDArrayObject::from_object(generator, ctx, ndarray);

-                gen_for_callback_incrementing(
-                    generator,
-                    ctx,
-                    None,
-                    llvm_usize.const_zero(),
-                    (len, false),
-                    |generator, ctx, _, i| {
-                        let elem = unsafe { val.data().get_unchecked(ctx, generator, &i, None) };
+                let num_0 = Int(SizeT).const_0(generator, ctx.ctx);

-                        polymorphic_print(
-                            ctx,
-                            generator,
-                            &[(elem_ty, elem.into())],
-                            "",
-                            None,
-                            true,
-                            as_rtio,
-                        )?;
+                // Print `ndarray` as a flat list delimited by interspersed with ", \0"
+                ndarray.foreach(generator, ctx, |generator, ctx, _, hdl| {
+                    let i = hdl.get_index(generator, ctx);
+                    let scalar = hdl.get_scalar(generator, ctx);

-                        gen_if_callback(
-                            generator,
-                            ctx,
-                            |_, ctx| {
-                                Ok(ctx
-                                    .builder
-                                    .build_int_compare(IntPredicate::ULT, i, last, "")
-                                    .unwrap())
-                            },
-                            |generator, ctx| {
-                                printf(ctx, generator, ", \0".into(), Vec::default());
+                    // if (i != 0) { puts(", "); }
+                    gen_if_callback(
+                        generator,
+                        ctx,
+                        |_, ctx| {
+                            let not_first = i.compare(ctx, IntPredicate::NE, num_0);
+                            Ok(not_first.value)
+                        },
+                        |generator, ctx| {
+                            printf(ctx, generator, ", \0".into(), Vec::default());
+                            Ok(())
+                        },
+                        |_, _| Ok(()),
+                    )?;

-                                Ok(())
-                            },
-                            |_, _| Ok(()),
-                        )?;
-
-                        Ok(())
-                    },
-                    llvm_usize.const_int(1, false),
-                )?;
+                    // Print element
+                    polymorphic_print(
+                        ctx,
+                        generator,
+                        &[(scalar.ty, scalar.value.into())],
+                        "",
+                        None,
+                        true,
+                        as_rtio,
+                    )?;
+                    Ok(())
+                })?;

                fmt.push_str(")]");
                flush(ctx, generator, &mut fmt, &mut args);
@ -1418,9 +1122,13 @@ fn polymorphic_print<'ctx>(
                fmt.push_str("range(");
                flush(ctx, generator, &mut fmt, &mut args);

-                let val = RangeValue::from_ptr_val(value.into_pointer_value(), None);
+                let range = AnyObject { ty, value };
+                let range = RangeObject::from_object(generator, ctx, range);

-                let (start, stop, step) = destructure_range(ctx, val);
+                let (start, stop, step) = range.instance.destructure(generator, ctx);
+                let start = start.value;
+                let stop = stop.value;
+                let step = step.value;

                polymorphic_print(
                    ctx,
--- a/nac3artiq/src/lib.rs
+++ b/nac3artiq/src/lib.rs
@ -16,65 +16,65 @@
    clippy::wildcard_imports
 )]

-use std::{
-    collections::{HashMap, HashSet},
-    fs,
-    io::Write,
-    process::Command,
-    rc::Rc,
-    sync::Arc,
-};
+use std::collections::{HashMap, HashSet};
+use std::fs;
+use std::io::Write;
+use std::process::Command;
+use std::rc::Rc;
+use std::sync::Arc;

-use itertools::Itertools;
-use parking_lot::{Mutex, RwLock};
-use pyo3::{
-    create_exception, exceptions,
-    prelude::*,
-    types::{PyBytes, PyDict, PySet},
+use inkwell::{
+    context::Context,
+    memory_buffer::MemoryBuffer,
+    module::{Linkage, Module},
+    passes::PassBuilderOptions,
+    support::is_multithreaded,
+    targets::*,
+    OptimizationLevel,
 };
-use tempfile::{self, TempDir};
+use itertools::Itertools;
+use nac3core::codegen::irrt::setup_irrt_exceptions;
+use nac3core::codegen::{gen_func_impl, CodeGenLLVMOptions, CodeGenTargetMachineOptions};
+use nac3core::toplevel::builtins::get_exn_constructor;
+use nac3core::typecheck::typedef::{into_var_map, TypeEnum, Unifier, VarMap};
+use nac3parser::{
+    ast::{ExprKind, Stmt, StmtKind, StrRef},
+    parser::parse_program,
+};
+use pyo3::create_exception;
+use pyo3::prelude::*;
+use pyo3::{exceptions, types::PyBytes, types::PyDict, types::PySet};
+
+use parking_lot::{Mutex, RwLock};

 use nac3core::{
-    codegen::{
-        concrete_type::ConcreteTypeStore, gen_func_impl, irrt::load_irrt, CodeGenLLVMOptions,
-        CodeGenTargetMachineOptions, CodeGenTask, WithCall, WorkerRegistry,
-    },
-    inkwell::{
-        context::Context,
-        memory_buffer::MemoryBuffer,
-        module::{Linkage, Module},
-        passes::PassBuilderOptions,
-        support::is_multithreaded,
-        targets::*,
-        OptimizationLevel,
-    },
-    nac3parser::{
-        ast::{Constant, ExprKind, Located, Stmt, StmtKind, StrRef},
-        parser::parse_program,
-    },
+    codegen::irrt::load_irrt,
+    codegen::{concrete_type::ConcreteTypeStore, CodeGenTask, WithCall, WorkerRegistry},
    symbol_resolver::SymbolResolver,
    toplevel::{
-        builtins::get_exn_constructor,
        composer::{BuiltinFuncCreator, BuiltinFuncSpec, ComposerConfig, TopLevelComposer},
        DefinitionId, GenCall, TopLevelDef,
    },
-    typecheck::{
-        type_inferencer::PrimitiveStore,
-        typedef::{into_var_map, FunSignature, FuncArg, Type, TypeEnum, Unifier, VarMap},
-    },
+    typecheck::typedef::{FunSignature, FuncArg},
+    typecheck::{type_inferencer::PrimitiveStore, typedef::Type},
 };
+
 use nac3ld::Linker;

-use codegen::{
-    attributes_writeback, gen_core_log, gen_rtio_log, rpc_codegen_callback, ArtiqCodeGenerator,
+use crate::{
+    codegen::{
+        attributes_writeback, gen_core_log, gen_rtio_log, rpc_codegen_callback, ArtiqCodeGenerator,
+    },
+    symbol_resolver::{DeferredEvaluationStore, InnerResolver, PythonHelper, Resolver},
 };
-use symbol_resolver::{DeferredEvaluationStore, InnerResolver, PythonHelper, Resolver};
-use timeline::TimeFns;
+use tempfile::{self, TempDir};

 mod codegen;
 mod symbol_resolver;
 mod timeline;

+use timeline::TimeFns;
+
 #[derive(PartialEq, Clone, Copy)]
 enum Isa {
    Host,
@ -195,8 +195,10 @@ impl Nac3 {
                    body.retain(|stmt| {
                        if let StmtKind::FunctionDef { ref decorator_list, .. } = stmt.node {
                            decorator_list.iter().any(|decorator| {
-                                if let Some(id) = decorator_id_string(decorator) {
-                                    id == "kernel" || id == "portable" || id == "rpc"
+                                if let ExprKind::Name { id, .. } = decorator.node {
+                                    id.to_string() == "kernel"
+                                        || id.to_string() == "portable"
+                                        || id.to_string() == "rpc"
                                } else {
                                    false
                                }
@ -209,8 +211,9 @@ impl Nac3 {
                }
                StmtKind::FunctionDef { ref decorator_list, .. } => {
                    decorator_list.iter().any(|decorator| {
-                        if let Some(id) = decorator_id_string(decorator) {
-                            id == "extern" || id == "kernel" || id == "portable" || id == "rpc"
+                        if let ExprKind::Name { id, .. } = decorator.node {
+                            let id = id.to_string();
+                            id == "extern" || id == "portable" || id == "kernel" || id == "rpc"
                        } else {
                            false
                        }
@ -446,6 +449,7 @@ impl Nac3 {
                        pyid_to_type: pyid_to_type.clone(),
                        primitive_ids: self.primitive_ids.clone(),
                        global_value_ids: global_value_ids.clone(),
+                        class_names: Mutex::default(),
                        name_to_pyid: name_to_pyid.clone(),
                        module: module.clone(),
                        id_to_pyval: RwLock::default(),
@ -476,25 +480,9 @@ impl Nac3 {

            match &stmt.node {
                StmtKind::FunctionDef { decorator_list, .. } => {
-                    if decorator_list
-                        .iter()
-                        .any(|decorator| decorator_id_string(decorator) == Some("rpc".to_string()))
-                    {
-                        store_fun
-                            .call1(
-                                py,
-                                (
-                                    def_id.0.into_py(py),
-                                    module.getattr(py, name.to_string().as_str()).unwrap(),
-                                ),
-                            )
-                            .unwrap();
-                        let is_async = decorator_list.iter().any(|decorator| {
-                            decorator_get_flags(decorator)
-                                .iter()
-                                .any(|constant| *constant == Constant::Str("async".into()))
-                        });
-                        rpc_ids.push((None, def_id, is_async));
+                    if decorator_list.iter().any(|decorator| matches!(decorator.node, ExprKind::Name { id, .. } if id == "rpc".into())) {
+                        store_fun.call1(py, (def_id.0.into_py(py), module.getattr(py, name.to_string().as_str()).unwrap())).unwrap();
+                        rpc_ids.push((None, def_id));
                    }
                }
                StmtKind::ClassDef { name, body, .. } => {
@ -502,26 +490,19 @@ impl Nac3 {
                    let class_obj = module.getattr(py, class_name.as_str()).unwrap();
                    for stmt in body {
                        if let StmtKind::FunctionDef { name, decorator_list, .. } = &stmt.node {
-                            if decorator_list.iter().any(|decorator| {
-                                decorator_id_string(decorator) == Some("rpc".to_string())
-                            }) {
-                                let is_async = decorator_list.iter().any(|decorator| {
-                                    decorator_get_flags(decorator)
-                                        .iter()
-                                        .any(|constant| *constant == Constant::Str("async".into()))
-                                });
+                            if decorator_list.iter().any(|decorator| matches!(decorator.node, ExprKind::Name { id, .. } if id == "rpc".into())) {
                                if name == &"__init__".into() {
                                    return Err(CompileError::new_err(format!(
                                        "compilation failed\n----------\nThe constructor of class {} should not be decorated with rpc decorator (at {})",
                                        class_name, stmt.location
                                    )));
                                }
-                                rpc_ids.push((Some((class_obj.clone(), *name)), def_id, is_async));
+                                rpc_ids.push((Some((class_obj.clone(), *name)), def_id));
                            }
                        }
                    }
                }
-                _ => (),
+                _ => ()
            }

            let id = *name_to_pyid.get(&name).unwrap();
@ -560,6 +541,7 @@ impl Nac3 {
            pyid_to_type: pyid_to_type.clone(),
            primitive_ids: self.primitive_ids.clone(),
            global_value_ids: global_value_ids.clone(),
+            class_names: Mutex::default(),
            id_to_pyval: RwLock::default(),
            id_to_primitive: RwLock::default(),
            field_to_val: RwLock::default(),
@ -577,8 +559,9 @@ impl Nac3 {
            .unwrap();

        // Process IRRT
-        let context = Context::create();
-        let irrt = load_irrt(&context, resolver.as_ref());
+        let context = inkwell::context::Context::create();
+        let irrt = load_irrt(&context);
+        setup_irrt_exceptions(&context, &irrt, resolver.as_ref());

        let fun_signature =
            FunSignature { args: vec![], ret: self.primitive.none, vars: VarMap::new() };
@ -617,12 +600,13 @@ impl Nac3 {
        let top_level = Arc::new(composer.make_top_level_context());

        {
+            let rpc_codegen = rpc_codegen_callback();
            let defs = top_level.definitions.read();
-            for (class_data, id, is_async) in &rpc_ids {
+            for (class_data, id) in &rpc_ids {
                let mut def = defs[id.0].write();
                match &mut *def {
                    TopLevelDef::Function { codegen_callback, .. } => {
-                        *codegen_callback = Some(rpc_codegen_callback(*is_async));
+                        *codegen_callback = Some(rpc_codegen.clone());
                    }
                    TopLevelDef::Class { methods, .. } => {
                        let (class_def, method_name) = class_data.as_ref().unwrap();
@ -633,7 +617,7 @@ impl Nac3 {
                            if let TopLevelDef::Function { codegen_callback, .. } =
                                &mut *defs[id.0].write()
                            {
-                                *codegen_callback = Some(rpc_codegen_callback(*is_async));
+                                *codegen_callback = Some(rpc_codegen.clone());
                                store_fun
                                    .call1(
                                        py,
@ -648,11 +632,6 @@ impl Nac3 {
                            }
                        }
                    }
-                    TopLevelDef::Variable { .. } => {
-                        return Err(CompileError::new_err(String::from(
-                            "Unsupported @rpc annotation on global variable",
-                        )))
-                    }
                }
            }
        }
@ -712,7 +691,7 @@ impl Nac3 {
            let buffer = buffer.as_slice().into();
            membuffer.lock().push(buffer);
        })));
-        let size_t = context
+        let size_t = Context::create()
            .ptr_sized_int_type(&self.get_llvm_target_machine().get_target_data(), None)
            .get_bit_width();
        let num_threads = if is_multithreaded() { 4 } else { 1 };
@ -731,7 +710,7 @@ impl Nac3 {

            let mut generator =
                ArtiqCodeGenerator::new("attributes_writeback".to_string(), size_t, self.time_fns);
-            let context = Context::create();
+            let context = inkwell::context::Context::create();
            let module = context.create_module("attributes_writeback");
            let target_machine = self.llvm_options.create_target_machine().unwrap();
            module.set_data_layout(&target_machine.get_target_data().get_data_layout());
@ -869,41 +848,6 @@ impl Nac3 {
    }
 }

-/// Retrieves the Name.id from a decorator, supports decorators with arguments.
-fn decorator_id_string(decorator: &Located<ExprKind>) -> Option<String> {
-    if let ExprKind::Name { id, .. } = decorator.node {
-        // Bare decorator
-        return Some(id.to_string());
-    } else if let ExprKind::Call { func, .. } = &decorator.node {
-        // Decorators that are calls (e.g. "@rpc()") have Call for the node,
-        // need to extract the id from within.
-        if let ExprKind::Name { id, .. } = func.node {
-            return Some(id.to_string());
-        }
-    }
-    None
-}
-
-/// Retrieves flags from a decorator, if any.
-fn decorator_get_flags(decorator: &Located<ExprKind>) -> Vec<Constant> {
-    let mut flags = vec![];
-    if let ExprKind::Call { keywords, .. } = &decorator.node {
-        for keyword in keywords {
-            if keyword.node.arg != Some("flags".into()) {
-                continue;
-            }
-            if let ExprKind::Set { elts } = &keyword.node.value.node {
-                for elt in elts {
-                    if let ExprKind::Constant { value, .. } = &elt.node {
-                        flags.push(value.clone());
-                    }
-                }
-            }
-        }
-    }
-    flags
-}
-
 fn link_with_lld(elf_filename: String, obj_filename: String) -> PyResult<()> {
    let linker_args = vec![
        "-shared".to_string(),
--- a/nac3artiq/src/symbol_resolver.rs
+++ b/nac3artiq/src/symbol_resolver.rs
@ -1,30 +1,17 @@
-use std::{
-    collections::{HashMap, HashSet},
-    sync::{
-        atomic::{AtomicBool, Ordering::Relaxed},
-        Arc,
-    },
+use crate::PrimitivePythonId;
+use inkwell::{
+    module::Linkage,
+    types::BasicType,
+    values::{BasicValue, BasicValueEnum},
+    AddressSpace,
 };
-
 use itertools::Itertools;
-use parking_lot::RwLock;
-use pyo3::{
-    types::{PyDict, PyTuple},
-    PyAny, PyObject, PyResult, Python,
-};
-
 use nac3core::{
    codegen::{
-        classes::{NDArrayType, ProxyType},
+        model::*,
+        object::ndarray::{make_contiguous_strides, NDArray},
        CodeGenContext, CodeGenerator,
    },
-    inkwell::{
-        module::Linkage,
-        types::{BasicType, BasicTypeEnum},
-        values::BasicValueEnum,
-        AddressSpace,
-    },
-    nac3parser::ast::{self, StrRef},
    symbol_resolver::{StaticValue, SymbolResolver, SymbolValue, ValueEnum},
    toplevel::{
        helper::PrimDef,
@ -36,8 +23,19 @@ use nac3core::{
        typedef::{into_var_map, iter_type_vars, Type, TypeEnum, TypeVar, Unifier, VarMap},
    },
 };
-
-use super::PrimitivePythonId;
+use nac3parser::ast::{self, StrRef};
+use parking_lot::{Mutex, RwLock};
+use pyo3::{
+    types::{PyDict, PyTuple},
+    PyAny, PyErr, PyObject, PyResult, Python,
+};
+use std::{
+    collections::{HashMap, HashSet},
+    sync::{
+        atomic::{AtomicBool, Ordering::Relaxed},
+        Arc,
+    },
+};

 pub enum PrimitiveValue {
    I32(i32),
@ -82,6 +80,7 @@ pub struct InnerResolver {
    pub id_to_primitive: RwLock<HashMap<u64, PrimitiveValue>>,
    pub field_to_val: RwLock<HashMap<ResolverField, Option<PyFieldHandle>>>,
    pub global_value_ids: Arc<RwLock<HashMap<u64, PyObject>>>,
+    pub class_names: Mutex<HashMap<StrRef, Type>>,
    pub pyid_to_def: Arc<RwLock<HashMap<u64, DefinitionId>>>,
    pub pyid_to_type: Arc<RwLock<HashMap<u64, Type>>>,
    pub primitive_ids: PrimitivePythonId,
@ -1088,15 +1087,12 @@ impl InnerResolver {
            let (ndarray_dtype, ndarray_ndims) =
                unpack_ndarray_var_tys(&mut ctx.unifier, ndarray_ty);

-            let llvm_usize = generator.get_size_type(ctx.ctx);
-            let ndarray_dtype_llvm_ty = ctx.get_llvm_type(generator, ndarray_dtype);
-            let ndarray_llvm_ty = NDArrayType::new(generator, ctx.ctx, ndarray_dtype_llvm_ty);
-
+            let dtype = Any(ctx.get_llvm_type(generator, ndarray_dtype));
            {
                if self.global_value_ids.read().contains_key(&id) {
                    let global = ctx.module.get_global(&id_str).unwrap_or_else(|| {
                        ctx.module.add_global(
-                            ndarray_llvm_ty.as_underlying_type(),
+                            Struct(NDArray).get_type(generator, ctx.ctx),
                            Some(AddressSpace::default()),
                            &id_str,
                        )
@ -1116,100 +1112,138 @@ impl InnerResolver {
            } else {
                todo!("Unpacking literal of more than one element unimplemented")
            };
-            let Ok(ndarray_ndims) = u64::try_from(ndarray_ndims) else {
+            let Ok(ndims) = u64::try_from(ndarray_ndims) else {
                unreachable!("Expected u64 value for ndarray_ndims")
            };

            // Obtain the shape of the ndarray
            let shape_tuple: &PyTuple = obj.getattr("shape")?.downcast()?;
-            assert_eq!(shape_tuple.len(), ndarray_ndims as usize);
-            let shape_values: Result<Option<Vec<_>>, _> = shape_tuple
+            assert_eq!(shape_tuple.len(), ndims as usize);
+
+            // The Rust type inferencer cannot figure this out
+            let shape_values: Result<Vec<Instance<'ctx, Int<SizeT>>>, PyErr> = shape_tuple
                .iter()
                .enumerate()
                .map(|(i, elem)| {
-                    self.get_obj_value(py, elem, ctx, generator, ctx.primitives.usize()).map_err(
-                        |e| super::CompileError::new_err(format!("Error getting element {i}: {e}")),
-                    )
+                    let value = self
+                        .get_obj_value(py, elem, ctx, generator, ctx.primitives.usize())
+                        .map_err(|e| {
+                            super::CompileError::new_err(format!("Error getting element {i}: {e}"))
+                        })?
+                        .unwrap();
+                    let value = Int(SizeT).check_value(generator, ctx.ctx, value).unwrap();
+                    Ok(value)
                })
                .collect();
-            let shape_values = shape_values?.unwrap();
-            let shape_values = llvm_usize.const_array(
-                &shape_values.into_iter().map(BasicValueEnum::into_int_value).collect_vec(),
-            );
+            let shape_values = shape_values?;
+
+            // Also use this opportunity to get the constant values of `shape_values` for calculating strides.
+            let shape_u64s = shape_values
+                .iter()
+                .map(|dim| {
+                    assert!(dim.value.is_const());
+                    dim.value.get_zero_extended_constant().unwrap()
+                })
+                .collect_vec();
+            let shape_values = Int(SizeT).const_array(generator, ctx.ctx, &shape_values);

            // create a global for ndarray.shape and initialize it using the shape
            let shape_global = ctx.module.add_global(
-                llvm_usize.array_type(ndarray_ndims as u32),
+                Array { len: AnyLen(ndims as u32), item: Int(SizeT) }.get_type(generator, ctx.ctx),
                Some(AddressSpace::default()),
                &(id_str.clone() + ".shape"),
            );
-            shape_global.set_initializer(&shape_values);
+            shape_global.set_initializer(&shape_values.value);

            // Obtain the (flattened) elements of the ndarray
            let sz: usize = obj.getattr("size")?.extract()?;
-            let data: Result<Option<Vec<_>>, _> = (0..sz)
+            let data_values: Vec<Instance<'ctx, Any>> = (0..sz)
                .map(|i| {
                    obj.getattr("flat")?.get_item(i).and_then(|elem| {
-                        self.get_obj_value(py, elem, ctx, generator, ndarray_dtype).map_err(|e| {
-                            super::CompileError::new_err(format!("Error getting element {i}: {e}"))
-                        })
+                        let value = self
+                            .get_obj_value(py, elem, ctx, generator, ndarray_dtype)
+                            .map_err(|e| {
+                                super::CompileError::new_err(format!(
+                                    "Error getting element {i}: {e}"
+                                ))
+                            })?
+                            .unwrap();
+
+                        let value = dtype.check_value(generator, ctx.ctx, value).unwrap();
+                        Ok(value)
                    })
                })
-                .collect();
-            let data = data?.unwrap().into_iter();
-            let data = match ndarray_dtype_llvm_ty {
-                BasicTypeEnum::ArrayType(ty) => {
-                    ty.const_array(&data.map(BasicValueEnum::into_array_value).collect_vec())
-                }
-
-                BasicTypeEnum::FloatType(ty) => {
-                    ty.const_array(&data.map(BasicValueEnum::into_float_value).collect_vec())
-                }
-
-                BasicTypeEnum::IntType(ty) => {
-                    ty.const_array(&data.map(BasicValueEnum::into_int_value).collect_vec())
-                }
-
-                BasicTypeEnum::PointerType(ty) => {
-                    ty.const_array(&data.map(BasicValueEnum::into_pointer_value).collect_vec())
-                }
-
-                BasicTypeEnum::StructType(ty) => {
-                    ty.const_array(&data.map(BasicValueEnum::into_struct_value).collect_vec())
-                }
-
-                BasicTypeEnum::VectorType(_) => unreachable!(),
-            };
+                .try_collect()?;
+            let data = dtype.const_array(generator, ctx.ctx, &data_values);

            // create a global for ndarray.data and initialize it using the elements
+            //
+            // NOTE: NDArray's `data` is `u8*`. Here, `data_global` is an array of `dtype`.
+            // We will have to cast it to an `u8*` later.
            let data_global = ctx.module.add_global(
-                ndarray_dtype_llvm_ty.array_type(sz as u32),
+                Array { len: AnyLen(sz as u32), item: dtype }.get_type(generator, ctx.ctx),
                Some(AddressSpace::default()),
                &(id_str.clone() + ".data"),
            );
-            data_global.set_initializer(&data);
+            data_global.set_initializer(&data.value);
+
+            // Get the constant itemsize.
+            let itemsize = dtype.get_type(generator, ctx.ctx).size_of().unwrap();
+            let itemsize = itemsize.get_zero_extended_constant().unwrap();
+
+            // Create the strides needed for ndarray.strides
+            let strides = make_contiguous_strides(itemsize, ndims, &shape_u64s);
+            let strides = strides
+                .into_iter()
+                .map(|stride| Int(SizeT).const_int(generator, ctx.ctx, stride))
+                .collect_vec();
+            let strides = Int(SizeT).const_array(generator, ctx.ctx, &strides);
+
+            // create a global for ndarray.strides and initialize it
+            let strides_global = ctx.module.add_global(
+                Array { len: AnyLen(ndims as u32), item: Int(Byte) }.get_type(generator, ctx.ctx),
+                Some(AddressSpace::default()),
+                &(id_str.clone() + ".strides"),
+            );
+            strides_global.set_initializer(&strides.value);

            // create a global for the ndarray object and initialize it
-            let value = ndarray_llvm_ty.as_underlying_type().const_named_struct(&[
-                llvm_usize.const_int(ndarray_ndims, false).into(),
-                shape_global
-                    .as_pointer_value()
-                    .const_cast(llvm_usize.ptr_type(AddressSpace::default()))
-                    .into(),
-                data_global
-                    .as_pointer_value()
-                    .const_cast(ndarray_dtype_llvm_ty.ptr_type(AddressSpace::default()))
-                    .into(),
-            ]);
+            // We are also doing [`Model::check_value`] instead of [`Model::believe_value`] to catch bugs.

-            let ndarray = ctx.module.add_global(
-                ndarray_llvm_ty.as_underlying_type(),
+            // NOTE: data_global is an array of dtype, we want a `u8*`.
+            let ndarray_data = Ptr(dtype).check_value(generator, ctx.ctx, data_global).unwrap();
+            let ndarray_data = Ptr(Int(Byte)).pointer_cast(generator, ctx, ndarray_data.value);
+
+            let ndarray_itemsize = Int(SizeT).const_int(generator, ctx.ctx, itemsize);
+
+            let ndarray_ndims = Int(SizeT).const_int(generator, ctx.ctx, ndims as u64);
+
+            let ndarray_shape =
+                Ptr(Int(SizeT)).check_value(generator, ctx.ctx, shape_global).unwrap();
+
+            let ndarray_strides =
+                Ptr(Int(SizeT)).check_value(generator, ctx.ctx, strides_global).unwrap();
+
+            let ndarray = Struct(NDArray).const_struct(
+                generator,
+                ctx.ctx,
+                &[
+                    ndarray_data.value.as_basic_value_enum(),
+                    ndarray_itemsize.value.as_basic_value_enum(),
+                    ndarray_ndims.value.as_basic_value_enum(),
+                    ndarray_shape.value.as_basic_value_enum(),
+                    ndarray_strides.value.as_basic_value_enum(),
+                ],
+            );
+
+            let ndarray_global = ctx.module.add_global(
+                Struct(NDArray).get_type(generator, ctx.ctx),
                Some(AddressSpace::default()),
                &id_str,
            );
-            ndarray.set_initializer(&value);
+            ndarray_global.set_initializer(&ndarray.value);

-            Ok(Some(ndarray.as_pointer_value().into()))
+            Ok(Some(ndarray_global.as_pointer_value().into()))
        } else if ty_id == self.primitive_ids.tuple {
            let expected_ty_enum = ctx.unifier.get_ty_immutable(expected_ty);
            let TypeEnum::TTuple { ty, is_vararg_ctx: false } = expected_ty_enum.as_ref() else {
@ -1470,7 +1504,6 @@ impl SymbolResolver for Resolver {
        &self,
        id: StrRef,
        _: &mut CodeGenContext<'ctx, '_>,
-        _: &mut dyn CodeGenerator,
    ) -> Option<ValueEnum<'ctx>> {
        let sym_value = {
            let id_to_val = self.0.id_to_pyval.read();
--- a/nac3artiq/src/timeline.rs
+++ b/nac3artiq/src/timeline.rs
@ -1,12 +1,9 @@
-use itertools::Either;
-
-use nac3core::{
-    codegen::CodeGenContext,
-    inkwell::{
-        values::{BasicValueEnum, CallSiteValue},
-        AddressSpace, AtomicOrdering,
-    },
+use inkwell::{
+    values::{BasicValueEnum, CallSiteValue},
+    AddressSpace, AtomicOrdering,
 };
+use itertools::Either;
+use nac3core::codegen::CodeGenContext;

 /// Functions for manipulating the timeline.
 pub trait TimeFns {
@ -34,7 +31,7 @@ impl TimeFns for NowPinningTimeFns64 {
            .unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
        let now_hiptr = ctx
            .builder
-            .build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
+            .build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
            .map(BasicValueEnum::into_pointer_value)
            .unwrap();

@ -83,7 +80,7 @@ impl TimeFns for NowPinningTimeFns64 {
            .unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
        let now_hiptr = ctx
            .builder
-            .build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
+            .build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
            .map(BasicValueEnum::into_pointer_value)
            .unwrap();

@ -112,7 +109,7 @@ impl TimeFns for NowPinningTimeFns64 {
            .unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
        let now_hiptr = ctx
            .builder
-            .build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
+            .build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
            .map(BasicValueEnum::into_pointer_value)
            .unwrap();

@ -210,7 +207,7 @@ impl TimeFns for NowPinningTimeFns {
            .unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
        let now_hiptr = ctx
            .builder
-            .build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
+            .build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
            .map(BasicValueEnum::into_pointer_value)
            .unwrap();

@ -261,7 +258,7 @@ impl TimeFns for NowPinningTimeFns {
        let time_lo = ctx.builder.build_int_truncate(time, i32_type, "time.lo").unwrap();
        let now_hiptr = ctx
            .builder
-            .build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
+            .build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
            .map(BasicValueEnum::into_pointer_value)
            .unwrap();

--- a/nac3ast/Cargo.toml
+++ b/nac3ast/Cargo.toml
@ -10,6 +10,7 @@ constant-optimization = ["fold"]
 fold = []

 [dependencies]
+lazy_static = "1.5"
 parking_lot = "0.12"
 string-interner = "0.17"
 fxhash = "0.2"
--- a/nac3ast/src/ast_gen.rs
+++ b/nac3ast/src/ast_gen.rs
@ -5,12 +5,14 @@ pub use crate::location::Location;

 use fxhash::FxBuildHasher;
 use parking_lot::{Mutex, MutexGuard};
-use std::{cell::RefCell, collections::HashMap, fmt, sync::LazyLock};
+use std::{cell::RefCell, collections::HashMap, fmt};
 use string_interner::{symbol::SymbolU32, DefaultBackend, StringInterner};

 pub type Interner = StringInterner<DefaultBackend, FxBuildHasher>;
-static INTERNER: LazyLock<Mutex<Interner>> =
-    LazyLock::new(|| Mutex::new(StringInterner::with_hasher(FxBuildHasher::default())));
+lazy_static! {
+    static ref INTERNER: Mutex<Interner> =
+        Mutex::new(StringInterner::with_hasher(FxBuildHasher::default()));
+}

 thread_local! {
    static LOCAL_INTERNER: RefCell<HashMap<String, StrRef>> = RefCell::default();
--- a/nac3ast/src/lib.rs
+++ b/nac3ast/src/lib.rs
@ -14,6 +14,9 @@
    clippy::wildcard_imports
 )]

+#[macro_use]
+extern crate lazy_static;
+
 mod ast_gen;
 mod constant;
 #[cfg(feature = "fold")]
--- a/nac3core/Cargo.toml
+++ b/nac3core/Cargo.toml
@ -10,17 +10,17 @@ no-escape-analysis = []
 [dependencies]
 itertools = "0.13"
 crossbeam = "0.8"
-indexmap = "2.6"
+indexmap = "2.2"
 parking_lot = "0.12"
-rayon = "1.10"
+rayon = "1.8"
 nac3parser = { path = "../nac3parser" }
 strum = "0.26"
 strum_macros = "0.26"

 [dependencies.inkwell]
-version = "0.5"
+version = "0.4"
 default-features = false
-features = ["llvm14-0-prefer-dynamic", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]
+features = ["llvm14-0", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]

 [dev-dependencies]
 test-case = "1.2.0"
--- a/nac3core/build.rs
+++ b/nac3core/build.rs
@ -1,3 +1,4 @@
+use regex::Regex;
 use std::{
    env,
    fs::File,
@ -6,9 +7,8 @@ use std::{
    process::{Command, Stdio},
 };

-use regex::Regex;
-
 fn main() {
+    // Define relevant directories
    let out_dir = env::var("OUT_DIR").unwrap();
    let out_dir = Path::new(&out_dir);
    let irrt_dir = Path::new("irrt");
@ -23,7 +23,6 @@ fn main() {
        "--target=wasm32",
        "-x",
        "c++",
-        "-std=c++20",
        "-fno-discard-value-names",
        "-fno-exceptions",
        "-fno-rtti",
@ -99,6 +98,8 @@ fn main() {
        file.write_all(filtered_output.as_bytes()).unwrap();
    }

+    // Assemble the emitted and filtered IR to .bc
+    // That .bc will be integrated into nac3core's codegen
    let mut llvm_as = Command::new("llvm-as-irrt")
        .stdin(Stdio::piped())
        .arg("-o")
--- a/nac3core/irrt/irrt.cpp
+++ b/nac3core/irrt/irrt.cpp
@ -1,6 +1,15 @@
-#include "irrt/exception.hpp"
-#include "irrt/int_types.hpp"
-#include "irrt/list.hpp"
-#include "irrt/math.hpp"
-#include "irrt/ndarray.hpp"
-#include "irrt/slice.hpp"
+#include <irrt/exception.hpp>
+#include <irrt/int_types.hpp>
+#include <irrt/list.hpp>
+#include <irrt/math_util.hpp>
+#include <irrt/ndarray/array.hpp>
+#include <irrt/ndarray/basic.hpp>
+#include <irrt/ndarray/broadcast.hpp>
+#include <irrt/ndarray/def.hpp>
+#include <irrt/ndarray/indexing.hpp>
+#include <irrt/ndarray/iter.hpp>
+#include <irrt/ndarray/matmul.hpp>
+#include <irrt/ndarray/reshape.hpp>
+#include <irrt/ndarray/transpose.hpp>
+#include <irrt/original.hpp>
+#include <irrt/slice.hpp>
--- a/nac3core/irrt/irrt/cslice.hpp
+++ b/nac3core/irrt/irrt/cslice.hpp
@ -1,9 +1,9 @@
 #pragma once

-#include "irrt/int_types.hpp"
+#include <irrt/int_types.hpp>

-template<typename SizeT>
-struct CSlice {
-    uint8_t* base;
+template <typename SizeT> struct CSlice
+{
+    uint8_t *base;
    SizeT len;
 };
--- a/nac3core/irrt/irrt/cstr_util.hpp
+++ b/nac3core/irrt/irrt/cstr_util.hpp
@ -0,0 +1,20 @@
+#pragma once
+
+#include <irrt/int_types.hpp>
+
+namespace cstr
+{
+/**
+ * @brief Implementation of `strlen()`.
+ */
+uint32_t length(const char *str)
+{
+    uint32_t length = 0;
+    while (*str != '\0')
+    {
+        length++;
+        str++;
+    }
+    return length;
+}
+} // namespace cstr
--- a/nac3core/irrt/irrt/debug.hpp
+++ b/nac3core/irrt/irrt/debug.hpp
@ -1,6 +1,5 @@
 #pragma once

-// Set in nac3core/build.rs
 #ifdef IRRT_DEBUG_ASSERT
 #define IRRT_DEBUG_ASSERT_BOOL true
 #else
@ -8,18 +7,15 @@
 #endif

 #define raise_debug_assert(SizeT, msg, param1, param2, param3) \
-    raise_exception(SizeT, EXN_ASSERTION_ERROR, "IRRT debug assert failed: " msg, param1, param2, param3)
+    raise_exception(SizeT, EXN_ASSERTION_ERROR,                \
+                    "IRRT debug assert failed: " msg, param1, param2, param3);

-#define debug_assert_eq(SizeT, lhs, rhs)                                           \
-    if constexpr (IRRT_DEBUG_ASSERT_BOOL) {                                        \
-        if ((lhs) != (rhs)) {                                                      \
-            raise_debug_assert(SizeT, "LHS = {0}. RHS = {1}", lhs, rhs, NO_PARAM); \
-        }                                                                          \
+#define debug_assert_eq(SizeT, lhs, rhs)                                       \
+    if (IRRT_DEBUG_ASSERT_BOOL && (lhs) != (rhs)) {                            \
+        raise_debug_assert(SizeT, "LHS = {0}. RHS = {1}", lhs, rhs, NO_PARAM); \
    }

-#define debug_assert(SizeT, expr)                                                  \
-    if constexpr (IRRT_DEBUG_ASSERT_BOOL) {                                        \
-        if (!(expr)) {                                                             \
-            raise_debug_assert(SizeT, "Got false.", NO_PARAM, NO_PARAM, NO_PARAM); \
-        }                                                                          \
+#define debug_assert(SizeT, expr)                                              \
+    if (IRRT_DEBUG_ASSERT_BOOL && !(expr)) {                                   \
+        raise_debug_assert(SizeT, "Got false.", NO_PARAM, NO_PARAM, NO_PARAM); \
    }
--- a/nac3core/irrt/irrt/exception.hpp
+++ b/nac3core/irrt/irrt/exception.hpp
@ -1,7 +1,8 @@
 #pragma once

-#include "irrt/cslice.hpp"
-#include "irrt/int_types.hpp"
+#include <irrt/cslice.hpp>
+#include <irrt/cstr_util.hpp>
+#include <irrt/int_types.hpp>

 /**
 * @brief The int type of ARTIQ exception IDs.
@ -12,11 +13,12 @@ typedef int32_t ExceptionId;
 * Set of exceptions C++ IRRT can use.
 * Must be synchronized with `setup_irrt_exceptions` in `nac3core/src/codegen/irrt/mod.rs`.
 */
-extern "C" {
-ExceptionId EXN_INDEX_ERROR;
-ExceptionId EXN_VALUE_ERROR;
-ExceptionId EXN_ASSERTION_ERROR;
-ExceptionId EXN_TYPE_ERROR;
+extern "C"
+{
+    ExceptionId EXN_INDEX_ERROR;
+    ExceptionId EXN_VALUE_ERROR;
+    ExceptionId EXN_ASSERTION_ERROR;
+    ExceptionId EXN_TYPE_ERROR;
 }

 /**
@ -25,14 +27,15 @@ ExceptionId EXN_TYPE_ERROR;
 * The parameter `err` could be `Exception<int32_t>` or `Exception<int64_t>`. The caller
 * must make sure to pass `Exception`s with the correct `SizeT` depending on the `size_t` of the runtime.
 */
-extern "C" void __nac3_raise(void* err);
+extern "C" void __nac3_raise(void *err);

-namespace {
+namespace
+{
 /**
 * @brief NAC3's Exception struct
 */
-template<typename SizeT>
-struct Exception {
+template <typename SizeT> struct Exception
+{
    ExceptionId id;
    CSlice<SizeT> filename;
    int32_t line;
@ -42,29 +45,24 @@ struct Exception {
    int64_t params[3];
 };

-constexpr int64_t NO_PARAM = 0;
+const int64_t NO_PARAM = 0;

-template<typename SizeT>
-void _raise_exception_helper(ExceptionId id,
-                             const char* filename,
-                             int32_t line,
-                             const char* function,
-                             const char* msg,
-                             int64_t param0,
-                             int64_t param1,
-                             int64_t param2) {
+template <typename SizeT>
+void _raise_exception_helper(ExceptionId id, const char *filename, int32_t line, const char *function, const char *msg,
+                             int64_t param0, int64_t param1, int64_t param2)
+{
    Exception<SizeT> e = {
        .id = id,
-        .filename = {.base = reinterpret_cast<const uint8_t*>(filename), .len = __builtin_strlen(filename)},
+        .filename = {.base = (uint8_t *)filename, .len = (int32_t)cstr::length(filename)},
        .line = line,
        .column = 0,
-        .function = {.base = reinterpret_cast<const uint8_t*>(function), .len = __builtin_strlen(function)},
-        .msg = {.base = reinterpret_cast<const uint8_t*>(msg), .len = __builtin_strlen(msg)},
+        .function = {.base = (uint8_t *)function, .len = (int32_t)cstr::length(function)},
+        .msg = {.base = (uint8_t *)msg, .len = (int32_t)cstr::length(msg)},
    };
    e.params[0] = param0;
    e.params[1] = param1;
    e.params[2] = param2;
-    __nac3_raise(reinterpret_cast<void*>(&e));
+    __nac3_raise((void *)&e);
    __builtin_unreachable();
 }

@ -74,9 +72,9 @@ void _raise_exception_helper(ExceptionId id,
 * @param id The ID of the exception to raise.
 * @param msg A global constant C-string of the error message.
 *
- * `param0` to `param2` are optional format arguments of `msg`. They should be set to
+ * `param0` and `param2` are optional format arguments of `msg`. They should be set to
 * `NO_PARAM` to indicate they are unused.
 */
-#define raise_exception(SizeT, id, msg, param0, param1, param2) \
+#define raise_exception(SizeT, id, msg, param0, param1, param2)                                                        \
    _raise_exception_helper<SizeT>(id, __FILE__, __LINE__, __FUNCTION__, msg, param0, param1, param2)
-}  // namespace
+} // namespace
--- a/nac3core/irrt/irrt/int_types.hpp
+++ b/nac3core/irrt/irrt/int_types.hpp
@ -1,22 +1,8 @@
 #pragma once

-#if __STDC_VERSION__ >= 202000
 using int8_t = _BitInt(8);
 using uint8_t = unsigned _BitInt(8);
 using int32_t = _BitInt(32);
 using uint32_t = unsigned _BitInt(32);
 using int64_t = _BitInt(64);
 using uint64_t = unsigned _BitInt(64);
-#else
-using int8_t = _ExtInt(8);
-using uint8_t = unsigned _ExtInt(8);
-using int32_t = _ExtInt(32);
-using uint32_t = unsigned _ExtInt(32);
-using int64_t = _ExtInt(64);
-using uint64_t = unsigned _ExtInt(64);
-#endif
-
-// NDArray indices are always `uint32_t`.
-using NDIndex = uint32_t;
-// The type of an index or a value describing the length of a range/slice is always `int32_t`.
-using SliceIndex = int32_t;
--- a/nac3core/irrt/irrt/list.hpp
+++ b/nac3core/irrt/irrt/list.hpp
@ -1,75 +1,19 @@
 #pragma once

-#include "irrt/int_types.hpp"
-#include "irrt/math_util.hpp"
+#include <irrt/int_types.hpp>
+#include <irrt/slice.hpp>

-extern "C" {
-// Handle list assignment and dropping part of the list when
-// both dest_step and src_step are +1.
-// - All the index must *not* be out-of-bound or negative,
-// - The end index is *inclusive*,
-// - The length of src and dest slice size should already
-// be checked: if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest)
-SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
-                                             SliceIndex dest_end,
-                                             SliceIndex dest_step,
-                                             uint8_t* dest_arr,
-                                             SliceIndex dest_arr_len,
-                                             SliceIndex src_start,
-                                             SliceIndex src_end,
-                                             SliceIndex src_step,
-                                             uint8_t* src_arr,
-                                             SliceIndex src_arr_len,
-                                             const SliceIndex size) {
-    /* if dest_arr_len == 0, do nothing since we do not support extending list */
-    if (dest_arr_len == 0)
-        return dest_arr_len;
-    /* if both step is 1, memmove directly, handle the dropping of the list, and shrink size */
-    if (src_step == dest_step && dest_step == 1) {
-        const SliceIndex src_len = (src_end >= src_start) ? (src_end - src_start + 1) : 0;
-        const SliceIndex dest_len = (dest_end >= dest_start) ? (dest_end - dest_start + 1) : 0;
-        if (src_len > 0) {
-            __builtin_memmove(dest_arr + dest_start * size, src_arr + src_start * size, src_len * size);
-        }
-        if (dest_len > 0) {
-            /* dropping */
-            __builtin_memmove(dest_arr + (dest_start + src_len) * size, dest_arr + (dest_end + 1) * size,
-                              (dest_arr_len - dest_end - 1) * size);
-        }
-        /* shrink size */
-        return dest_arr_len - (dest_len - src_len);
-    }
-    /* if two range overlaps, need alloca */
-    uint8_t need_alloca = (dest_arr == src_arr)
-                          && !(max(dest_start, dest_end) < min(src_start, src_end)
-                               || max(src_start, src_end) < min(dest_start, dest_end));
-    if (need_alloca) {
-        uint8_t* tmp = reinterpret_cast<uint8_t*>(__builtin_alloca(src_arr_len * size));
-        __builtin_memcpy(tmp, src_arr, src_arr_len * size);
-        src_arr = tmp;
-    }
-    SliceIndex src_ind = src_start;
-    SliceIndex dest_ind = dest_start;
-    for (; (src_step > 0) ? (src_ind <= src_end) : (src_ind >= src_end); src_ind += src_step, dest_ind += dest_step) {
-        /* for constant optimization */
-        if (size == 1) {
-            __builtin_memcpy(dest_arr + dest_ind, src_arr + src_ind, 1);
-        } else if (size == 4) {
-            __builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
-        } else if (size == 8) {
-            __builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
-        } else {
-            /* memcpy for var size, cannot overlap after previous alloca */
-            __builtin_memcpy(dest_arr + dest_ind * size, src_arr + src_ind * size, size);
-        }
-    }
-    /* only dest_step == 1 can we shrink the dest list. */
-    /* size should be ensured prior to calling this function */
-    if (dest_step == 1 && dest_end >= dest_start) {
-        __builtin_memmove(dest_arr + dest_ind * size, dest_arr + (dest_end + 1) * size,
-                          (dest_arr_len - dest_end - 1) * size);
-        return dest_arr_len - (dest_end - dest_ind) - 1;
-    }
-    return dest_arr_len;
-}
-}  // extern "C"
+namespace
+{
+/**
+ * @brief A list in NAC3.
+ *
+ * The `items` field is opaque. You must rely on external contexts to
+ * know how to interpret it.
+ */
+template <typename SizeT> struct List
+{
+    uint8_t *items;
+    SizeT len;
+};
+} // namespace
--- a/nac3core/irrt/irrt/math.hpp
+++ b/nac3core/irrt/irrt/math.hpp
@ -1,93 +0,0 @@
-#pragma once
-
-namespace {
-// adapted from GNU Scientific Library: https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
-// need to make sure `exp >= 0` before calling this function
-template<typename T>
-T __nac3_int_exp_impl(T base, T exp) {
-    T res = 1;
-    /* repeated squaring method */
-    do {
-        if (exp & 1) {
-            res *= base; /* for n odd */
-        }
-        exp >>= 1;
-        base *= base;
-    } while (exp);
-    return res;
-}
-}  // namespace
-
-#define DEF_nac3_int_exp_(T)                   \
-    T __nac3_int_exp_##T(T base, T exp) {      \
-        return __nac3_int_exp_impl(base, exp); \
-    }
-
-extern "C" {
-
-// Putting semicolons here to make clang-format not reformat this into
-// a stair shape.
-DEF_nac3_int_exp_(int32_t);
-DEF_nac3_int_exp_(int64_t);
-DEF_nac3_int_exp_(uint32_t);
-DEF_nac3_int_exp_(uint64_t);
-
-int32_t __nac3_isinf(double x) {
-    return __builtin_isinf(x);
-}
-
-int32_t __nac3_isnan(double x) {
-    return __builtin_isnan(x);
-}
-
-double tgamma(double arg);
-
-double __nac3_gamma(double z) {
-    // Handling for denormals
-    //     | x                 | Python gamma(x) | C tgamma(x) |
-    // --- | ----------------- | --------------- | ----------- |
-    // (1) | nan               | nan             | nan         |
-    // (2) | -inf              | -inf            | inf         |
-    // (3) | inf               | inf             | inf         |
-    // (4) | 0.0               | inf             | inf         |
-    // (5) | {-1.0, -2.0, ...} | inf             | nan         |
-
-    // (1)-(3)
-    if (__builtin_isinf(z) || __builtin_isnan(z)) {
-        return z;
-    }
-
-    double v = tgamma(z);
-
-    // (4)-(5)
-    return __builtin_isinf(v) || __builtin_isnan(v) ? __builtin_inf() : v;
-}
-
-double lgamma(double arg);
-
-double __nac3_gammaln(double x) {
-    // libm's handling of value overflows differs from scipy:
-    // - scipy: gammaln(-inf) -> -inf
-    // - libm : lgamma(-inf) -> inf
-
-    if (__builtin_isinf(x)) {
-        return x;
-    }
-
-    return lgamma(x);
-}
-
-double j0(double x);
-
-double __nac3_j0(double x) {
-    // libm's handling of value overflows differs from scipy:
-    // - scipy: j0(inf) -> nan
-    // - libm : j0(inf) -> 0.0
-
-    if (__builtin_isinf(x)) {
-        return __builtin_nan("");
-    }
-
-    return j0(x);
-}
-}
--- a/nac3core/irrt/irrt/math_util.hpp
+++ b/nac3core/irrt/irrt/math_util.hpp
@ -1,13 +1,14 @@
 #pragma once

-namespace {
-template<typename T>
-const T& max(const T& a, const T& b) {
+namespace
+{
+template <typename T> const T &max(const T &a, const T &b)
+{
    return a > b ? a : b;
 }

-template<typename T>
-const T& min(const T& a, const T& b) {
+template <typename T> const T &min(const T &a, const T &b)
+{
    return a > b ? b : a;
 }
-}  // namespace
+} // namespace
--- a/nac3core/irrt/irrt/ndarray.hpp
+++ b/nac3core/irrt/irrt/ndarray.hpp
@ -1,144 +0,0 @@
-#pragma once
-
-#include "irrt/int_types.hpp"
-
-namespace {
-template<typename SizeT>
-SizeT __nac3_ndarray_calc_size_impl(const SizeT* list_data, SizeT list_len, SizeT begin_idx, SizeT end_idx) {
-    __builtin_assume(end_idx <= list_len);
-
-    SizeT num_elems = 1;
-    for (SizeT i = begin_idx; i < end_idx; ++i) {
-        SizeT val = list_data[i];
-        __builtin_assume(val > 0);
-        num_elems *= val;
-    }
-    return num_elems;
-}
-
-template<typename SizeT>
-void __nac3_ndarray_calc_nd_indices_impl(SizeT index, const SizeT* dims, SizeT num_dims, NDIndex* idxs) {
-    SizeT stride = 1;
-    for (SizeT dim = 0; dim < num_dims; dim++) {
-        SizeT i = num_dims - dim - 1;
-        __builtin_assume(dims[i] > 0);
-        idxs[i] = (index / stride) % dims[i];
-        stride *= dims[i];
-    }
-}
-
-template<typename SizeT>
-SizeT __nac3_ndarray_flatten_index_impl(const SizeT* dims, SizeT num_dims, const NDIndex* indices, SizeT num_indices) {
-    SizeT idx = 0;
-    SizeT stride = 1;
-    for (SizeT i = 0; i < num_dims; ++i) {
-        SizeT ri = num_dims - i - 1;
-        if (ri < num_indices) {
-            idx += stride * indices[ri];
-        }
-
-        __builtin_assume(dims[i] > 0);
-        stride *= dims[ri];
-    }
-    return idx;
-}
-
-template<typename SizeT>
-void __nac3_ndarray_calc_broadcast_impl(const SizeT* lhs_dims,
-                                        SizeT lhs_ndims,
-                                        const SizeT* rhs_dims,
-                                        SizeT rhs_ndims,
-                                        SizeT* out_dims) {
-    SizeT max_ndims = lhs_ndims > rhs_ndims ? lhs_ndims : rhs_ndims;
-
-    for (SizeT i = 0; i < max_ndims; ++i) {
-        const SizeT* lhs_dim_sz = i < lhs_ndims ? &lhs_dims[lhs_ndims - i - 1] : nullptr;
-        const SizeT* rhs_dim_sz = i < rhs_ndims ? &rhs_dims[rhs_ndims - i - 1] : nullptr;
-        SizeT* out_dim = &out_dims[max_ndims - i - 1];
-
-        if (lhs_dim_sz == nullptr) {
-            *out_dim = *rhs_dim_sz;
-        } else if (rhs_dim_sz == nullptr) {
-            *out_dim = *lhs_dim_sz;
-        } else if (*lhs_dim_sz == 1) {
-            *out_dim = *rhs_dim_sz;
-        } else if (*rhs_dim_sz == 1) {
-            *out_dim = *lhs_dim_sz;
-        } else if (*lhs_dim_sz == *rhs_dim_sz) {
-            *out_dim = *lhs_dim_sz;
-        } else {
-            __builtin_unreachable();
-        }
-    }
-}
-
-template<typename SizeT>
-void __nac3_ndarray_calc_broadcast_idx_impl(const SizeT* src_dims,
-                                            SizeT src_ndims,
-                                            const NDIndex* in_idx,
-                                            NDIndex* out_idx) {
-    for (SizeT i = 0; i < src_ndims; ++i) {
-        SizeT src_i = src_ndims - i - 1;
-        out_idx[src_i] = src_dims[src_i] == 1 ? 0 : in_idx[src_i];
-    }
-}
-}  // namespace
-
-extern "C" {
-uint32_t __nac3_ndarray_calc_size(const uint32_t* list_data, uint32_t list_len, uint32_t begin_idx, uint32_t end_idx) {
-    return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
-}
-
-uint64_t
-__nac3_ndarray_calc_size64(const uint64_t* list_data, uint64_t list_len, uint64_t begin_idx, uint64_t end_idx) {
-    return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
-}
-
-void __nac3_ndarray_calc_nd_indices(uint32_t index, const uint32_t* dims, uint32_t num_dims, NDIndex* idxs) {
-    __nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
-}
-
-void __nac3_ndarray_calc_nd_indices64(uint64_t index, const uint64_t* dims, uint64_t num_dims, NDIndex* idxs) {
-    __nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
-}
-
-uint32_t
-__nac3_ndarray_flatten_index(const uint32_t* dims, uint32_t num_dims, const NDIndex* indices, uint32_t num_indices) {
-    return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
-}
-
-uint64_t
-__nac3_ndarray_flatten_index64(const uint64_t* dims, uint64_t num_dims, const NDIndex* indices, uint64_t num_indices) {
-    return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
-}
-
-void __nac3_ndarray_calc_broadcast(const uint32_t* lhs_dims,
-                                   uint32_t lhs_ndims,
-                                   const uint32_t* rhs_dims,
-                                   uint32_t rhs_ndims,
-                                   uint32_t* out_dims) {
-    return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
-}
-
-void __nac3_ndarray_calc_broadcast64(const uint64_t* lhs_dims,
-                                     uint64_t lhs_ndims,
-                                     const uint64_t* rhs_dims,
-                                     uint64_t rhs_ndims,
-                                     uint64_t* out_dims) {
-    return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
-}
-
-void __nac3_ndarray_calc_broadcast_idx(const uint32_t* src_dims,
-                                       uint32_t src_ndims,
-                                       const NDIndex* in_idx,
-                                       NDIndex* out_idx) {
-    __nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
-}
-
-void __nac3_ndarray_calc_broadcast_idx64(const uint64_t* src_dims,
-                                         uint64_t src_ndims,
-                                         const NDIndex* in_idx,
-                                         NDIndex* out_idx) {
-    __nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
-}
-}
--- a/nac3core/irrt/irrt/ndarray/array.hpp
+++ b/nac3core/irrt/irrt/ndarray/array.hpp
@ -0,0 +1,130 @@
+#pragma once
+
+#include <irrt/debug.hpp>
+#include <irrt/exception.hpp>
+#include <irrt/int_types.hpp>
+#include <irrt/list.hpp>
+#include <irrt/ndarray/basic.hpp>
+#include <irrt/ndarray/def.hpp>
+
+namespace
+{
+namespace ndarray
+{
+namespace array
+{
+template <typename SizeT>
+void set_and_validate_list_shape_helper(SizeT axis, List<SizeT> *list, SizeT ndims, SizeT *shape)
+{
+    if (shape[axis] == -1)
+    {
+        // Dimension is unspecified. Set it.
+        shape[axis] = list->len;
+    }
+    else
+    {
+        // Dimension is specified. Check.
+        if (shape[axis] != list->len)
+        {
+            // Mismatch, throw an error.
+            // NOTE: NumPy's error message is more complex and needs more PARAMS to display.
+            raise_exception(SizeT, EXN_VALUE_ERROR,
+                            "The requested array has an inhomogenous shape "
+                            "after {0} dimension(s).",
+                            axis, shape[axis], list->len);
+        }
+    }
+
+    if (axis + 1 == ndims)
+    {
+        // `list` has type `list[ItemType]`
+        // Do nothing
+    }
+    else
+    {
+        // `list` has type `list[list[...]]`
+        List<SizeT> **lists = (List<SizeT> **)(list->items);
+        for (SizeT i = 0; i < list->len; i++)
+        {
+            set_and_validate_list_shape_helper<SizeT>(axis + 1, lists[i], ndims, shape);
+        }
+    }
+}
+
+// TODO: Document me
+template <typename SizeT> void set_and_validate_list_shape(List<SizeT> *list, SizeT ndims, SizeT *shape)
+{
+    for (SizeT axis = 0; axis < ndims; axis++)
+    {
+        shape[axis] = -1; // Sentinel to say this dimension is unspecified.
+    }
+    set_and_validate_list_shape_helper<SizeT>(0, list, ndims, shape);
+}
+
+template <typename SizeT>
+void write_list_to_array_helper(SizeT axis, SizeT *index, List<SizeT> *list, NDArray<SizeT> *ndarray)
+{
+    debug_assert_eq(SizeT, list->len, ndarray->shape[axis]);
+    if (IRRT_DEBUG_ASSERT_BOOL)
+    {
+        if (!ndarray::basic::is_c_contiguous(ndarray))
+        {
+            raise_debug_assert(SizeT, "ndarray is not C-contiguous", ndarray->strides[0], ndarray->strides[1],
+                               NO_PARAM);
+        }
+    }
+
+    if (axis + 1 == ndarray->ndims)
+    {
+        // `list` has type `list[ItemType]`
+        // `ndarray` is contiguous, so we can do this, and this is fast.
+        uint8_t *dst = ndarray->data + (ndarray->itemsize * (*index));
+        __builtin_memcpy(dst, list->items, ndarray->itemsize * list->len);
+        *index += list->len;
+    }
+    else
+    {
+        // `list` has type `list[list[...]]`
+        List<SizeT> **lists = (List<SizeT> **)(list->items);
+
+        for (SizeT i = 0; i < list->len; i++)
+        {
+            write_list_to_array_helper<SizeT>(axis + 1, index, lists[i], ndarray);
+        }
+    }
+}
+
+// TODO: Document me
+template <typename SizeT> void write_list_to_array(List<SizeT> *list, NDArray<SizeT> *ndarray)
+{
+    SizeT index = 0;
+    write_list_to_array_helper<SizeT>((SizeT)0, &index, list, ndarray);
+}
+} // namespace array
+} // namespace ndarray
+} // namespace
+
+extern "C"
+{
+    using namespace ndarray::array;
+
+    void __nac3_ndarray_array_set_and_validate_list_shape(List<int32_t> *list, int32_t ndims, int32_t *shape)
+    {
+        set_and_validate_list_shape(list, ndims, shape);
+    }
+
+    void __nac3_ndarray_array_set_and_validate_list_shape64(List<int64_t> *list, int64_t ndims, int64_t *shape)
+    {
+        set_and_validate_list_shape(list, ndims, shape);
+    }
+
+    void __nac3_ndarray_array_write_list_to_array(List<int32_t> *list, NDArray<int32_t> *ndarray)
+    {
+        write_list_to_array(list, ndarray);
+    }
+
+    void __nac3_ndarray_array_write_list_to_array64(List<int64_t> *list, NDArray<int64_t> *ndarray)
+    {
+        write_list_to_array(list, ndarray);
+    }
+}
--- a/nac3core/irrt/irrt/ndarray/basic.hpp
+++ b/nac3core/irrt/irrt/ndarray/basic.hpp
@ -0,0 +1,380 @@
+#pragma once
+
+#include <irrt/debug.hpp>
+#include <irrt/exception.hpp>
+#include <irrt/int_types.hpp>
+#include <irrt/ndarray/def.hpp>
+
+namespace
+{
+namespace ndarray
+{
+namespace basic
+{
+/**
+ * @brief Asserts that `shape` does not contain negative dimensions.
+ *
+ * @param ndims Number of dimensions in `shape`
+ * @param shape The shape to check on
+ */
+template <typename SizeT> void assert_shape_no_negative(SizeT ndims, const SizeT *shape)
+{
+    for (SizeT axis = 0; axis < ndims; axis++)
+    {
+        if (shape[axis] < 0)
+        {
+            raise_exception(SizeT, EXN_VALUE_ERROR,
+                            "negative dimensions are not allowed; axis {0} "
+                            "has dimension {1}",
+                            axis, shape[axis], NO_PARAM);
+        }
+    }
+}
+
+/**
+ * @brief Check two shapes are the same in the context of writing outputting to an ndarray.
+ *
+ * This function throws error messages for output shape mismatches.
+ */
+template <typename SizeT>
+void assert_output_shape_same(SizeT ndarray_ndims, const SizeT *ndarray_shape, SizeT output_ndims,
+                              const SizeT *output_shape)
+{
+    if (ndarray_ndims != output_ndims)
+    {
+        // There is no corresponding NumPy error message like this.
+        raise_exception(SizeT, EXN_VALUE_ERROR, "Cannot write output of ndims {0} to an ndarray with ndims {1}",
+                        output_ndims, ndarray_ndims, NO_PARAM);
+    }
+
+    for (SizeT axis = 0; axis < ndarray_ndims; axis++)
+    {
+        if (ndarray_shape[axis] != output_shape[axis])
+        {
+            // There is no corresponding NumPy error message like this.
+            raise_exception(SizeT, EXN_VALUE_ERROR,
+                            "Mismatched dimensions on axis {0}, output has "
+                            "dimension {1}, but destination ndarray has dimension {2}.",
+                            axis, output_shape[axis], ndarray_shape[axis]);
+        }
+    }
+}
+
+/**
+ * @brief Returns the number of elements of an ndarray given its shape.
+ *
+ * @param ndims Number of dimensions in `shape`
+ * @param shape The shape of the ndarray
+ */
+template <typename SizeT> SizeT calc_size_from_shape(SizeT ndims, const SizeT *shape)
+{
+    SizeT size = 1;
+    for (SizeT axis = 0; axis < ndims; axis++)
+        size *= shape[axis];
+    return size;
+}
+
+/**
+ * @brief Compute the array indices of the `nth` (0-based) element of an ndarray given only its shape.
+ *
+ * @param ndims Number of elements in `shape` and `indices`
+ * @param shape The shape of the ndarray
+ * @param indices The returned indices indexing the ndarray with shape `shape`.
+ * @param nth The index of the element of interest.
+ */
+template <typename SizeT> void set_indices_by_nth(SizeT ndims, const SizeT *shape, SizeT *indices, SizeT nth)
+{
+    for (SizeT i = 0; i < ndims; i++)
+    {
+        SizeT axis = ndims - i - 1;
+        SizeT dim = shape[axis];
+
+        indices[axis] = nth % dim;
+        nth /= dim;
+    }
+}
+
+/**
+ * @brief Return the number of elements of an `ndarray`
+ *
+ * This function corresponds to `<an_ndarray>.size`
+ */
+template <typename SizeT> SizeT size(const NDArray<SizeT> *ndarray)
+{
+    return calc_size_from_shape(ndarray->ndims, ndarray->shape);
+}
+
+/**
+ * @brief Return of the number of its content of an `ndarray`.
+ *
+ * This function corresponds to `<an_ndarray>.nbytes`.
+ */
+template <typename SizeT> SizeT nbytes(const NDArray<SizeT> *ndarray)
+{
+    return size(ndarray) * ndarray->itemsize;
+}
+
+/**
+ * @brief Get the `len()` of an ndarray, and asserts that `ndarray` is a sized object.
+ *
+ * This function corresponds to `<an_ndarray>.__len__`.
+ *
+ * @param dst_length The returned result
+ */
+template <typename SizeT> SizeT len(const NDArray<SizeT> *ndarray)
+{
+    // numpy prohibits `__len__` on unsized objects
+    if (ndarray->ndims == 0)
+    {
+        raise_exception(SizeT, EXN_TYPE_ERROR, "len() of unsized object", NO_PARAM, NO_PARAM, NO_PARAM);
+    }
+    else
+    {
+        return ndarray->shape[0];
+    }
+}
+
+/**
+ * @brief Return a boolean indicating if `ndarray` is (C-)contiguous.
+ *
+ * You may want to see: ndarray's rules for C-contiguity: https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45
+ */
+template <typename SizeT> bool is_c_contiguous(const NDArray<SizeT> *ndarray)
+{
+    // Other references:
+    // - tinynumpy's implementation: https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L102
+    // - ndarray's flags["C_CONTIGUOUS"]: https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html#numpy.ndarray.flags
+    // - ndarray's rules for C-contiguity: https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45
+
+    // From https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45:
+    //
+    // The traditional rule is that for an array to be flagged as C contiguous,
+    // the following must hold:
+    //
+    // strides[-1] == itemsize
+    // strides[i] == shape[i+1] * strides[i + 1]
+    // [...]
+    // According to these rules, a 0- or 1-dimensional array is either both
+    // C- and F-contiguous, or neither; and an array with 2+ dimensions
+    // can be C- or F- contiguous, or neither, but not both. Though there
+    // there are exceptions for arrays with zero or one item, in the first
+    // case the check is relaxed up to and including the first dimension
+    // with shape[i] == 0. In the second case `strides == itemsize` will
+    // can be true for all dimensions and both flags are set.
+
+    if (ndarray->ndims == 0)
+    {
+        return true;
+    }
+
+    if (ndarray->strides[ndarray->ndims - 1] != ndarray->itemsize)
+    {
+        return false;
+    }
+
+    for (SizeT i = 1; i < ndarray->ndims; i++)
+    {
+        SizeT axis_i = ndarray->ndims - i - 1;
+        if (ndarray->strides[axis_i] != ndarray->shape[axis_i + 1] * ndarray->strides[axis_i + 1])
+        {
+            return false;
+        }
+    }
+
+    return true;
+}
+
+/**
+ * @brief Return the pointer to the element indexed by `indices`.
+ */
+template <typename SizeT> uint8_t *get_pelement_by_indices(const NDArray<SizeT> *ndarray, const SizeT *indices)
+{
+    uint8_t *element = ndarray->data;
+    for (SizeT dim_i = 0; dim_i < ndarray->ndims; dim_i++)
+        element += indices[dim_i] * ndarray->strides[dim_i];
+    return element;
+}
+
+/**
+ * @brief Convenience function. Like `get_pelement_by_indices` but
+ * reinterprets the element pointer.
+ */
+template <typename SizeT, typename T> T *get_ptr(const NDArray<SizeT> *ndarray, const SizeT *indices)
+{
+    return (T *)get_pelement_by_indices(ndarray, indices);
+}
+
+/**
+ * @brief Return the pointer to the nth (0-based) element in a flattened view of `ndarray`.
+ *
+ * This function does no bound check.
+ */
+template <typename SizeT> uint8_t *get_nth_pelement(const NDArray<SizeT> *ndarray, SizeT nth)
+{
+    uint8_t *element = ndarray->data;
+    for (SizeT i = 0; i < ndarray->ndims; i++)
+    {
+        SizeT axis = ndarray->ndims - i - 1;
+        SizeT dim = ndarray->shape[axis];
+        element += ndarray->strides[axis] * (nth % dim);
+        nth /= dim;
+    }
+    return element;
+}
+
+/**
+ * @brief Update the strides of an ndarray given an ndarray `shape`
+ * and assuming that the ndarray is fully c-contagious.
+ *
+ * You might want to read https://ajcr.net/stride-guide-part-1/.
+ */
+template <typename SizeT> void set_strides_by_shape(NDArray<SizeT> *ndarray)
+{
+    SizeT stride_product = 1;
+    for (SizeT i = 0; i < ndarray->ndims; i++)
+    {
+        SizeT axis = ndarray->ndims - i - 1;
+        ndarray->strides[axis] = stride_product * ndarray->itemsize;
+        stride_product *= ndarray->shape[axis];
+    }
+}
+
+/**
+ * @brief Set an element in `ndarray`.
+ *
+ * @param pelement Pointer to the element in `ndarray` to be set.
+ * @param pvalue Pointer to the value `pelement` will be set to.
+ */
+template <typename SizeT> void set_pelement_value(NDArray<SizeT> *ndarray, uint8_t *pelement, const uint8_t *pvalue)
+{
+    __builtin_memcpy(pelement, pvalue, ndarray->itemsize);
+}
+
+/**
+ * @brief Copy data from one ndarray to another of the exact same size and itemsize.
+ *
+ * Both ndarrays will be viewed in their flatten views when copying the elements.
+ */
+template <typename SizeT> void copy_data(const NDArray<SizeT> *src_ndarray, NDArray<SizeT> *dst_ndarray)
+{
+    // TODO: Make this faster with memcpy
+
+    debug_assert_eq(SizeT, src_ndarray->itemsize, dst_ndarray->itemsize);
+
+    for (SizeT i = 0; i < size(src_ndarray); i++)
+    {
+        auto src_element = ndarray::basic::get_nth_pelement(src_ndarray, i);
+        auto dst_element = ndarray::basic::get_nth_pelement(dst_ndarray, i);
+        ndarray::basic::set_pelement_value(dst_ndarray, dst_element, src_element);
+    }
+}
+} // namespace basic
+} // namespace ndarray
+} // namespace
+
+extern "C"
+{
+    using namespace ndarray::basic;
+
+    void __nac3_ndarray_util_assert_shape_no_negative(int32_t ndims, int32_t *shape)
+    {
+        assert_shape_no_negative(ndims, shape);
+    }
+
+    void __nac3_ndarray_util_assert_shape_no_negative64(int64_t ndims, int64_t *shape)
+    {
+        assert_shape_no_negative(ndims, shape);
+    }
+
+    void __nac3_ndarray_util_assert_output_shape_same(int32_t ndarray_ndims, const int32_t *ndarray_shape,
+                                                      int32_t output_ndims, const int32_t *output_shape)
+    {
+        assert_output_shape_same(ndarray_ndims, ndarray_shape, output_ndims, output_shape);
+    }
+
+    void __nac3_ndarray_util_assert_output_shape_same64(int64_t ndarray_ndims, const int64_t *ndarray_shape,
+                                                        int64_t output_ndims, const int64_t *output_shape)
+    {
+        assert_output_shape_same(ndarray_ndims, ndarray_shape, output_ndims, output_shape);
+    }
+
+    uint32_t __nac3_ndarray_size(NDArray<int32_t> *ndarray)
+    {
+        return size(ndarray);
+    }
+
+    uint64_t __nac3_ndarray_size64(NDArray<int64_t> *ndarray)
+    {
+        return size(ndarray);
+    }
+
+    uint32_t __nac3_ndarray_nbytes(NDArray<int32_t> *ndarray)
+    {
+        return nbytes(ndarray);
+    }
+
+    uint64_t __nac3_ndarray_nbytes64(NDArray<int64_t> *ndarray)
+    {
+        return nbytes(ndarray);
+    }
+
+    int32_t __nac3_ndarray_len(NDArray<int32_t> *ndarray)
+    {
+        return len(ndarray);
+    }
+
+    int64_t __nac3_ndarray_len64(NDArray<int64_t> *ndarray)
+    {
+        return len(ndarray);
+    }
+
+    bool __nac3_ndarray_is_c_contiguous(NDArray<int32_t> *ndarray)
+    {
+        return is_c_contiguous(ndarray);
+    }
+
+    bool __nac3_ndarray_is_c_contiguous64(NDArray<int64_t> *ndarray)
+    {
+        return is_c_contiguous(ndarray);
+    }
+
+    uint8_t *__nac3_ndarray_get_nth_pelement(const NDArray<int32_t> *ndarray, int32_t nth)
+    {
+        return get_nth_pelement(ndarray, nth);
+    }
+
+    uint8_t *__nac3_ndarray_get_nth_pelement64(const NDArray<int64_t> *ndarray, int64_t nth)
+    {
+        return get_nth_pelement(ndarray, nth);
+    }
+
+    uint8_t *__nac3_ndarray_get_pelement_by_indices(const NDArray<int32_t> *ndarray, int32_t *indices)
+    {
+        return get_pelement_by_indices(ndarray, indices);
+    }
+
+    uint8_t *__nac3_ndarray_get_pelement_by_indices64(const NDArray<int64_t> *ndarray, int64_t *indices)
+    {
+        return get_pelement_by_indices(ndarray, indices);
+    }
+
+    void __nac3_ndarray_set_strides_by_shape(NDArray<int32_t> *ndarray)
+    {
+        set_strides_by_shape(ndarray);
+    }
+
+    void __nac3_ndarray_set_strides_by_shape64(NDArray<int64_t> *ndarray)
+    {
+        set_strides_by_shape(ndarray);
+    }
+
+    void __nac3_ndarray_copy_data(NDArray<int32_t> *src_ndarray, NDArray<int32_t> *dst_ndarray)
+    {
+        copy_data(src_ndarray, dst_ndarray);
+    }
+
+    void __nac3_ndarray_copy_data64(NDArray<int64_t> *src_ndarray, NDArray<int64_t> *dst_ndarray)
+    {
+        copy_data(src_ndarray, dst_ndarray);
+    }
+}
--- a/nac3core/irrt/irrt/ndarray/broadcast.hpp
+++ b/nac3core/irrt/irrt/ndarray/broadcast.hpp
@ -0,0 +1,188 @@
+#pragma once
+
+#include <irrt/int_types.hpp>
+#include <irrt/ndarray/def.hpp>
+#include <irrt/slice.hpp>
+
+namespace
+{
+template <typename SizeT> struct ShapeEntry
+{
+    SizeT ndims;
+    SizeT *shape;
+};
+} // namespace
+
+namespace
+{
+namespace ndarray
+{
+namespace broadcast
+{
+/**
+ * @brief Return true if `src_shape` can broadcast to `dst_shape`.
+ *
+ * See https://numpy.org/doc/stable/user/basics.broadcasting.html
+ */
+template <typename SizeT>
+bool can_broadcast_shape_to(SizeT target_ndims, const SizeT *target_shape, SizeT src_ndims, const SizeT *src_shape)
+{
+    if (src_ndims > target_ndims)
+    {
+        return false;
+    }
+
+    for (SizeT i = 0; i < src_ndims; i++)
+    {
+        SizeT target_dim = target_shape[target_ndims - i - 1];
+        SizeT src_dim = src_shape[src_ndims - i - 1];
+        if (!(src_dim == 1 || target_dim == src_dim))
+        {
+            return false;
+        }
+    }
+    return true;
+}
+
+/**
+ * @brief Performs `np.broadcast_shapes(<shapes>)`
+ *
+ * @param num_shapes Number of entries in `shapes`
+ * @param shapes The list of shape to do `np.broadcast_shapes` on.
+ * @param dst_ndims The length of `dst_shape`.
+ *   `dst_ndims` must be `max([shape.ndims for shape in shapes])`, but the caller has to calculate it/provide it.
+ *   for this function since they should already know in order to allocate `dst_shape` in the first place.
+ * @param dst_shape The resulting shape. Must be pre-allocated by the caller. This function calculate the result
+ *   of `np.broadcast_shapes` and write it here.
+ */
+template <typename SizeT>
+void broadcast_shapes(SizeT num_shapes, const ShapeEntry<SizeT> *shapes, SizeT dst_ndims, SizeT *dst_shape)
+{
+    for (SizeT dst_axis = 0; dst_axis < dst_ndims; dst_axis++)
+    {
+        dst_shape[dst_axis] = 1;
+    }
+
+#ifdef IRRT_DEBUG_ASSERT
+    SizeT max_ndims_found = 0;
+#endif
+
+    for (SizeT i = 0; i < num_shapes; i++)
+    {
+        ShapeEntry<SizeT> entry = shapes[i];
+
+        // Check pre-condition: `dst_ndims` must be `max([shape.ndims for shape in shapes])`
+        debug_assert(SizeT, entry.ndims <= dst_ndims);
+
+#ifdef IRRT_DEBUG_ASSERT
+        max_ndims_found = max(max_ndims_found, entry.ndims);
+#endif
+
+        for (SizeT j = 0; j < entry.ndims; j++)
+        {
+            SizeT entry_axis = entry.ndims - j - 1;
+            SizeT dst_axis = dst_ndims - j - 1;
+
+            SizeT entry_dim = entry.shape[entry_axis];
+            SizeT dst_dim = dst_shape[dst_axis];
+
+            if (dst_dim == 1)
+            {
+                dst_shape[dst_axis] = entry_dim;
+            }
+            else if (entry_dim == 1 || entry_dim == dst_dim)
+            {
+                // Do nothing
+            }
+            else
+            {
+                raise_exception(SizeT, EXN_VALUE_ERROR,
+                                "shape mismatch: objects cannot be broadcast "
+                                "to a single shape.",
+                                NO_PARAM, NO_PARAM, NO_PARAM);
+            }
+        }
+    }
+
+    // Check pre-condition: `dst_ndims` must be `max([shape.ndims for shape in shapes])`
+    debug_assert_eq(SizeT, max_ndims_found, dst_ndims);
+}
+
+/**
+ * @brief Perform `np.broadcast_to(<ndarray>, <target_shape>)` and appropriate assertions.
+ *
+ * This function attempts to broadcast `src_ndarray` to a new shape defined by `dst_ndarray.shape`,
+ * and return the result by modifying `dst_ndarray`.
+ *
+ * # Notes on `dst_ndarray`
+ * The caller is responsible for allocating space for the resulting ndarray.
+ * Here is what this function expects from `dst_ndarray` when called:
+ *   - `dst_ndarray->data` does not have to be initialized.
+ *   - `dst_ndarray->itemsize` does not have to be initialized.
+ *   - `dst_ndarray->ndims` must be initialized, determining the length of `dst_ndarray->shape`
+ *   - `dst_ndarray->shape` must be allocated, and must contain the desired target broadcast shape.
+ *   - `dst_ndarray->strides` must be allocated, through it can contain uninitialized values.
+ * When this function call ends:
+ *   - `dst_ndarray->data` is set to `src_ndarray->data` (`dst_ndarray` is just a view to `src_ndarray`)
+ *   - `dst_ndarray->itemsize` is set to `src_ndarray->itemsize`
+ *   - `dst_ndarray->ndims` is unchanged.
+ *   - `dst_ndarray->shape` is unchanged.
+ *   - `dst_ndarray->strides` is updated accordingly by how ndarray broadcast_to works.
+ */
+template <typename SizeT> void broadcast_to(const NDArray<SizeT> *src_ndarray, NDArray<SizeT> *dst_ndarray)
+{
+    if (!ndarray::broadcast::can_broadcast_shape_to(dst_ndarray->ndims, dst_ndarray->shape, src_ndarray->ndims,
+                                                    src_ndarray->shape))
+    {
+        raise_exception(SizeT, EXN_VALUE_ERROR, "operands could not be broadcast together", NO_PARAM, NO_PARAM,
+                        NO_PARAM);
+    }
+
+    dst_ndarray->data = src_ndarray->data;
+    dst_ndarray->itemsize = src_ndarray->itemsize;
+
+    for (SizeT i = 0; i < dst_ndarray->ndims; i++)
+    {
+        SizeT src_axis = src_ndarray->ndims - i - 1;
+        SizeT dst_axis = dst_ndarray->ndims - i - 1;
+        if (src_axis < 0 || (src_ndarray->shape[src_axis] == 1 && dst_ndarray->shape[dst_axis] != 1))
+        {
+            // Freeze the steps in-place
+            dst_ndarray->strides[dst_axis] = 0;
+        }
+        else
+        {
+            dst_ndarray->strides[dst_axis] = src_ndarray->strides[src_axis];
+        }
+    }
+}
+} // namespace broadcast
+} // namespace ndarray
+} // namespace
+
+extern "C"
+{
+    using namespace ndarray::broadcast;
+
+    void __nac3_ndarray_broadcast_to(NDArray<int32_t> *src_ndarray, NDArray<int32_t> *dst_ndarray)
+    {
+        broadcast_to(src_ndarray, dst_ndarray);
+    }
+
+    void __nac3_ndarray_broadcast_to64(NDArray<int64_t> *src_ndarray, NDArray<int64_t> *dst_ndarray)
+    {
+        broadcast_to(src_ndarray, dst_ndarray);
+    }
+
+    void __nac3_ndarray_broadcast_shapes(int32_t num_shapes, const ShapeEntry<int32_t> *shapes, int32_t dst_ndims,
+                                         int32_t *dst_shape)
+    {
+        broadcast_shapes(num_shapes, shapes, dst_ndims, dst_shape);
+    }
+
+    void __nac3_ndarray_broadcast_shapes64(int64_t num_shapes, const ShapeEntry<int64_t> *shapes, int64_t dst_ndims,
+                                           int64_t *dst_shape)
+    {
+        broadcast_shapes(num_shapes, shapes, dst_ndims, dst_shape);
+    }
+}
--- a/nac3core/irrt/irrt/ndarray/def.hpp
+++ b/nac3core/irrt/irrt/ndarray/def.hpp
@ -0,0 +1,47 @@
+#pragma once
+
+#include <irrt/int_types.hpp>
+
+namespace
+{
+/**
+ * @brief The NDArray object
+ *
+ * The official numpy implementations: https://github.com/numpy/numpy/blob/735a477f0bc2b5b84d0e72d92f224bde78d4e069/doc/source/reference/c-api/types-and-structures.rst
+ */
+template <typename SizeT> struct NDArray
+{
+    /**
+     * @brief The underlying data this `ndarray` is pointing to.
+     *
+     * Must be set to `nullptr` to indicate that this NDArray's `data` is uninitialized.
+     */
+    uint8_t *data;
+
+    /**
+     * @brief The number of bytes of a single element in `data`.
+     */
+    SizeT itemsize;
+
+    /**
+     * @brief The number of dimensions of this shape.
+     */
+    SizeT ndims;
+
+    /**
+     * @brief The NDArray shape, with length equal to `ndims`.
+     *
+     * Note that it may contain 0.
+     */
+    SizeT *shape;
+
+    /**
+     * @brief Array strides, with length equal to `ndims`
+     *
+     * The stride values are in units of bytes, not number of elements.
+     *
+     * Note that `strides` can have negative values.
+     */
+    SizeT *strides;
+};
+} // namespace
--- a/nac3core/irrt/irrt/ndarray/indexing.hpp
+++ b/nac3core/irrt/irrt/ndarray/indexing.hpp
@ -0,0 +1,242 @@
+#pragma once
+
+#include <irrt/exception.hpp>
+#include <irrt/int_types.hpp>
+#include <irrt/ndarray/basic.hpp>
+#include <irrt/ndarray/def.hpp>
+#include <irrt/slice.hpp>
+
+namespace
+{
+typedef uint8_t NDIndexType;
+
+/**
+ * @brief A single element index
+ *
+ * `data` points to a `int32_t`.
+ */
+
+const NDIndexType ND_INDEX_TYPE_SINGLE_ELEMENT = 0;
+/**
+ * @brief A slice index
+ *
+ * `data` points to a `Slice<int32_t>`.
+ */
+const NDIndexType ND_INDEX_TYPE_SLICE = 1;
+
+/**
+ * @brief `np.newaxis` / `None`
+ *
+ * `data` is unused.
+ */
+const NDIndexType ND_INDEX_TYPE_NEWAXIS = 2;
+
+/**
+ * @brief `Ellipsis` / `...`
+ *
+ * `data` is unused.
+ */
+const NDIndexType ND_INDEX_TYPE_ELLIPSIS = 3;
+
+/**
+ * @brief An index used in ndarray indexing
+ */
+struct NDIndex
+{
+    /**
+     * @brief Enum tag to specify the type of index.
+     *
+     * Please see comments of each enum constant.
+     */
+    NDIndexType type;
+
+    /**
+     * @brief The accompanying data associated with `type`.
+     *
+     * Please see comments of each enum constant.
+     */
+    uint8_t *data;
+};
+} // namespace
+
+namespace
+{
+namespace ndarray
+{
+namespace indexing
+{
+/**
+ * @brief Perform ndarray "basic indexing" (https://numpy.org/doc/stable/user/basics.indexing.html#basic-indexing)
+ *
+ * This function is very similar to performing `dst_ndarray = src_ndarray[indices]` in Python.
+ *
+ * This function also does proper assertions on `indices` to check for out of bounds access.
+ *
+ * # Notes on `dst_ndarray`
+ * The caller is responsible for allocating space for the resulting ndarray.
+ * Here is what this function expects from `dst_ndarray` when called:
+ *   - `dst_ndarray->data` does not have to be initialized.
+ *   - `dst_ndarray->itemsize` does not have to be initialized.
+ *   - `dst_ndarray->ndims` must be initialized, and it must be equal to the expected `ndims` of the `dst_ndarray` after
+ *       indexing `src_ndarray` with `indices`.
+ *   - `dst_ndarray->shape` must be allocated, through it can contain uninitialized values.
+ *   - `dst_ndarray->strides` must be allocated, through it can contain uninitialized values.
+ * When this function call ends:
+ *   - `dst_ndarray->data` is set to `src_ndarray->data` (`dst_ndarray` is just a view to `src_ndarray`)
+ *   - `dst_ndarray->itemsize` is set to `src_ndarray->itemsize`
+ *   - `dst_ndarray->ndims` is unchanged.
+ *   - `dst_ndarray->shape` is updated according to how `src_ndarray` is indexed.
+ *   - `dst_ndarray->strides` is updated accordingly by how ndarray indexing works.
+ *
+ * @param indices indices to index `src_ndarray`, ordered in the same way you would write them in Python.
+ * @param src_ndarray The NDArray to be indexed.
+ * @param dst_ndarray The resulting NDArray after indexing. Further details in the comments above,
+ */
+template <typename SizeT>
+void index(SizeT num_indices, const NDIndex *indices, const NDArray<SizeT> *src_ndarray, NDArray<SizeT> *dst_ndarray)
+{
+    // Validate `indices`.
+
+    // Expected value of `dst_ndarray->ndims`.
+    SizeT expected_dst_ndims = src_ndarray->ndims;
+    // To check for "too many indices for array: array is ?-dimensional, but ? were indexed"
+    SizeT num_indexed = 0;
+    // There may be ellipsis `...` in `indices`. There can only be 0 or 1 ellipsis.
+    SizeT num_ellipsis = 0;
+
+    for (SizeT i = 0; i < num_indices; i++)
+    {
+        if (indices[i].type == ND_INDEX_TYPE_SINGLE_ELEMENT)
+        {
+            expected_dst_ndims--;
+            num_indexed++;
+        }
+        else if (indices[i].type == ND_INDEX_TYPE_SLICE)
+        {
+            num_indexed++;
+        }
+        else if (indices[i].type == ND_INDEX_TYPE_NEWAXIS)
+        {
+            expected_dst_ndims++;
+        }
+        else if (indices[i].type == ND_INDEX_TYPE_ELLIPSIS)
+        {
+            num_ellipsis++;
+            if (num_ellipsis > 1)
+            {
+                raise_exception(SizeT, EXN_INDEX_ERROR, "an index can only have a single ellipsis ('...')", NO_PARAM,
+                                NO_PARAM, NO_PARAM);
+            }
+        }
+        else
+        {
+            __builtin_unreachable();
+        }
+    }
+
+    debug_assert_eq(SizeT, expected_dst_ndims, dst_ndarray->ndims);
+
+    if (src_ndarray->ndims - num_indexed < 0)
+    {
+        raise_exception(SizeT, EXN_INDEX_ERROR,
+                        "too many indices for array: array is {0}-dimensional, "
+                        "but {1} were indexed",
+                        src_ndarray->ndims, num_indices, NO_PARAM);
+    }
+
+    dst_ndarray->data = src_ndarray->data;
+    dst_ndarray->itemsize = src_ndarray->itemsize;
+
+    // Reference code: https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L652
+    SizeT src_axis = 0;
+    SizeT dst_axis = 0;
+
+    for (int32_t i = 0; i < num_indices; i++)
+    {
+        const NDIndex *index = &indices[i];
+        if (index->type == ND_INDEX_TYPE_SINGLE_ELEMENT)
+        {
+            SizeT input = (SizeT) * ((int32_t *)index->data);
+            SizeT k = slice::resolve_index_in_length(src_ndarray->shape[src_axis], input);
+
+            if (k == -1)
+            {
+                raise_exception(SizeT, EXN_INDEX_ERROR,
+                                "index {0} is out of bounds for axis {1} "
+                                "with size {2}",
+                                input, src_axis, src_ndarray->shape[src_axis]);
+            }
+
+            dst_ndarray->data += k * src_ndarray->strides[src_axis];
+
+            src_axis++;
+        }
+        else if (index->type == ND_INDEX_TYPE_SLICE)
+        {
+            Slice<int32_t> *slice = (Slice<int32_t> *)index->data;
+
+            Range<int32_t> range = slice->indices_checked<SizeT>(src_ndarray->shape[src_axis]);
+
+            dst_ndarray->data += (SizeT)range.start * src_ndarray->strides[src_axis];
+            dst_ndarray->strides[dst_axis] = ((SizeT)range.step) * src_ndarray->strides[src_axis];
+            dst_ndarray->shape[dst_axis] = (SizeT)range.len<SizeT>();
+
+            dst_axis++;
+            src_axis++;
+        }
+        else if (index->type == ND_INDEX_TYPE_NEWAXIS)
+        {
+            dst_ndarray->strides[dst_axis] = 0;
+            dst_ndarray->shape[dst_axis] = 1;
+
+            dst_axis++;
+        }
+        else if (index->type == ND_INDEX_TYPE_ELLIPSIS)
+        {
+            // The number of ':' entries this '...' implies.
+            SizeT ellipsis_size = src_ndarray->ndims - num_indexed;
+
+            for (SizeT j = 0; j < ellipsis_size; j++)
+            {
+                dst_ndarray->strides[dst_axis] = src_ndarray->strides[src_axis];
+                dst_ndarray->shape[dst_axis] = src_ndarray->shape[src_axis];
+
+                dst_axis++;
+                src_axis++;
+            }
+        }
+        else
+        {
+            __builtin_unreachable();
+        }
+    }
+
+    for (; dst_axis < dst_ndarray->ndims; dst_axis++, src_axis++)
+    {
+        dst_ndarray->shape[dst_axis] = src_ndarray->shape[src_axis];
+        dst_ndarray->strides[dst_axis] = src_ndarray->strides[src_axis];
+    }
+
+    debug_assert_eq(SizeT, src_ndarray->ndims, src_axis);
+    debug_assert_eq(SizeT, dst_ndarray->ndims, dst_axis);
+}
+} // namespace indexing
+} // namespace ndarray
+} // namespace
+
+extern "C"
+{
+    using namespace ndarray::indexing;
+
+    void __nac3_ndarray_index(int32_t num_indices, NDIndex *indices, NDArray<int32_t> *src_ndarray,
+                              NDArray<int32_t> *dst_ndarray)
+    {
+        index(num_indices, indices, src_ndarray, dst_ndarray);
+    }
+
+    void __nac3_ndarray_index64(int64_t num_indices, NDIndex *indices, NDArray<int64_t> *src_ndarray,
+                                NDArray<int64_t> *dst_ndarray)
+    {
+        index(num_indices, indices, src_ndarray, dst_ndarray);
+    }
+}
--- a/nac3core/irrt/irrt/ndarray/iter.hpp
+++ b/nac3core/irrt/irrt/ndarray/iter.hpp
@ -0,0 +1,142 @@
+#pragma once
+
+#include <irrt/int_types.hpp>
+#include <irrt/ndarray/def.hpp>
+
+namespace
+{
+/**
+ * @brief Helper struct to enumerate through all indices under a shape.
+ *
+ * i.e., If `shape` is `[3, 2]`, by repeating `next()`, then you get:
+ * - `[0, 0]`
+ * - `[0, 1]`
+ * - `[1, 0]`
+ * - `[1, 1]`
+ * - `[2, 0]`
+ * - `[2, 1]`
+ * - end.
+ *
+ * Interesting cases:
+ * - If ndims == 0, there is one enumeration.
+ * - If shape contains zeroes, there are no enumerations.
+ */
+template <typename SizeT> struct NDIter
+{
+    SizeT ndims;
+    SizeT *shape;
+    SizeT *strides;
+
+    /**
+     * @brief The current indices.
+     *
+     * Must be allocated by the caller.
+     */
+    SizeT *indices;
+
+    /**
+     * @brief The nth (0-based) index of the current indices.
+     */
+    SizeT nth;
+
+    /**
+     * @brief Pointer to the current element.
+     */
+    uint8_t *element;
+
+    /**
+     * @brief The product of shape.
+     */
+    SizeT size;
+
+    // TODO:: There is something called backstrides to speedup iteration.
+    // See https://ajcr.net/stride-guide-part-1/, and https://docs.scipy.org/doc/numpy-1.13.0/reference/c-api.types-and-structures.html#c.PyArrayIterObject.PyArrayIterObject.backstrides.
+    // Maybe LLVM is clever and knows how to optimize.
+
+    void initialize(SizeT ndims, SizeT *shape, SizeT *strides, uint8_t *element, SizeT *indices)
+    {
+        this->ndims = ndims;
+        this->shape = shape;
+        this->strides = strides;
+
+        this->indices = indices;
+        this->element = element;
+
+        // Compute size and backstrides
+        this->size = 1;
+        for (SizeT i = 0; i < ndims; i++)
+        {
+            this->size *= shape[i];
+        }
+
+        for (SizeT axis = 0; axis < ndims; axis++)
+            indices[axis] = 0;
+        nth = 0;
+    }
+
+    void initialize_by_ndarray(NDArray<SizeT> *ndarray, SizeT *indices)
+    {
+        this->initialize(ndarray->ndims, ndarray->shape, ndarray->strides, ndarray->data, indices);
+    }
+
+    bool has_next()
+    {
+        return nth < size;
+    }
+
+    void next()
+    {
+        for (SizeT i = 0; i < ndims; i++)
+        {
+            SizeT axis = ndims - i - 1;
+            indices[axis]++;
+            if (indices[axis] >= shape[axis])
+            {
+                indices[axis] = 0;
+
+                // TODO: Can be optimized with backstrides.
+                element -= strides[axis] * (shape[axis] - 1);
+            }
+            else
+            {
+                element += strides[axis];
+                break;
+            }
+        }
+        nth++;
+    }
+};
+} // namespace
+
+extern "C"
+{
+    void __nac3_nditer_initialize(NDIter<int32_t> *iter, NDArray<int32_t> *ndarray, int32_t *indices)
+    {
+        iter->initialize_by_ndarray(ndarray, indices);
+    }
+
+    void __nac3_nditer_initialize64(NDIter<int64_t> *iter, NDArray<int64_t> *ndarray, int64_t *indices)
+    {
+        iter->initialize_by_ndarray(ndarray, indices);
+    }
+
+    bool __nac3_nditer_has_next(NDIter<int32_t> *iter)
+    {
+        return iter->has_next();
+    }
+
+    bool __nac3_nditer_has_next64(NDIter<int64_t> *iter)
+    {
+        return iter->has_next();
+    }
+
+    void __nac3_nditer_next(NDIter<int32_t> *iter)
+    {
+        iter->next();
+    }
+
+    void __nac3_nditer_next64(NDIter<int64_t> *iter)
+    {
+        iter->next();
+    }
+}
--- a/nac3core/irrt/irrt/ndarray/matmul.hpp
+++ b/nac3core/irrt/irrt/ndarray/matmul.hpp
@ -0,0 +1,92 @@
+#pragma once
+
+#include <irrt/debug.hpp>
+#include <irrt/exception.hpp>
+#include <irrt/int_types.hpp>
+#include <irrt/ndarray/basic.hpp>
+#include <irrt/ndarray/broadcast.hpp>
+#include <irrt/ndarray/iter.hpp>
+
+// NOTE: Everything would be much easier and elegant if einsum is implemented.
+
+namespace
+{
+namespace ndarray
+{
+namespace matmul
+{
+
+/**
+ * @brief Perform the broadcast in `np.einsum("...ij,...jk->...ik", a, b)`.
+ *
+ * Example:
+ *   Suppose      `a_shape ==      [1, 97, 4, 2]`
+ *       and      `b_shape == [99, 98,  1, 2, 5]`,
+ *
+ *   ...then  `new_a_shape == [99, 98, 97, 4, 2]`,
+ *            `new_b_shape == [99, 98, 97, 2, 5]`,
+ *      and     `dst_shape == [99, 98, 97, 4, 5]`.
+ *                             ^^^^^^^^^^  ^^^^
+ *                          (broadcasted)  (4x2 @ 2x5 => 4x5)
+ *
+ * @param a_ndims Length of `a_shape`.
+ * @param a_shape Shape of `a`.
+ * @param b_ndims Length of `b_shape`.
+ * @param b_shape Shape of `b`.
+ * @param final_ndims Should be equal to `max(a_ndims, b_ndims)`. This is the length of `new_a_shape`,
+ * `new_b_shape`, and `dst_shape` - the number of dimensions after broadcasting.
+ */
+template <typename SizeT>
+void calculate_shapes(SizeT a_ndims, SizeT *a_shape, SizeT b_ndims, SizeT *b_shape, SizeT final_ndims,
+                      SizeT *new_a_shape, SizeT *new_b_shape, SizeT *dst_shape)
+{
+    debug_assert(SizeT, a_ndims >= 2);
+    debug_assert(SizeT, b_ndims >= 2);
+    debug_assert_eq(SizeT, max(a_ndims, b_ndims), final_ndims);
+
+    // Check that a and b are compatible for matmul
+    if (a_shape[a_ndims - 1] != b_shape[b_ndims - 2])
+    {
+        // This is a custom error message. Different from NumPy.
+        raise_exception(SizeT, EXN_VALUE_ERROR, "Cannot multiply LHS (shape ?x{0}) with RHS (shape {1}x?})",
+                        a_shape[a_ndims - 1], b_shape[b_ndims - 2], NO_PARAM);
+    }
+
+    const SizeT num_entries = 2;
+    ShapeEntry<SizeT> entries[num_entries] = {{.ndims = a_ndims - 2, .shape = a_shape},
+                                              {.ndims = b_ndims - 2, .shape = b_shape}};
+
+    // TODO: Optimize this
+    ndarray::broadcast::broadcast_shapes<SizeT>(num_entries, entries, final_ndims - 2, new_a_shape);
+    ndarray::broadcast::broadcast_shapes<SizeT>(num_entries, entries, final_ndims - 2, new_b_shape);
+    ndarray::broadcast::broadcast_shapes<SizeT>(num_entries, entries, final_ndims - 2, dst_shape);
+
+    new_a_shape[final_ndims - 2] = a_shape[a_ndims - 2];
+    new_a_shape[final_ndims - 1] = a_shape[a_ndims - 1];
+    new_b_shape[final_ndims - 2] = b_shape[b_ndims - 2];
+    new_b_shape[final_ndims - 1] = b_shape[b_ndims - 1];
+    dst_shape[final_ndims - 2] = a_shape[a_ndims - 2];
+    dst_shape[final_ndims - 1] = b_shape[b_ndims - 1];
+}
+} // namespace matmul
+} // namespace ndarray
+} // namespace
+
+extern "C"
+{
+    using namespace ndarray::matmul;
+
+    void __nac3_ndarray_matmul_calculate_shapes(int32_t a_ndims, int32_t *a_shape, int32_t b_ndims, int32_t *b_shape,
+                                                int32_t final_ndims, int32_t *new_a_shape, int32_t *new_b_shape,
+                                                int32_t *dst_shape)
+    {
+        calculate_shapes(a_ndims, a_shape, b_ndims, b_shape, final_ndims, new_a_shape, new_b_shape, dst_shape);
+    }
+
+    void __nac3_ndarray_matmul_calculate_shapes64(int64_t a_ndims, int64_t *a_shape, int64_t b_ndims, int64_t *b_shape,
+                                                  int64_t final_ndims, int64_t *new_a_shape, int64_t *new_b_shape,
+                                                  int64_t *dst_shape)
+    {
+        calculate_shapes(a_ndims, a_shape, b_ndims, b_shape, final_ndims, new_a_shape, new_b_shape, dst_shape);
+    }
+}
--- a/nac3core/irrt/irrt/ndarray/reshape.hpp
+++ b/nac3core/irrt/irrt/ndarray/reshape.hpp
@ -0,0 +1,125 @@
+#pragma once
+
+#include <irrt/int_types.hpp>
+#include <irrt/ndarray/def.hpp>
+
+namespace
+{
+namespace ndarray
+{
+namespace reshape
+{
+/**
+ * @brief Perform assertions on and resolve unknown dimensions in `new_shape` in `np.reshape(<ndarray>, new_shape)`
+ *
+ * If `new_shape` indeed contains unknown dimensions (specified with `-1`, just like numpy), `new_shape` will be
+ * modified to contain the resolved dimension.
+ *
+ * To perform assertions on and resolve unknown dimensions in `new_shape`, we don't need the actual
+ * `<ndarray>` object itself, but only the `.size` of the `<ndarray>`.
+ *
+ * @param size The `.size` of `<ndarray>`
+ * @param new_ndims Number of elements in `new_shape`
+ * @param new_shape Target shape to reshape to
+ */
+template <typename SizeT> void resolve_and_check_new_shape(SizeT size, SizeT new_ndims, SizeT *new_shape)
+{
+    // Is there a -1 in `new_shape`?
+    bool neg1_exists = false;
+    // Location of -1, only initialized if `neg1_exists` is true
+    SizeT neg1_axis_i;
+    // The computed ndarray size of `new_shape`
+    SizeT new_size = 1;
+
+    for (SizeT axis_i = 0; axis_i < new_ndims; axis_i++)
+    {
+        SizeT dim = new_shape[axis_i];
+        if (dim < 0)
+        {
+            if (dim == -1)
+            {
+                if (neg1_exists)
+                {
+                    // Multiple `-1` found. Throw an error.
+                    raise_exception(SizeT, EXN_VALUE_ERROR, "can only specify one unknown dimension", NO_PARAM,
+                                    NO_PARAM, NO_PARAM);
+                }
+                else
+                {
+                    neg1_exists = true;
+                    neg1_axis_i = axis_i;
+                }
+            }
+            else
+            {
+                // TODO: What? In `np.reshape` any negative dimensions is
+                // treated like its `-1`.
+                //
+                // Try running `np.zeros((3, 4)).reshape((-999, 2))`
+                //
+                // It is not documented by numpy.
+                // Throw an error for now...
+
+                raise_exception(SizeT, EXN_VALUE_ERROR, "Found non -1 negative dimension {0} on axis {1}", dim, axis_i,
+                                NO_PARAM);
+            }
+        }
+        else
+        {
+            new_size *= dim;
+        }
+    }
+
+    bool can_reshape;
+    if (neg1_exists)
+    {
+        // Let `x` be the unknown dimension
+        // Solve `x * <new_size> = <size>`
+        if (new_size == 0 && size == 0)
+        {
+            // `x` has infinitely many solutions
+            can_reshape = false;
+        }
+        else if (new_size == 0 && size != 0)
+        {
+            // `x` has no solutions
+            can_reshape = false;
+        }
+        else if (size % new_size != 0)
+        {
+            // `x` has no integer solutions
+            can_reshape = false;
+        }
+        else
+        {
+            can_reshape = true;
+            new_shape[neg1_axis_i] = size / new_size; // Resolve dimension
+        }
+    }
+    else
+    {
+        can_reshape = (new_size == size);
+    }
+
+    if (!can_reshape)
+    {
+        raise_exception(SizeT, EXN_VALUE_ERROR, "cannot reshape array of size {0} into given shape", size, NO_PARAM,
+                        NO_PARAM);
+    }
+}
+} // namespace reshape
+} // namespace ndarray
+} // namespace
+
+extern "C"
+{
+    void __nac3_ndarray_reshape_resolve_and_check_new_shape(int32_t size, int32_t new_ndims, int32_t *new_shape)
+    {
+        ndarray::reshape::resolve_and_check_new_shape(size, new_ndims, new_shape);
+    }
+
+    void __nac3_ndarray_reshape_resolve_and_check_new_shape64(int64_t size, int64_t new_ndims, int64_t *new_shape)
+    {
+        ndarray::reshape::resolve_and_check_new_shape(size, new_ndims, new_shape);
+    }
+}
--- a/nac3core/irrt/irrt/ndarray/transpose.hpp
+++ b/nac3core/irrt/irrt/ndarray/transpose.hpp
@ -0,0 +1,155 @@
+#pragma once
+
+#include <irrt/int_types.hpp>
+#include <irrt/ndarray/def.hpp>
+#include <irrt/slice.hpp>
+
+/*
+ * Notes on `np.transpose(<array>, <axes>)`
+ *
+ * TODO: `axes`, if specified, can actually contain negative indices,
+ * but it is not documented in numpy.
+ *
+ * Supporting it for now.
+ */
+
+namespace
+{
+namespace ndarray
+{
+namespace transpose
+{
+/**
+ * @brief Do assertions on `<axes>` in `np.transpose(<array>, <axes>)`.
+ *
+ * Note that `np.transpose`'s `<axe>` argument is optional. If the argument
+ * is specified but the user, use this function to do assertions on it.
+ *
+ * @param ndims The number of dimensions of `<array>`
+ * @param num_axes Number of elements in `<axes>` as specified by the user.
+ *   This should be equal to `ndims`. If not, a "ValueError: axes don't match array" is thrown.
+ * @param axes The user specified `<axes>`.
+ */
+template <typename SizeT> void assert_transpose_axes(SizeT ndims, SizeT num_axes, const SizeT *axes)
+{
+    if (ndims != num_axes)
+    {
+        raise_exception(SizeT, EXN_VALUE_ERROR, "axes don't match array", NO_PARAM, NO_PARAM, NO_PARAM);
+    }
+
+    // TODO: Optimize this
+    bool *axe_specified = (bool *)__builtin_alloca(sizeof(bool) * ndims);
+    for (SizeT i = 0; i < ndims; i++)
+        axe_specified[i] = false;
+
+    for (SizeT i = 0; i < ndims; i++)
+    {
+        SizeT axis = slice::resolve_index_in_length(ndims, axes[i]);
+        if (axis == -1)
+        {
+            // TODO: numpy actually throws a `numpy.exceptions.AxisError`
+            raise_exception(SizeT, EXN_VALUE_ERROR, "axis {0} is out of bounds for array of dimension {1}", axis, ndims,
+                            NO_PARAM);
+        }
+
+        if (axe_specified[axis])
+        {
+            raise_exception(SizeT, EXN_VALUE_ERROR, "repeated axis in transpose", NO_PARAM, NO_PARAM, NO_PARAM);
+        }
+
+        axe_specified[axis] = true;
+    }
+}
+
+/**
+ * @brief Create a transpose view of `src_ndarray` and perform proper assertions.
+ *
+ * This function is very similar to doing `dst_ndarray = np.transpose(src_ndarray, <axes>)`.
+ * If `<axes>` is supposed to be `None`, caller can pass in a `nullptr` to `<axes>`.
+ *
+ * The transpose view created is returned by modifying `dst_ndarray`.
+ *
+ * The caller is responsible for setting up `dst_ndarray` before calling this function.
+ * Here is what this function expects from `dst_ndarray` when called:
+ *   - `dst_ndarray->data` does not have to be initialized.
+ *   - `dst_ndarray->itemsize` does not have to be initialized.
+ *   - `dst_ndarray->ndims` must be initialized, must be equal to `src_ndarray->ndims`.
+ *   - `dst_ndarray->shape` must be allocated, through it can contain uninitialized values.
+ *   - `dst_ndarray->strides` must be allocated, through it can contain uninitialized values.
+ * When this function call ends:
+ *   - `dst_ndarray->data` is set to `src_ndarray->data` (`dst_ndarray` is just a view to `src_ndarray`)
+ *   - `dst_ndarray->itemsize` is set to `src_ndarray->itemsize`
+ *   - `dst_ndarray->ndims` is unchanged
+ *   - `dst_ndarray->shape` is updated according to how `np.transpose` works
+ *   - `dst_ndarray->strides` is updated according to how `np.transpose` works
+ *
+ * @param src_ndarray The NDArray to build a transpose view on
+ * @param dst_ndarray The resulting NDArray after transpose. Further details in the comments above,
+ * @param num_axes Number of elements in axes. Unused if `axes` is nullptr.
+ * @param axes Axes permutation. Set it to `nullptr` if `<axes>` is `None`.
+ */
+template <typename SizeT>
+void transpose(const NDArray<SizeT> *src_ndarray, NDArray<SizeT> *dst_ndarray, SizeT num_axes, const SizeT *axes)
+{
+    debug_assert_eq(SizeT, src_ndarray->ndims, dst_ndarray->ndims);
+    const auto ndims = src_ndarray->ndims;
+
+    if (axes != nullptr)
+        assert_transpose_axes(ndims, num_axes, axes);
+
+    dst_ndarray->data = src_ndarray->data;
+    dst_ndarray->itemsize = src_ndarray->itemsize;
+
+    // Check out https://ajcr.net/stride-guide-part-2/ to see how `np.transpose` works behind the scenes.
+    if (axes == nullptr)
+    {
+        // `np.transpose(<array>, axes=None)`
+
+        /*
+         * Minor note: `np.transpose(<array>, axes=None)` is equivalent to
+         * `np.transpose(<array>, axes=[N-1, N-2, ..., 0])` - basically it
+         * is reversing the order of strides and shape.
+         *
+         * This is a fast implementation to handle this special (but very common) case.
+         */
+
+        for (SizeT axis = 0; axis < ndims; axis++)
+        {
+            dst_ndarray->shape[axis] = src_ndarray->shape[ndims - axis - 1];
+            dst_ndarray->strides[axis] = src_ndarray->strides[ndims - axis - 1];
+        }
+    }
+    else
+    {
+        // `np.transpose(<array>, <axes>)`
+
+        // Permute strides and shape according to `axes`, while resolving negative indices in `axes`
+        for (SizeT axis = 0; axis < ndims; axis++)
+        {
+            // `i` cannot be OUT_OF_BOUNDS because of assertions
+            SizeT i = slice::resolve_index_in_length(ndims, axes[axis]);
+
+            dst_ndarray->shape[axis] = src_ndarray->shape[i];
+            dst_ndarray->strides[axis] = src_ndarray->strides[i];
+        }
+    }
+}
+} // namespace transpose
+} // namespace ndarray
+} // namespace
+
+extern "C"
+{
+    using namespace ndarray::transpose;
+    void __nac3_ndarray_transpose(const NDArray<int32_t> *src_ndarray, NDArray<int32_t> *dst_ndarray, int32_t num_axes,
+                                  const int32_t *axes)
+    {
+        transpose(src_ndarray, dst_ndarray, num_axes, axes);
+    }
+
+    void __nac3_ndarray_transpose64(const NDArray<int64_t> *src_ndarray, NDArray<int64_t> *dst_ndarray,
+                                    int64_t num_axes, const int64_t *axes)
+    {
+        transpose(src_ndarray, dst_ndarray, num_axes, axes);
+    }
+}
--- a/nac3core/irrt/irrt/original.hpp
+++ b/nac3core/irrt/irrt/original.hpp
@ -0,0 +1,215 @@
+#pragma once
+
+#include <irrt/int_types.hpp>
+#include <irrt/math_util.hpp>
+
+// The type of an index or a value describing the length of a range/slice is always `int32_t`.
+using SliceIndex = int32_t;
+
+namespace
+{
+// adapted from GNU Scientific Library: https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
+// need to make sure `exp >= 0` before calling this function
+template <typename T> T __nac3_int_exp_impl(T base, T exp)
+{
+    T res = 1;
+    /* repeated squaring method */
+    do
+    {
+        if (exp & 1)
+        {
+            res *= base; /* for n odd */
+        }
+        exp >>= 1;
+        base *= base;
+    } while (exp);
+    return res;
+}
+} // namespace
+
+extern "C"
+{
+#define DEF_nac3_int_exp_(T)                                                                                           \
+    T __nac3_int_exp_##T(T base, T exp)                                                                                \
+    {                                                                                                                  \
+        return __nac3_int_exp_impl(base, exp);                                                                         \
+    }
+
+    DEF_nac3_int_exp_(int32_t) DEF_nac3_int_exp_(int64_t) DEF_nac3_int_exp_(uint32_t) DEF_nac3_int_exp_(uint64_t)
+
+        SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len)
+    {
+        if (i < 0)
+        {
+            i = len + i;
+        }
+        if (i < 0)
+        {
+            return 0;
+        }
+        else if (i > len)
+        {
+            return len;
+        }
+        return i;
+    }
+
+    SliceIndex __nac3_range_slice_len(const SliceIndex start, const SliceIndex end, const SliceIndex step)
+    {
+        SliceIndex diff = end - start;
+        if (diff > 0 && step > 0)
+        {
+            return ((diff - 1) / step) + 1;
+        }
+        else if (diff < 0 && step < 0)
+        {
+            return ((diff + 1) / step) + 1;
+        }
+        else
+        {
+            return 0;
+        }
+    }
+
+    // Handle list assignment and dropping part of the list when
+    // both dest_step and src_step are +1.
+    // - All the index must *not* be out-of-bound or negative,
+    // - The end index is *inclusive*,
+    // - The length of src and dest slice size should already
+    // be checked: if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest)
+    SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start, SliceIndex dest_end, SliceIndex dest_step,
+                                                 uint8_t *dest_arr, SliceIndex dest_arr_len, SliceIndex src_start,
+                                                 SliceIndex src_end, SliceIndex src_step, uint8_t *src_arr,
+                                                 SliceIndex src_arr_len, const SliceIndex size)
+    {
+        /* if dest_arr_len == 0, do nothing since we do not support extending list */
+        if (dest_arr_len == 0)
+            return dest_arr_len;
+        /* if both step is 1, memmove directly, handle the dropping of the list, and shrink size */
+        if (src_step == dest_step && dest_step == 1)
+        {
+            const SliceIndex src_len = (src_end >= src_start) ? (src_end - src_start + 1) : 0;
+            const SliceIndex dest_len = (dest_end >= dest_start) ? (dest_end - dest_start + 1) : 0;
+            if (src_len > 0)
+            {
+                __builtin_memmove(dest_arr + dest_start * size, src_arr + src_start * size, src_len * size);
+            }
+            if (dest_len > 0)
+            {
+                /* dropping */
+                __builtin_memmove(dest_arr + (dest_start + src_len) * size, dest_arr + (dest_end + 1) * size,
+                                  (dest_arr_len - dest_end - 1) * size);
+            }
+            /* shrink size */
+            return dest_arr_len - (dest_len - src_len);
+        }
+        /* if two range overlaps, need alloca */
+        uint8_t need_alloca = (dest_arr == src_arr) && !(max(dest_start, dest_end) < min(src_start, src_end) ||
+                                                         max(src_start, src_end) < min(dest_start, dest_end));
+        if (need_alloca)
+        {
+            uint8_t *tmp = reinterpret_cast<uint8_t *>(__builtin_alloca(src_arr_len * size));
+            __builtin_memcpy(tmp, src_arr, src_arr_len * size);
+            src_arr = tmp;
+        }
+        SliceIndex src_ind = src_start;
+        SliceIndex dest_ind = dest_start;
+        for (; (src_step > 0) ? (src_ind <= src_end) : (src_ind >= src_end); src_ind += src_step, dest_ind += dest_step)
+        {
+            /* for constant optimization */
+            if (size == 1)
+            {
+                __builtin_memcpy(dest_arr + dest_ind, src_arr + src_ind, 1);
+            }
+            else if (size == 4)
+            {
+                __builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
+            }
+            else if (size == 8)
+            {
+                __builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
+            }
+            else
+            {
+                /* memcpy for var size, cannot overlap after previous alloca */
+                __builtin_memcpy(dest_arr + dest_ind * size, src_arr + src_ind * size, size);
+            }
+        }
+        /* only dest_step == 1 can we shrink the dest list. */
+        /* size should be ensured prior to calling this function */
+        if (dest_step == 1 && dest_end >= dest_start)
+        {
+            __builtin_memmove(dest_arr + dest_ind * size, dest_arr + (dest_end + 1) * size,
+                              (dest_arr_len - dest_end - 1) * size);
+            return dest_arr_len - (dest_end - dest_ind) - 1;
+        }
+        return dest_arr_len;
+    }
+
+    int32_t __nac3_isinf(double x)
+    {
+        return __builtin_isinf(x);
+    }
+
+    int32_t __nac3_isnan(double x)
+    {
+        return __builtin_isnan(x);
+    }
+
+    double tgamma(double arg);
+
+    double __nac3_gamma(double z)
+    {
+        // Handling for denormals
+        //     | x                 | Python gamma(x) | C tgamma(x) |
+        // --- | ----------------- | --------------- | ----------- |
+        // (1) | nan               | nan             | nan         |
+        // (2) | -inf              | -inf            | inf         |
+        // (3) | inf               | inf             | inf         |
+        // (4) | 0.0               | inf             | inf         |
+        // (5) | {-1.0, -2.0, ...} | inf             | nan         |
+
+        // (1)-(3)
+        if (__builtin_isinf(z) || __builtin_isnan(z))
+        {
+            return z;
+        }
+
+        double v = tgamma(z);
+
+        // (4)-(5)
+        return __builtin_isinf(v) || __builtin_isnan(v) ? __builtin_inf() : v;
+    }
+
+    double lgamma(double arg);
+
+    double __nac3_gammaln(double x)
+    {
+        // libm's handling of value overflows differs from scipy:
+        // - scipy: gammaln(-inf) -> -inf
+        // - libm : lgamma(-inf) -> inf
+
+        if (__builtin_isinf(x))
+        {
+            return x;
+        }
+
+        return lgamma(x);
+    }
+
+    double j0(double x);
+
+    double __nac3_j0(double x)
+    {
+        // libm's handling of value overflows differs from scipy:
+        // - scipy: j0(inf) -> nan
+        // - libm : j0(inf) -> 0.0
+
+        if (__builtin_isinf(x))
+        {
+            return __builtin_nan("");
+        }
+
+        return j0(x);
+    }
+} // extern "C"
--- a/nac3core/irrt/irrt/slice.hpp
+++ b/nac3core/irrt/irrt/slice.hpp
@ -1,28 +1,224 @@
 #pragma once

-#include "irrt/int_types.hpp"
+#include <irrt/debug.hpp>
+#include <irrt/exception.hpp>
+#include <irrt/int_types.hpp>
+#include <irrt/math_util.hpp>

-extern "C" {
-SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
-    if (i < 0) {
-        i = len + i;
-    }
-    if (i < 0) {
+namespace
+{
+namespace range
+{
+template <typename T> T len(T start, T stop, T step)
+{
+    // Reference: https://github.com/python/cpython/blob/9dbd12375561a393eaec4b21ee4ac568a407cdb0/Objects/rangeobject.c#L933
+    if (step > 0 && start < stop)
+        return 1 + (stop - 1 - start) / step;
+    else if (step < 0 && start > stop)
+        return 1 + (start - 1 - stop) / (-step);
+    else
        return 0;
-    } else if (i > len) {
-        return len;
+}
+} // namespace range
+
+/**
+ * @brief A Python range.
+ */
+template <typename T> struct Range
+{
+    T start;
+    T stop;
+    T step;
+
+    /**
+     * @brief Calculate the `len()` of this range.
+     */
+    template <typename SizeT> T len()
+    {
+        debug_assert(SizeT, step != 0);
+        return range::len(start, stop, step);
+    }
+};
+
+namespace slice
+{
+/**
+ * @brief Resolve a slice index under a given length like Python indexing.
+ *
+ * In Python, if you have a `list` of length 100, `list[-1]` resolves to
+ * `list[99]`, so `resolve_index_in_length_clamped(100, -1)` returns `99`.
+ *
+ * If `length` is 0, 0 is returned for any value of `index`.
+ *
+ * If `index` is out of bounds, clamps the returned value between `0` and
+ * `length - 1` (inclusive).
+ *
+ */
+template <typename T> T resolve_index_in_length_clamped(T length, T index)
+{
+    if (index < 0)
+    {
+        return max<T>(length + index, 0);
+    }
+    else
+    {
+        return min<T>(length, index);
    }
-    return i;
 }

-SliceIndex __nac3_range_slice_len(const SliceIndex start, const SliceIndex end, const SliceIndex step) {
-    SliceIndex diff = end - start;
-    if (diff > 0 && step > 0) {
-        return ((diff - 1) / step) + 1;
-    } else if (diff < 0 && step < 0) {
-        return ((diff + 1) / step) + 1;
-    } else {
-        return 0;
+/**
+ * @brief Like `resolve_index_in_length_clamped`, but returns `-1` if `index` is out of bounds.
+ */
+template <typename T> T resolve_index_in_length(T length, T index)
+{
+    T resolved = index < 0 ? length + index : index;
+    if (0 <= resolved && resolved < length)
+    {
+        return resolved;
+    }
+    else
+    {
+        return -1;
    }
 }
+
+/**
+ * @brief Resolve a slice as a range.
+ *
+ * In Python, this would be `range(*slice(start, stop, step).indices(length))`.
+ */
+template <typename T>
+void indices(bool start_defined, T start, bool stop_defined, T stop, bool step_defined, T step, T length,
+             T *range_start, T *range_stop, T *range_step)
+{
+    // Reference: https://github.com/python/cpython/blob/main/Objects/sliceobject.c#L388
+    *range_step = step_defined ? step : 1;
+    bool step_is_negative = *range_step < 0;
+
+    T lower, upper;
+    if (step_is_negative)
+    {
+        lower = -1;
+        upper = length - 1;
+    }
+    else
+    {
+        lower = 0;
+        upper = length;
+    }
+
+    if (start_defined)
+    {
+        *range_start = start < 0 ? max(lower, start + length) : min(upper, start);
+    }
+    else
+    {
+        *range_start = step_is_negative ? upper : lower;
+    }
+
+    if (stop_defined)
+    {
+        *range_stop = stop < 0 ? max(lower, stop + length) : min(upper, stop);
+    }
+    else
+    {
+        *range_stop = step_is_negative ? lower : upper;
+    }
+}
+} // namespace slice
+
+/**
+ * @brief A Python-like slice with **unresolved** indices.
+ */
+template <typename T> struct Slice
+{
+    bool start_defined;
+    T start;
+
+    bool stop_defined;
+    T stop;
+
+    bool step_defined;
+    T step;
+
+    Slice()
+    {
+        this->reset();
+    }
+
+    void reset()
+    {
+        this->start_defined = false;
+        this->stop_defined = false;
+        this->step_defined = false;
+    }
+
+    void set_start(T start)
+    {
+        this->start_defined = true;
+        this->start = start;
+    }
+
+    void set_stop(T stop)
+    {
+        this->stop_defined = true;
+        this->stop = stop;
+    }
+
+    void set_step(T step)
+    {
+        this->step_defined = true;
+        this->step = step;
+    }
+
+    /**
+     * @brief Resolve this slice as a range.
+     *
+     * In Python, this would be `range(*slice(start, stop, step).indices(length))`.
+     */
+    template <typename SizeT> Range<T> indices(T length)
+    {
+        // Reference: https://github.com/python/cpython/blob/main/Objects/sliceobject.c#L388
+        debug_assert(SizeT, length >= 0);
+
+        Range<T> result;
+        slice::indices(start_defined, start, stop_defined, stop, step_defined, step, length, &result.start,
+                       &result.stop, &result.step);
+        return result;
+    }
+
+    /**
+     * @brief Like `.indices()` but with assertions.
+     */
+    template <typename SizeT> Range<T> indices_checked(T length)
+    {
+        // TODO: Switch to `SizeT length`
+
+        if (length < 0)
+        {
+            raise_exception(SizeT, EXN_VALUE_ERROR, "length should not be negative, got {0}", length, NO_PARAM,
+                            NO_PARAM);
+        }
+
+        if (this->step_defined && this->step == 0)
+        {
+            raise_exception(SizeT, EXN_VALUE_ERROR, "slice step cannot be zero", NO_PARAM, NO_PARAM, NO_PARAM);
+        }
+
+        return this->indices<SizeT>(length);
+    }
+};
+} // namespace
+
+extern "C"
+{
+    int32_t __nac3_range_len_i32(int32_t start, int32_t stop, int32_t step)
+    {
+        range::len<int32_t>(start, stop, step);
+    }
+
+    int32_t __nac3_range_len_i3264(int32_t start, int32_t stop, int32_t step)
+    {
+        range::len<int64_t>(start, stop, step);
+    }
 }
--- a/nac3core/src/codegen/builtin_fns.rs
+++ b/nac3core/src/codegen/builtin_fns.rs
--- a/nac3core/src/codegen/classes.rs
+++ b/nac3core/src/codegen/classes.rs
--- a/nac3core/src/codegen/concrete_type.rs
+++ b/nac3core/src/codegen/concrete_type.rs
@ -1,9 +1,3 @@
-use std::collections::HashMap;
-
-use indexmap::IndexMap;
-
-use nac3parser::ast::StrRef;
-
 use crate::{
    symbol_resolver::SymbolValue,
    toplevel::DefinitionId,
@ -15,6 +9,10 @@ use crate::{
    },
 };

+use indexmap::IndexMap;
+use nac3parser::ast::StrRef;
+use std::collections::HashMap;
+
 pub struct ConcreteTypeStore {
    store: Vec<ConcreteTypeEnum>,
 }
--- a/nac3core/src/codegen/expr.rs
+++ b/nac3core/src/codegen/expr.rs
--- a/nac3core/src/codegen/extern_fns.rs
+++ b/nac3core/src/codegen/extern_fns.rs
@ -1,10 +1,8 @@
-use inkwell::{
-    attributes::{Attribute, AttributeLoc},
-    values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue},
-};
+use inkwell::attributes::{Attribute, AttributeLoc};
+use inkwell::values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue};
 use itertools::Either;

-use super::CodeGenContext;
+use crate::codegen::CodeGenContext;

 /// Macro to generate extern function
 /// Both function return type and function parameter type are `FloatValue`
--- a/nac3core/src/codegen/generator.rs
+++ b/nac3core/src/codegen/generator.rs
@ -1,18 +1,16 @@
+use crate::{
+    codegen::{bool_to_i1, bool_to_i8, classes::ArraySliceValue, expr::*, stmt::*, CodeGenContext},
+    symbol_resolver::ValueEnum,
+    toplevel::{DefinitionId, TopLevelDef},
+    typecheck::typedef::{FunSignature, Type},
+};
 use inkwell::{
    context::Context,
    types::{BasicTypeEnum, IntType},
    values::{BasicValueEnum, IntValue, PointerValue},
 };
-
 use nac3parser::ast::{Expr, Stmt, StrRef};

-use super::{bool_to_i1, bool_to_i8, classes::ArraySliceValue, expr::*, stmt::*, CodeGenContext};
-use crate::{
-    symbol_resolver::ValueEnum,
-    toplevel::{DefinitionId, TopLevelDef},
-    typecheck::typedef::{FunSignature, Type},
-};
-
 pub trait CodeGenerator {
    /// Return the module name for the code generator.
    fn get_name(&self) -> &str;
--- a/nac3core/src/codegen/irrt/mod.rs
+++ b/nac3core/src/codegen/irrt/mod.rs
@ -1,30 +1,28 @@
+use crate::{symbol_resolver::SymbolResolver, typecheck::typedef::Type};
+
+use super::{
+    model::*,
+    object::{
+        list::List,
+        ndarray::{broadcast::ShapeEntry, indexing::NDIndex, nditer::NDIter, NDArray},
+    },
+    CodeGenContext, CodeGenerator,
+};
+use function::CallFunction;
 use inkwell::{
    attributes::{Attribute, AttributeLoc},
    context::Context,
    memory_buffer::MemoryBuffer,
    module::Module,
-    types::{BasicTypeEnum, IntType},
+    types::BasicTypeEnum,
    values::{BasicValue, BasicValueEnum, CallSiteValue, FloatValue, IntValue},
    AddressSpace, IntPredicate,
 };
 use itertools::Either;
-
 use nac3parser::ast::Expr;

-use super::{
-    classes::{
-        ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue,
-        TypedArrayLikeAccessor, TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
-    },
-    llvm_intrinsics,
-    macros::codegen_unreachable,
-    stmt::gen_for_callback_incrementing,
-    CodeGenContext, CodeGenerator,
-};
-use crate::{symbol_resolver::SymbolResolver, typecheck::typedef::Type};
-
 #[must_use]
-pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver) -> Module<'ctx> {
+pub fn load_irrt(ctx: &Context) -> Module {
    let bitcode_buf = MemoryBuffer::create_from_memory_range(
        include_bytes!(concat!(env!("OUT_DIR"), "/irrt.bc")),
        "irrt_bitcode_buffer",
@ -40,25 +38,6 @@ pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver)
        let function = irrt_mod.get_function(symbol).unwrap();
        function.add_attribute(AttributeLoc::Function, ctx.create_enum_attribute(inline_attr, 0));
    }
-
-    // Initialize all global `EXN_*` exception IDs in IRRT with the [`SymbolResolver`].
-    let exn_id_type = ctx.i32_type();
-    let errors = &[
-        ("EXN_INDEX_ERROR", "0:IndexError"),
-        ("EXN_VALUE_ERROR", "0:ValueError"),
-        ("EXN_ASSERTION_ERROR", "0:AssertionError"),
-        ("EXN_TYPE_ERROR", "0:TypeError"),
-    ];
-    for (irrt_name, symbol_name) in errors {
-        let exn_id = symbol_resolver.get_string_id(symbol_name);
-        let exn_id = exn_id_type.const_int(exn_id as u64, false).as_basic_value_enum();
-
-        let global = irrt_mod.get_global(irrt_name).unwrap_or_else(|| {
-            panic!("Exception symbol name '{irrt_name}' should exist in the IRRT LLVM module")
-        });
-        global.set_initializer(&exn_id);
-    }
-
    irrt_mod
 }

@ -76,7 +55,7 @@ pub fn integer_power<'ctx, G: CodeGenerator + ?Sized>(
        (64, 64, true) => "__nac3_int_exp_int64_t",
        (32, 32, false) => "__nac3_int_exp_uint32_t",
        (64, 64, false) => "__nac3_int_exp_uint64_t",
-        _ => codegen_unreachable!(ctx),
+        _ => unreachable!(),
    };
    let base_type = base.get_type();
    let pow_fun = ctx.module.get_function(symbol).unwrap_or_else(|| {
@ -347,12 +326,11 @@ pub fn list_slice_assignment<'ctx, G: CodeGenerator + ?Sized>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
    ty: BasicTypeEnum<'ctx>,
-    dest_arr: ListValue<'ctx>,
+    dest_arr: Instance<'ctx, Ptr<Struct<List<Any<'ctx>>>>>,
    dest_idx: (IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>),
-    src_arr: ListValue<'ctx>,
+    src_arr: Instance<'ctx, Ptr<Struct<List<Any<'ctx>>>>>,
    src_idx: (IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>),
 ) {
-    let size_ty = generator.get_size_type(ctx.ctx);
    let int8_ptr = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
    let int32 = ctx.ctx.i32_type();
    let (fun_symbol, elem_ptr_type) = ("__nac3_list_slice_assign_var_size", int8_ptr);
@ -378,16 +356,14 @@ pub fn list_slice_assignment<'ctx, G: CodeGenerator + ?Sized>(

    let zero = int32.const_zero();
    let one = int32.const_int(1, false);
-    let dest_arr_ptr = dest_arr.data().base_ptr(ctx, generator);
+
    let dest_arr_ptr =
-        ctx.builder.build_pointer_cast(dest_arr_ptr, elem_ptr_type, "dest_arr_ptr_cast").unwrap();
-    let dest_len = dest_arr.load_size(ctx, Some("dest.len"));
-    let dest_len = ctx.builder.build_int_truncate_or_bit_cast(dest_len, int32, "srclen32").unwrap();
-    let src_arr_ptr = src_arr.data().base_ptr(ctx, generator);
+        dest_arr.get(generator, ctx, |f| f.items).pointer_cast(generator, ctx, Int(Byte)).value;
    let src_arr_ptr =
-        ctx.builder.build_pointer_cast(src_arr_ptr, elem_ptr_type, "src_arr_ptr_cast").unwrap();
-    let src_len = src_arr.load_size(ctx, Some("src.len"));
-    let src_len = ctx.builder.build_int_truncate_or_bit_cast(src_len, int32, "srclen32").unwrap();
+        src_arr.get(generator, ctx, |f| f.items).pointer_cast(generator, ctx, Int(Byte)).value;
+
+    let dest_len = dest_arr.get(generator, ctx, |f| f.len).truncate(generator, ctx, Int32).value;
+    let src_len = src_arr.get(generator, ctx, |f| f.len).truncate(generator, ctx, Int32).value;

    // index in bound and positive should be done
    // assert if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest), and
@ -462,7 +438,7 @@ pub fn list_slice_assignment<'ctx, G: CodeGenerator + ?Sized>(
                    BasicTypeEnum::IntType(t) => t.size_of(),
                    BasicTypeEnum::PointerType(t) => t.size_of(),
                    BasicTypeEnum::StructType(t) => t.size_of().unwrap(),
-                    _ => codegen_unreachable!(ctx),
+                    _ => unreachable!(),
                };
                ctx.builder.build_int_truncate_or_bit_cast(s, int32, "size").unwrap()
            }
@ -483,8 +459,10 @@ pub fn list_slice_assignment<'ctx, G: CodeGenerator + ?Sized>(
    let cont_bb = ctx.ctx.append_basic_block(current, "cont");
    ctx.builder.build_conditional_branch(need_update, update_bb, cont_bb).unwrap();
    ctx.builder.position_at_end(update_bb);
-    let new_len = ctx.builder.build_int_z_extend_or_bit_cast(new_len, size_ty, "new_len").unwrap();
-    dest_arr.store_size(ctx, generator, new_len);
+
+    let new_len = Int(SizeT).z_extend_or_bit_cast(generator, ctx, new_len);
+    dest_arr.set(ctx, |f| f.len, new_len);
+
    ctx.builder.build_unconditional_branch(cont_bb).unwrap();
    ctx.builder.position_at_end(cont_bb);
 }
@ -584,369 +562,339 @@ pub fn call_j0<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> Flo
        .unwrap()
 }

-/// Generates a call to `__nac3_ndarray_calc_size`. Returns an [`IntValue`] representing the
-/// calculated total size.
-///
-/// * `dims` - An [`ArrayLikeIndexer`] containing the size of each dimension.
-/// * `range` - The dimension index to begin and end (exclusively) calculating the dimensions for,
-///   or [`None`] if starting from the first dimension and ending at the last dimension
-///   respectively.
-pub fn call_ndarray_calc_size<'ctx, G, Dims>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    dims: &Dims,
-    (begin, end): (Option<IntValue<'ctx>>, Option<IntValue<'ctx>>),
-) -> IntValue<'ctx>
-where
-    G: CodeGenerator + ?Sized,
-    Dims: ArrayLikeIndexer<'ctx>,
-{
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
-
-    let ndarray_calc_size_fn_name = match llvm_usize.get_bit_width() {
-        32 => "__nac3_ndarray_calc_size",
-        64 => "__nac3_ndarray_calc_size64",
-        bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
-    };
-    let ndarray_calc_size_fn_t = llvm_usize.fn_type(
-        &[llvm_pusize.into(), llvm_usize.into(), llvm_usize.into(), llvm_usize.into()],
-        false,
-    );
-    let ndarray_calc_size_fn =
-        ctx.module.get_function(ndarray_calc_size_fn_name).unwrap_or_else(|| {
-            ctx.module.add_function(ndarray_calc_size_fn_name, ndarray_calc_size_fn_t, None)
-        });
-
-    let begin = begin.unwrap_or_else(|| llvm_usize.const_zero());
-    let end = end.unwrap_or_else(|| dims.size(ctx, generator));
-    ctx.builder
-        .build_call(
-            ndarray_calc_size_fn,
-            &[
-                dims.base_ptr(ctx, generator).into(),
-                dims.size(ctx, generator).into(),
-                begin.into(),
-                end.into(),
-            ],
-            "",
-        )
-        .map(CallSiteValue::try_as_basic_value)
-        .map(|v| v.map_left(BasicValueEnum::into_int_value))
-        .map(Either::unwrap_left)
-        .unwrap()
+// When [`TypeContext::size_type`] is 32-bits, the function name is "{fn_name}".
+// When [`TypeContext::size_type`] is 64-bits, the function name is "{fn_name}64".
+#[must_use]
+pub fn get_sizet_dependent_function_name<G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &CodeGenContext<'_, '_>,
+    name: &str,
+) -> String {
+    let mut name = name.to_owned();
+    match generator.get_size_type(ctx.ctx).get_bit_width() {
+        32 => {}
+        64 => name.push_str("64"),
+        bit_width => {
+            panic!("Unsupported int type bit width {bit_width}, must be either 32-bits or 64-bits")
+        }
+    }
+    name
 }

-/// Generates a call to `__nac3_ndarray_calc_nd_indices`. Returns a [`TypeArrayLikeAdpater`]
-/// containing `i32` indices of the flattened index.
-///
-/// * `index` - The index to compute the multidimensional index for.
-/// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
-///   `NDArray`.
-pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    index: IntValue<'ctx>,
-    ndarray: NDArrayValue<'ctx>,
-) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
-    let llvm_void = ctx.ctx.void_type();
-    let llvm_i32 = ctx.ctx.i32_type();
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
-    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
+/// Initialize all global `EXN_*` exception IDs in IRRT with the [`SymbolResolver`].
+pub fn setup_irrt_exceptions<'ctx>(
+    ctx: &'ctx Context,
+    module: &Module<'ctx>,
+    symbol_resolver: &dyn SymbolResolver,
+) {
+    let exn_id_type = ctx.i32_type();

-    let ndarray_calc_nd_indices_fn_name = match llvm_usize.get_bit_width() {
-        32 => "__nac3_ndarray_calc_nd_indices",
-        64 => "__nac3_ndarray_calc_nd_indices64",
-        bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
-    };
-    let ndarray_calc_nd_indices_fn =
-        ctx.module.get_function(ndarray_calc_nd_indices_fn_name).unwrap_or_else(|| {
-            let fn_type = llvm_void.fn_type(
-                &[llvm_usize.into(), llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into()],
-                false,
-            );
+    let errors = &[
+        ("EXN_INDEX_ERROR", "0:IndexError"),
+        ("EXN_VALUE_ERROR", "0:ValueError"),
+        ("EXN_ASSERTION_ERROR", "0:AssertionError"),
+        ("EXN_TYPE_ERROR", "0:TypeError"),
+    ];

-            ctx.module.add_function(ndarray_calc_nd_indices_fn_name, fn_type, None)
+    for (irrt_name, symbol_name) in errors {
+        let exn_id = symbol_resolver.get_string_id(symbol_name);
+        let exn_id = exn_id_type.const_int(exn_id as u64, false).as_basic_value_enum();
+
+        let global = module.get_global(irrt_name).unwrap_or_else(|| {
+            panic!("Exception symbol name '{irrt_name}' should exist in the IRRT LLVM module")
        });
-
-    let ndarray_num_dims = ndarray.load_ndims(ctx);
-    let ndarray_dims = ndarray.dim_sizes();
-
-    let indices = ctx.builder.build_array_alloca(llvm_i32, ndarray_num_dims, "").unwrap();
-
-    ctx.builder
-        .build_call(
-            ndarray_calc_nd_indices_fn,
-            &[
-                index.into(),
-                ndarray_dims.base_ptr(ctx, generator).into(),
-                ndarray_num_dims.into(),
-                indices.into(),
-            ],
-            "",
-        )
-        .unwrap();
-
-    TypedArrayLikeAdapter::from(
-        ArraySliceValue::from_ptr_val(indices, ndarray_num_dims, None),
-        Box::new(|_, v| v.into_int_value()),
-        Box::new(|_, v| v.into()),
-    )
+        global.set_initializer(&exn_id);
+    }
 }

-fn call_ndarray_flatten_index_impl<'ctx, G, Indices>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    ndarray: NDArrayValue<'ctx>,
-    indices: &Indices,
-) -> IntValue<'ctx>
-where
-    G: CodeGenerator + ?Sized,
-    Indices: ArrayLikeIndexer<'ctx>,
-{
-    let llvm_i32 = ctx.ctx.i32_type();
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
-    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
-
-    debug_assert_eq!(
-        IntType::try_from(indices.element_type(ctx, generator))
-            .map(IntType::get_bit_width)
-            .unwrap_or_default(),
-        llvm_i32.get_bit_width(),
-        "Expected i32 value for argument `indices` to `call_ndarray_flatten_index_impl`"
-    );
-    debug_assert_eq!(
-        indices.size(ctx, generator).get_type().get_bit_width(),
-        llvm_usize.get_bit_width(),
-        "Expected usize integer value for argument `indices_size` to `call_ndarray_flatten_index_impl`"
-    );
-
-    let ndarray_flatten_index_fn_name = match llvm_usize.get_bit_width() {
-        32 => "__nac3_ndarray_flatten_index",
-        64 => "__nac3_ndarray_flatten_index64",
-        bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
-    };
-    let ndarray_flatten_index_fn =
-        ctx.module.get_function(ndarray_flatten_index_fn_name).unwrap_or_else(|| {
-            let fn_type = llvm_usize.fn_type(
-                &[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_usize.into()],
-                false,
-            );
-
-            ctx.module.add_function(ndarray_flatten_index_fn_name, fn_type, None)
-        });
-
-    let ndarray_num_dims = ndarray.load_ndims(ctx);
-    let ndarray_dims = ndarray.dim_sizes();
-
-    let index = ctx
-        .builder
-        .build_call(
-            ndarray_flatten_index_fn,
-            &[
-                ndarray_dims.base_ptr(ctx, generator).into(),
-                ndarray_num_dims.into(),
-                indices.base_ptr(ctx, generator).into(),
-                indices.size(ctx, generator).into(),
-            ],
-            "",
-        )
-        .map(CallSiteValue::try_as_basic_value)
-        .map(|v| v.map_left(BasicValueEnum::into_int_value))
-        .map(Either::unwrap_left)
-        .unwrap();
-
-    index
-}
-
-/// Generates a call to `__nac3_ndarray_flatten_index`. Returns the flattened index for the
-/// multidimensional index.
-///
-/// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
-///   `NDArray`.
-/// * `indices` - The multidimensional index to compute the flattened index for.
-pub fn call_ndarray_flatten_index<'ctx, G, Index>(
+pub fn call_nac3_range_len_i32<'ctx, G: CodeGenerator + ?Sized>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
-    ndarray: NDArrayValue<'ctx>,
-    indices: &Index,
-) -> IntValue<'ctx>
-where
-    G: CodeGenerator + ?Sized,
-    Index: ArrayLikeIndexer<'ctx>,
-{
-    call_ndarray_flatten_index_impl(generator, ctx, ndarray, indices)
+    start: Instance<'ctx, Int<Int32>>,
+    stop: Instance<'ctx, Int<Int32>>,
+    step: Instance<'ctx, Int<Int32>>,
+) -> Instance<'ctx, Int<Int32>> {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_range_len_i32");
+    CallFunction::begin(generator, ctx, &name)
+        .arg(start)
+        .arg(stop)
+        .arg(step)
+        .returning_auto("range_len")
 }

-/// Generates a call to `__nac3_ndarray_calc_broadcast`. Returns a tuple containing the number of
-/// dimension and size of each dimension of the resultant `ndarray`.
-pub fn call_ndarray_calc_broadcast<'ctx, G: CodeGenerator + ?Sized>(
+pub fn call_nac3_ndarray_util_assert_shape_no_negative<'ctx, G: CodeGenerator + ?Sized>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
-    lhs: NDArrayValue<'ctx>,
-    rhs: NDArrayValue<'ctx>,
-) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
-
-    let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
-        32 => "__nac3_ndarray_calc_broadcast",
-        64 => "__nac3_ndarray_calc_broadcast64",
-        bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
-    };
-    let ndarray_calc_broadcast_fn =
-        ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
-            let fn_type = llvm_usize.fn_type(
-                &[
-                    llvm_pusize.into(),
-                    llvm_usize.into(),
-                    llvm_pusize.into(),
-                    llvm_usize.into(),
-                    llvm_pusize.into(),
-                ],
-                false,
-            );
-
-            ctx.module.add_function(ndarray_calc_broadcast_fn_name, fn_type, None)
-        });
-
-    let lhs_ndims = lhs.load_ndims(ctx);
-    let rhs_ndims = rhs.load_ndims(ctx);
-    let min_ndims = llvm_intrinsics::call_int_umin(ctx, lhs_ndims, rhs_ndims, None);
-
-    gen_for_callback_incrementing(
+    ndims: Instance<'ctx, Int<SizeT>>,
+    shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name = get_sizet_dependent_function_name(
        generator,
        ctx,
-        None,
-        llvm_usize.const_zero(),
-        (min_ndims, false),
-        |generator, ctx, _, idx| {
-            let idx = ctx.builder.build_int_sub(min_ndims, idx, "").unwrap();
-            let (lhs_dim_sz, rhs_dim_sz) = unsafe {
-                (
-                    lhs.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None),
-                    rhs.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None),
-                )
-            };
-
-            let llvm_usize_const_one = llvm_usize.const_int(1, false);
-            let lhs_eqz = ctx
-                .builder
-                .build_int_compare(IntPredicate::EQ, lhs_dim_sz, llvm_usize_const_one, "")
-                .unwrap();
-            let rhs_eqz = ctx
-                .builder
-                .build_int_compare(IntPredicate::EQ, rhs_dim_sz, llvm_usize_const_one, "")
-                .unwrap();
-            let lhs_or_rhs_eqz = ctx.builder.build_or(lhs_eqz, rhs_eqz, "").unwrap();
-
-            let lhs_eq_rhs = ctx
-                .builder
-                .build_int_compare(IntPredicate::EQ, lhs_dim_sz, rhs_dim_sz, "")
-                .unwrap();
-
-            let is_compatible = ctx.builder.build_or(lhs_or_rhs_eqz, lhs_eq_rhs, "").unwrap();
-
-            ctx.make_assert(
-                generator,
-                is_compatible,
-                "0:ValueError",
-                "operands could not be broadcast together",
-                [None, None, None],
-                ctx.current_loc,
-            );
-
-            Ok(())
-        },
-        llvm_usize.const_int(1, false),
-    )
-    .unwrap();
-
-    let max_ndims = llvm_intrinsics::call_int_umax(ctx, lhs_ndims, rhs_ndims, None);
-    let lhs_dims = lhs.dim_sizes().base_ptr(ctx, generator);
-    let lhs_ndims = lhs.load_ndims(ctx);
-    let rhs_dims = rhs.dim_sizes().base_ptr(ctx, generator);
-    let rhs_ndims = rhs.load_ndims(ctx);
-    let out_dims = ctx.builder.build_array_alloca(llvm_usize, max_ndims, "").unwrap();
-    let out_dims = ArraySliceValue::from_ptr_val(out_dims, max_ndims, None);
-
-    ctx.builder
-        .build_call(
-            ndarray_calc_broadcast_fn,
-            &[
-                lhs_dims.into(),
-                lhs_ndims.into(),
-                rhs_dims.into(),
-                rhs_ndims.into(),
-                out_dims.base_ptr(ctx, generator).into(),
-            ],
-            "",
-        )
-        .unwrap();
-
-    TypedArrayLikeAdapter::from(
-        out_dims,
-        Box::new(|_, v| v.into_int_value()),
-        Box::new(|_, v| v.into()),
-    )
+        "__nac3_ndarray_util_assert_shape_no_negative",
+    );
+    CallFunction::begin(generator, ctx, &name).arg(ndims).arg(shape).returning_void();
 }

-/// Generates a call to `__nac3_ndarray_calc_broadcast_idx`. Returns an [`ArrayAllocaValue`]
-/// containing the indices used for accessing `array` corresponding to the index of the broadcasted
-/// array `broadcast_idx`.
-pub fn call_ndarray_calc_broadcast_index<
-    'ctx,
-    G: CodeGenerator + ?Sized,
-    BroadcastIdx: UntypedArrayLikeAccessor<'ctx>,
->(
+pub fn call_nac3_ndarray_util_assert_output_shape_same<'ctx, G: CodeGenerator + ?Sized>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
-    array: NDArrayValue<'ctx>,
-    broadcast_idx: &BroadcastIdx,
-) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
-    let llvm_i32 = ctx.ctx.i32_type();
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
-    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
-
-    let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
-        32 => "__nac3_ndarray_calc_broadcast_idx",
-        64 => "__nac3_ndarray_calc_broadcast_idx64",
-        bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
-    };
-    let ndarray_calc_broadcast_fn =
-        ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
-            let fn_type = llvm_usize.fn_type(
-                &[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_pi32.into()],
-                false,
-            );
-
-            ctx.module.add_function(ndarray_calc_broadcast_fn_name, fn_type, None)
-        });
-
-    let broadcast_size = broadcast_idx.size(ctx, generator);
-    let out_idx = ctx.builder.build_array_alloca(llvm_i32, broadcast_size, "").unwrap();
-
-    let array_dims = array.dim_sizes().base_ptr(ctx, generator);
-    let array_ndims = array.load_ndims(ctx);
-    let broadcast_idx_ptr = unsafe {
-        broadcast_idx.ptr_offset_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
-    };
-
-    ctx.builder
-        .build_call(
-            ndarray_calc_broadcast_fn,
-            &[array_dims.into(), array_ndims.into(), broadcast_idx_ptr.into(), out_idx.into()],
-            "",
-        )
-        .unwrap();
-
-    TypedArrayLikeAdapter::from(
-        ArraySliceValue::from_ptr_val(out_idx, broadcast_size, None),
-        Box::new(|_, v| v.into_int_value()),
-        Box::new(|_, v| v.into()),
-    )
+    ndarray_ndims: Instance<'ctx, Int<SizeT>>,
+    ndarray_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    output_ndims: Instance<'ctx, Int<SizeT>>,
+    output_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name = get_sizet_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_util_assert_output_shape_same",
+    );
+    CallFunction::begin(generator, ctx, &name)
+        .arg(ndarray_ndims)
+        .arg(ndarray_shape)
+        .arg(output_ndims)
+        .arg(output_shape)
+        .returning_void();
+}
+
+pub fn call_nac3_ndarray_size<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) -> Instance<'ctx, Int<SizeT>> {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_size");
+    CallFunction::begin(generator, ctx, &name).arg(ndarray).returning_auto("size")
+}
+
+pub fn call_nac3_ndarray_nbytes<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) -> Instance<'ctx, Int<SizeT>> {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_nbytes");
+    CallFunction::begin(generator, ctx, &name).arg(ndarray).returning_auto("nbytes")
+}
+
+pub fn call_nac3_ndarray_len<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) -> Instance<'ctx, Int<SizeT>> {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_len");
+    CallFunction::begin(generator, ctx, &name).arg(ndarray).returning_auto("len")
+}
+
+pub fn call_nac3_ndarray_is_c_contiguous<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) -> Instance<'ctx, Int<Bool>> {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_is_c_contiguous");
+    CallFunction::begin(generator, ctx, &name).arg(ndarray).returning_auto("is_c_contiguous")
+}
+
+pub fn call_nac3_ndarray_get_nth_pelement<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    index: Instance<'ctx, Int<SizeT>>,
+) -> Instance<'ctx, Ptr<Int<Byte>>> {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_get_nth_pelement");
+    CallFunction::begin(generator, ctx, &name).arg(ndarray).arg(index).returning_auto("pelement")
+}
+
+pub fn call_nac3_ndarray_get_pelement_by_indices<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    indices: Instance<'ctx, Ptr<Int<SizeT>>>,
+) -> Instance<'ctx, Ptr<Int<Byte>>> {
+    let name =
+        get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_get_pelement_by_indices");
+    CallFunction::begin(generator, ctx, &name).arg(ndarray).arg(indices).returning_auto("pelement")
+}
+
+pub fn call_nac3_ndarray_set_strides_by_shape<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) {
+    let name =
+        get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_set_strides_by_shape");
+    CallFunction::begin(generator, ctx, &name).arg(ndarray).returning_void();
+}
+
+pub fn call_nac3_ndarray_copy_data<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    src_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    dst_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_copy_data");
+    CallFunction::begin(generator, ctx, &name).arg(src_ndarray).arg(dst_ndarray).returning_void();
+}
+
+pub fn call_nac3_nditer_initialize<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    iter: Instance<'ctx, Ptr<Struct<NDIter>>>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    indices: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_nditer_initialize");
+    CallFunction::begin(generator, ctx, &name).arg(iter).arg(ndarray).arg(indices).returning_void();
+}
+
+pub fn call_nac3_nditer_has_next<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    iter: Instance<'ctx, Ptr<Struct<NDIter>>>,
+) -> Instance<'ctx, Int<Bool>> {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_nditer_has_next");
+    CallFunction::begin(generator, ctx, &name).arg(iter).returning_auto("has_next")
+}
+
+pub fn call_nac3_nditer_next<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    iter: Instance<'ctx, Ptr<Struct<NDIter>>>,
+) {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_nditer_next");
+    CallFunction::begin(generator, ctx, &name).arg(iter).returning_void();
+}
+
+pub fn call_nac3_ndarray_index<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    num_indices: Instance<'ctx, Int<SizeT>>,
+    indices: Instance<'ctx, Ptr<Struct<NDIndex>>>,
+    src_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    dst_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_index");
+    CallFunction::begin(generator, ctx, &name)
+        .arg(num_indices)
+        .arg(indices)
+        .arg(src_ndarray)
+        .arg(dst_ndarray)
+        .returning_void();
+}
+
+pub fn call_nac3_ndarray_array_set_and_validate_list_shape<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    list: Instance<'ctx, Ptr<Struct<List<Int<Byte>>>>>,
+    ndims: Instance<'ctx, Int<SizeT>>,
+    shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name = get_sizet_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_array_set_and_validate_list_shape",
+    );
+    CallFunction::begin(generator, ctx, &name).arg(list).arg(ndims).arg(shape).returning_void();
+}
+
+pub fn call_nac3_ndarray_array_write_list_to_array<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    list: Instance<'ctx, Ptr<Struct<List<Int<Byte>>>>>,
+    ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) {
+    let name = get_sizet_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_array_write_list_to_array",
+    );
+    CallFunction::begin(generator, ctx, &name).arg(list).arg(ndarray).returning_void();
+}
+
+pub fn call_nac3_ndarray_reshape_resolve_and_check_new_shape<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    size: Instance<'ctx, Int<SizeT>>,
+    new_ndims: Instance<'ctx, Int<SizeT>>,
+    new_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name = get_sizet_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_reshape_resolve_and_check_new_shape",
+    );
+    CallFunction::begin(generator, ctx, &name)
+        .arg(size)
+        .arg(new_ndims)
+        .arg(new_shape)
+        .returning_void();
+}
+
+pub fn call_nac3_ndarray_broadcast_to<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    src_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    dst_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+) {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_broadcast_to");
+    CallFunction::begin(generator, ctx, &name).arg(src_ndarray).arg(dst_ndarray).returning_void();
+}
+
+pub fn call_nac3_ndarray_broadcast_shapes<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    num_shape_entries: Instance<'ctx, Int<SizeT>>,
+    shape_entries: Instance<'ctx, Ptr<Struct<ShapeEntry>>>,
+    dst_ndims: Instance<'ctx, Int<SizeT>>,
+    dst_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_broadcast_shapes");
+    CallFunction::begin(generator, ctx, &name)
+        .arg(num_shape_entries)
+        .arg(shape_entries)
+        .arg(dst_ndims)
+        .arg(dst_shape)
+        .returning_void();
+}
+
+pub fn call_nac3_ndarray_transpose<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    src_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    dst_ndarray: Instance<'ctx, Ptr<Struct<NDArray>>>,
+    num_axes: Instance<'ctx, Int<SizeT>>,
+    axes: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name = get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_transpose");
+    CallFunction::begin(generator, ctx, &name)
+        .arg(src_ndarray)
+        .arg(dst_ndarray)
+        .arg(num_axes)
+        .arg(axes)
+        .returning_void();
+}
+
+#[allow(clippy::too_many_arguments)]
+pub fn call_nac3_ndarray_matmul_calculate_shapes<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    a_ndims: Instance<'ctx, Int<SizeT>>,
+    a_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    b_ndims: Instance<'ctx, Int<SizeT>>,
+    b_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    final_ndims: Instance<'ctx, Int<SizeT>>,
+    new_a_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    new_b_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    dst_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    let name =
+        get_sizet_dependent_function_name(generator, ctx, "__nac3_ndarray_matmul_calculate_shapes");
+    CallFunction::begin(generator, ctx, &name)
+        .arg(a_ndims)
+        .arg(a_shape)
+        .arg(b_ndims)
+        .arg(b_shape)
+        .arg(final_ndims)
+        .arg(new_a_shape)
+        .arg(new_b_shape)
+        .arg(dst_shape)
+        .returning_void();
 }
--- a/nac3core/src/codegen/llvm_intrinsics.rs
+++ b/nac3core/src/codegen/llvm_intrinsics.rs
@ -1,14 +1,12 @@
-use inkwell::{
-    context::Context,
-    intrinsics::Intrinsic,
-    types::{AnyTypeEnum::IntType, FloatType},
-    values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue, PointerValue},
-    AddressSpace,
-};
+use crate::codegen::CodeGenContext;
+use inkwell::context::Context;
+use inkwell::intrinsics::Intrinsic;
+use inkwell::types::AnyTypeEnum::IntType;
+use inkwell::types::FloatType;
+use inkwell::values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue, PointerValue};
+use inkwell::AddressSpace;
 use itertools::Either;

-use super::CodeGenContext;
-
 /// Returns the string representation for the floating-point type `ft` when used in intrinsic
 /// functions.
 fn get_float_intrinsic_repr(ctx: &Context, ft: FloatType) -> &'static str {
@ -185,7 +183,7 @@ pub fn call_memcpy_generic<'ctx>(
        dest
    } else {
        ctx.builder
-            .build_bit_cast(dest, llvm_p0i8, "")
+            .build_bitcast(dest, llvm_p0i8, "")
            .map(BasicValueEnum::into_pointer_value)
            .unwrap()
    };
@ -193,7 +191,7 @@ pub fn call_memcpy_generic<'ctx>(
        src
    } else {
        ctx.builder
-            .build_bit_cast(src, llvm_p0i8, "")
+            .build_bitcast(src, llvm_p0i8, "")
            .map(BasicValueEnum::into_pointer_value)
            .unwrap()
    };
--- a/nac3core/src/codegen/mod.rs
+++ b/nac3core/src/codegen/mod.rs
@ -1,12 +1,11 @@
-use std::{
-    collections::{HashMap, HashSet},
-    sync::{
-        atomic::{AtomicBool, Ordering},
-        Arc,
+use crate::{
+    symbol_resolver::{StaticValue, SymbolResolver},
+    toplevel::{helper::PrimDef, TopLevelContext, TopLevelDef},
+    typecheck::{
+        type_inferencer::{CodeLocation, PrimitiveStore},
+        typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
    },
-    thread,
 };
-
 use crossbeam::channel::{unbounded, Receiver, Sender};
 use inkwell::{
    attributes::{Attribute, AttributeLoc},
@ -24,21 +23,16 @@ use inkwell::{
    AddressSpace, IntPredicate, OptimizationLevel,
 };
 use itertools::Itertools;
-use parking_lot::{Condvar, Mutex};
-
+use model::*;
 use nac3parser::ast::{Location, Stmt, StrRef};
-
-use crate::{
-    symbol_resolver::{StaticValue, SymbolResolver},
-    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, TopLevelContext, TopLevelDef},
-    typecheck::{
-        type_inferencer::{CodeLocation, PrimitiveStore},
-        typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
-    },
+use object::{list::List, ndarray::NDArray, range::Range};
+use parking_lot::{Condvar, Mutex};
+use std::collections::{HashMap, HashSet};
+use std::sync::{
+    atomic::{AtomicBool, Ordering},
+    Arc,
 };
-use classes::{ListType, NDArrayType, ProxyType, RangeType};
-use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
-pub use generator::{CodeGenerator, DefaultCodeGenerator};
+use std::thread;

 pub mod builtin_fns;
 pub mod classes;
@ -48,27 +42,16 @@ pub mod extern_fns;
 mod generator;
 pub mod irrt;
 pub mod llvm_intrinsics;
+pub mod model;
 pub mod numpy;
+pub mod object;
 pub mod stmt;

 #[cfg(test)]
 mod test;

-mod macros {
-    /// Codegen-variant of [`std::unreachable`] which accepts an instance of [`CodeGenContext`] as
-    /// its first argument to provide Python source information to indicate the codegen location
-    /// causing the assertion.
-    macro_rules! codegen_unreachable {
-        ($ctx:expr $(,)?) => {
-            std::unreachable!("unreachable code while processing {}", &$ctx.current_loc)
-        };
-        ($ctx:expr, $($arg:tt)*) => {
-            std::unreachable!("unreachable code while processing {}: {}", &$ctx.current_loc, std::format!("{}", std::format_args!($($arg)+)))
-        };
-    }
-
-    pub(crate) use codegen_unreachable;
-}
+use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
+pub use generator::{CodeGenerator, DefaultCodeGenerator};

 #[derive(Default)]
 pub struct StaticValueStore {
@ -504,17 +487,12 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
                                type_cache,
                                *params.iter().next().unwrap().1,
                            );
-
-                            ListType::new(generator, ctx, element_type).as_base_type().into()
+                            let item = Any(element_type);
+                            Ptr(Struct(List { item })).get_type(generator, ctx).as_basic_type_enum()
                        }

                        TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-                            let (dtype, _) = unpack_ndarray_var_tys(unifier, ty);
-                            let element_type = get_llvm_type(
-                                ctx, module, generator, unifier, top_level, type_cache, dtype,
-                            );
-
-                            NDArrayType::new(generator, ctx, element_type).as_base_type().into()
+                            Ptr(Struct(NDArray)).get_type(generator, ctx).as_basic_type_enum()
                        }

                        _ => unreachable!(
@ -742,7 +720,7 @@ pub fn gen_func_impl<
                Some(t) => t.as_basic_type_enum(),
            }
        }),
-        (primitives.range, RangeType::new(context).as_base_type().into()),
+        (primitives.range, Ptr(Range::<Int32>::default()).get_type(generator, context).into()),
        (primitives.exception, {
            let name = "Exception";
            if let Some(t) = module.get_struct_type(name) {
@ -852,9 +830,10 @@ pub fn gen_func_impl<
    builder.position_at_end(init_bb);
    let body_bb = context.append_basic_block(fn_val, "body");

-    // Store non-vararg argument values into local variables
    let mut var_assignment = HashMap::new();
    let offset = u32::from(has_sret);
+
+    // Store non-vararg argument values into local variables
    for (n, arg) in args.iter().enumerate().filter(|(_, arg)| !arg.is_vararg) {
        let param = fn_val.get_nth_param((n as u32) + offset).unwrap();
        let local_type = get_llvm_type(
--- a/nac3core/src/codegen/model/any.rs
+++ b/nac3core/src/codegen/model/any.rs
@ -0,0 +1,42 @@
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum},
+    values::BasicValueEnum,
+};
+
+use crate::codegen::CodeGenerator;
+
+use super::*;
+
+/// A [`Model`] of any [`BasicTypeEnum`].
+///
+/// Use this when you cannot know the type beforehand or cannot be abstracted with [`Model`].
+#[derive(Debug, Clone, Copy)]
+pub struct Any<'ctx>(pub BasicTypeEnum<'ctx>);
+
+impl<'ctx> Model<'ctx> for Any<'ctx> {
+    type Value = BasicValueEnum<'ctx>;
+    type Type = BasicTypeEnum<'ctx>;
+
+    fn get_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        _ctx: &'ctx Context,
+    ) -> Self::Type {
+        self.0
+    }
+
+    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &mut G,
+        _ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError> {
+        let ty = ty.as_basic_type_enum();
+        if ty == self.0 {
+            Ok(())
+        } else {
+            Err(ModelError(format!("Expecting {}, but got {}", self.0, ty)))
+        }
+    }
+}
--- a/nac3core/src/codegen/model/array.rs
+++ b/nac3core/src/codegen/model/array.rs
@ -0,0 +1,140 @@
+use std::fmt;
+
+use inkwell::{
+    context::Context,
+    types::{ArrayType, BasicType, BasicTypeEnum},
+    values::{ArrayValue, IntValue},
+};
+
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+use super::*;
+
+pub trait LenKind: fmt::Debug + Clone + Copy {
+    fn get_length(&self) -> u32;
+}
+
+/// A statically known length.
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Len<const N: u32>;
+
+/// A dynamically known length.
+#[derive(Debug, Clone, Copy)]
+pub struct AnyLen(pub u32);
+
+impl<const N: u32> LenKind for Len<N> {
+    fn get_length(&self) -> u32 {
+        N
+    }
+}
+
+impl LenKind for AnyLen {
+    fn get_length(&self) -> u32 {
+        self.0
+    }
+}
+
+/// A Model for an [`ArrayType`].
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Array<Len, Item> {
+    /// Length of this array.
+    pub len: Len,
+    /// [`Model`] of an array item.
+    pub item: Item,
+}
+
+impl<'ctx, Len: LenKind, Item: Model<'ctx>> Model<'ctx> for Array<Len, Item> {
+    type Value = ArrayValue<'ctx>;
+    type Type = ArrayType<'ctx>;
+
+    fn get_type<G: CodeGenerator + ?Sized>(&self, generator: &G, ctx: &'ctx Context) -> Self::Type {
+        self.item.get_type(generator, ctx).array_type(self.len.get_length())
+    }
+
+    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError> {
+        let ty = ty.as_basic_type_enum();
+        let BasicTypeEnum::ArrayType(ty) = ty else {
+            return Err(ModelError(format!("Expecting ArrayType, but got {ty:?}")));
+        };
+
+        if ty.len() != self.len.get_length() {
+            return Err(ModelError(format!(
+                "Expecting ArrayType with size {}, but got an ArrayType with size {}",
+                ty.len(),
+                self.len.get_length()
+            )));
+        }
+
+        self.item
+            .check_type(generator, ctx, ty.get_element_type())
+            .map_err(|err| err.under_context("an ArrayType"))?;
+
+        Ok(())
+    }
+}
+
+impl<'ctx, Len: LenKind, Item: Model<'ctx>> Instance<'ctx, Ptr<Array<Len, Item>>> {
+    /// Get the pointer to the `i`-th (0-based) array element.
+    pub fn gep(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        i: IntValue<'ctx>,
+    ) -> Instance<'ctx, Ptr<Item>> {
+        let zero = ctx.ctx.i32_type().const_zero();
+        let ptr = unsafe { ctx.builder.build_in_bounds_gep(self.value, &[zero, i], "").unwrap() };
+
+        Ptr(self.model.0.item).believe_value(ptr)
+    }
+
+    /// Like `gep` but `i` is a constant.
+    pub fn gep_const(&self, ctx: &CodeGenContext<'ctx, '_>, i: u64) -> Instance<'ctx, Ptr<Item>> {
+        assert!(
+            i < u64::from(self.model.0.len.get_length()),
+            "Index {i} is out of bounds. Array length = {}",
+            self.model.0.len.get_length()
+        );
+
+        let i = ctx.ctx.i32_type().const_int(i, false);
+        self.gep(ctx, i)
+    }
+
+    /// Convenience function equivalent to `.gep(...).load(...)`.
+    pub fn get<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        i: IntValue<'ctx>,
+    ) -> Instance<'ctx, Item> {
+        self.gep(ctx, i).load(generator, ctx)
+    }
+
+    /// Like `get` but `i` is a constant.
+    pub fn get_const<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        i: u64,
+    ) -> Instance<'ctx, Item> {
+        self.gep_const(ctx, i).load(generator, ctx)
+    }
+
+    /// Convenience function equivalent to `.gep(...).store(...)`.
+    pub fn set(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        i: IntValue<'ctx>,
+        value: Instance<'ctx, Item>,
+    ) {
+        self.gep(ctx, i).store(ctx, value);
+    }
+
+    /// Like `set` but `i` is a constant.
+    pub fn set_const(&self, ctx: &CodeGenContext<'ctx, '_>, i: u64, value: Instance<'ctx, Item>) {
+        self.gep_const(ctx, i).store(ctx, value);
+    }
+}
--- a/nac3core/src/codegen/model/core.rs
+++ b/nac3core/src/codegen/model/core.rs
@ -0,0 +1,156 @@
+use std::fmt;
+
+use inkwell::{context::Context, types::*, values::*};
+use itertools::Itertools;
+
+use super::*;
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+#[derive(Debug, Clone)]
+pub struct ModelError(pub String);
+
+impl ModelError {
+    pub(super) fn under_context(mut self, context: &str) -> Self {
+        self.0.push_str(" ... in ");
+        self.0.push_str(context);
+        self
+    }
+}
+
+pub trait Model<'ctx>: fmt::Debug + Clone + Copy {
+    type Value: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>>;
+    type Type: BasicType<'ctx>;
+
+    /// Return the [`BasicType`] of this model.
+    #[must_use]
+    fn get_type<G: CodeGenerator + ?Sized>(&self, generator: &G, ctx: &'ctx Context) -> Self::Type;
+
+    fn sizeof<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> IntValue<'ctx> {
+        self.get_type(generator, ctx).size_of().unwrap()
+    }
+
+    /// Check if a [`BasicType`] is the same type of this model.
+    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError>;
+
+    /// Create an instance from a value with [`Instance::model`] being this model.
+    ///
+    /// Caller must make sure the type of `value` and the type of this `model` are equivalent.
+    #[must_use]
+    fn believe_value(&self, value: Self::Value) -> Instance<'ctx, Self> {
+        Instance { model: *self, value }
+    }
+
+    /// Check if a [`BasicValue`]'s type is equivalent to the type of this model.
+    /// Wrap it into an [`Instance`] if it is.
+    fn check_value<V: BasicValue<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        value: V,
+    ) -> Result<Instance<'ctx, Self>, ModelError> {
+        let value = value.as_basic_value_enum();
+        self.check_type(generator, ctx, value.get_type())
+            .map_err(|err| err.under_context(format!("the value {value:?}").as_str()))?;
+
+        let Ok(value) = Self::Value::try_from(value) else {
+            unreachable!("check_type() has bad implementation")
+        };
+        Ok(self.believe_value(value))
+    }
+
+    // Allocate a value on the stack and return its pointer.
+    fn alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Ptr<Self>> {
+        let p = ctx.builder.build_alloca(self.get_type(generator, ctx.ctx), "").unwrap();
+        Ptr(*self).believe_value(p)
+    }
+
+    // Allocate an array on the stack and return its pointer.
+    fn array_alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        len: IntValue<'ctx>,
+    ) -> Instance<'ctx, Ptr<Self>> {
+        let p = ctx.builder.build_array_alloca(self.get_type(generator, ctx.ctx), len, "").unwrap();
+        Ptr(*self).believe_value(p)
+    }
+
+    fn var_alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&str>,
+    ) -> Result<Instance<'ctx, Ptr<Self>>, String> {
+        let ty = self.get_type(generator, ctx.ctx).as_basic_type_enum();
+        let p = generator.gen_var_alloc(ctx, ty, name)?;
+        Ok(Ptr(*self).believe_value(p))
+    }
+
+    fn array_var_alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        len: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> Result<Instance<'ctx, Ptr<Self>>, String> {
+        // TODO: Remove ArraySliceValue
+        let ty = self.get_type(generator, ctx.ctx).as_basic_type_enum();
+        let p = generator.gen_array_var_alloc(ctx, ty, len, name)?;
+        Ok(Ptr(*self).believe_value(PointerValue::from(p)))
+    }
+
+    fn const_array<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        values: &[Instance<'ctx, Self>],
+    ) -> Instance<'ctx, Array<AnyLen, Self>> {
+        macro_rules! make {
+            ($t:expr, $into_value:expr) => {
+                $t.const_array(
+                    &values
+                        .iter()
+                        .map(|x| $into_value(x.value.as_basic_value_enum()))
+                        .collect_vec(),
+                )
+            };
+        }
+
+        let value = match self.get_type(generator, ctx).as_basic_type_enum() {
+            BasicTypeEnum::ArrayType(t) => make!(t, BasicValueEnum::into_array_value),
+            BasicTypeEnum::IntType(t) => make!(t, BasicValueEnum::into_int_value),
+            BasicTypeEnum::FloatType(t) => make!(t, BasicValueEnum::into_float_value),
+            BasicTypeEnum::PointerType(t) => make!(t, BasicValueEnum::into_pointer_value),
+            BasicTypeEnum::StructType(t) => make!(t, BasicValueEnum::into_struct_value),
+            BasicTypeEnum::VectorType(t) => make!(t, BasicValueEnum::into_vector_value),
+        };
+
+        Array { len: AnyLen(values.len() as u32), item: *self }
+            .check_value(generator, ctx, value)
+            .unwrap()
+    }
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct Instance<'ctx, M: Model<'ctx>> {
+    /// The model of this instance.
+    pub model: M,
+    /// The value of this instance.
+    ///
+    /// Caller must make sure the type of `value` and the type of this `model` are equivalent,
+    /// down to having the same [`IntType::get_bit_width`] in case of [`IntType`] for example.
+    pub value: M::Value,
+}
--- a/nac3core/src/codegen/model/float.rs
+++ b/nac3core/src/codegen/model/float.rs
@ -0,0 +1,87 @@
+use std::fmt;
+
+use inkwell::{context::Context, types::FloatType, values::FloatValue};
+
+use crate::codegen::CodeGenerator;
+
+use super::*;
+
+pub trait FloatKind<'ctx>: fmt::Debug + Clone + Copy {
+    fn get_float_type<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &'ctx Context,
+    ) -> FloatType<'ctx>;
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Float32;
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Float64;
+
+impl<'ctx> FloatKind<'ctx> for Float32 {
+    fn get_float_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        ctx: &'ctx Context,
+    ) -> FloatType<'ctx> {
+        ctx.f32_type()
+    }
+}
+
+impl<'ctx> FloatKind<'ctx> for Float64 {
+    fn get_float_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        ctx: &'ctx Context,
+    ) -> FloatType<'ctx> {
+        ctx.f64_type()
+    }
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct AnyFloat<'ctx>(FloatType<'ctx>);
+
+impl<'ctx> FloatKind<'ctx> for AnyFloat<'ctx> {
+    fn get_float_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        _ctx: &'ctx Context,
+    ) -> FloatType<'ctx> {
+        self.0
+    }
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Float<N>(pub N);
+
+impl<'ctx, N: FloatKind<'ctx>> Model<'ctx> for Float<N> {
+    type Value = FloatValue<'ctx>;
+    type Type = FloatType<'ctx>;
+
+    fn get_type<G: CodeGenerator + ?Sized>(&self, generator: &G, ctx: &'ctx Context) -> Self::Type {
+        self.0.get_float_type(generator, ctx)
+    }
+
+    fn check_type<T: inkwell::types::BasicType<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError> {
+        let ty = ty.as_basic_type_enum();
+        let Ok(ty) = FloatType::try_from(ty) else {
+            return Err(ModelError(format!("Expecting FloatType, but got {ty:?}")));
+        };
+
+        let exp_ty = self.0.get_float_type(generator, ctx);
+
+        // TODO: Inkwell does not have get_bit_width for FloatType?
+        // TODO: Quick hack for now, but does this actually work?
+        if ty != exp_ty {
+            return Err(ModelError(format!("Expecting {exp_ty:?}, but got {ty:?}")));
+        }
+
+        Ok(())
+    }
+}
--- a/nac3core/src/codegen/model/function.rs
+++ b/nac3core/src/codegen/model/function.rs
@ -0,0 +1,106 @@
+use inkwell::{
+    attributes::{Attribute, AttributeLoc},
+    types::{BasicMetadataTypeEnum, BasicType, FunctionType},
+    values::{AnyValue, BasicMetadataValueEnum, BasicValue, BasicValueEnum, CallSiteValue},
+};
+use itertools::Itertools;
+
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+use super::*;
+
+#[derive(Debug, Clone, Copy)]
+struct Arg<'ctx> {
+    ty: BasicMetadataTypeEnum<'ctx>,
+    val: BasicMetadataValueEnum<'ctx>,
+}
+
+/// A structure to construct & call an LLVM function.
+///
+/// This is a helper to reduce IRRT Inkwell function call boilerplate
+// TODO: Remove the lifetimes somehow? There are 4 of them.
+pub struct CallFunction<'ctx, 'a, 'b, 'c, 'd, G: CodeGenerator + ?Sized> {
+    generator: &'d mut G,
+    ctx: &'b CodeGenContext<'ctx, 'a>,
+    /// Function name
+    name: &'c str,
+    /// Call arguments
+    args: Vec<Arg<'ctx>>,
+    /// LLVM function Attributes
+    attrs: Vec<&'static str>,
+}
+
+impl<'ctx, 'a, 'b, 'c, 'd, G: CodeGenerator + ?Sized> CallFunction<'ctx, 'a, 'b, 'c, 'd, G> {
+    pub fn begin(generator: &'d mut G, ctx: &'b CodeGenContext<'ctx, 'a>, name: &'c str) -> Self {
+        CallFunction { generator, ctx, name, args: Vec::new(), attrs: Vec::new() }
+    }
+
+    /// Push a list of LLVM function attributes to the function declaration.
+    #[must_use]
+    pub fn attrs(mut self, attrs: Vec<&'static str>) -> Self {
+        self.attrs = attrs;
+        self
+    }
+
+    /// Push a call argument to the function call.
+    #[allow(clippy::needless_pass_by_value)]
+    #[must_use]
+    pub fn arg<M: Model<'ctx>>(mut self, arg: Instance<'ctx, M>) -> Self {
+        let arg = Arg {
+            ty: arg.model.get_type(self.generator, self.ctx.ctx).as_basic_type_enum().into(),
+            val: arg.value.as_basic_value_enum().into(),
+        };
+        self.args.push(arg);
+        self
+    }
+
+    /// Call the function and expect the function to return a value of type of `return_model`.
+    #[must_use]
+    pub fn returning<M: Model<'ctx>>(self, name: &str, return_model: M) -> Instance<'ctx, M> {
+        let ret_ty = return_model.get_type(self.generator, self.ctx.ctx);
+
+        let ret = self.get_function(|tys| ret_ty.fn_type(tys, false), name);
+        let ret = BasicValueEnum::try_from(ret.as_any_value_enum()).unwrap(); // Must work
+        let ret = return_model.check_value(self.generator, self.ctx.ctx, ret).unwrap(); // Must work
+        ret
+    }
+
+    /// Like [`CallFunction::returning_`] but `return_model` is automatically inferred.
+    #[must_use]
+    pub fn returning_auto<M: Model<'ctx> + Default>(self, name: &str) -> Instance<'ctx, M> {
+        self.returning(name, M::default())
+    }
+
+    /// Call the function and expect the function to return a void-type.
+    pub fn returning_void(self) {
+        let ret_ty = self.ctx.ctx.void_type();
+
+        let _ = self.get_function(|tys| ret_ty.fn_type(tys, false), "");
+    }
+
+    fn get_function<F>(&self, make_fn_type: F, return_value_name: &str) -> CallSiteValue<'ctx>
+    where
+        F: FnOnce(&[BasicMetadataTypeEnum<'ctx>]) -> FunctionType<'ctx>,
+    {
+        // Get the LLVM function.
+        let func = self.ctx.module.get_function(self.name).unwrap_or_else(|| {
+            // Declare the function if it doesn't exist.
+            let tys = self.args.iter().map(|arg| arg.ty).collect_vec();
+
+            let func_type = make_fn_type(&tys);
+            let func = self.ctx.module.add_function(self.name, func_type, None);
+
+            for attr in &self.attrs {
+                func.add_attribute(
+                    AttributeLoc::Function,
+                    self.ctx.ctx.create_enum_attribute(Attribute::get_named_enum_kind_id(attr), 0),
+                );
+            }
+
+            func
+        });
+
+        let vals = self.args.iter().map(|arg| arg.val).collect_vec();
+        self.ctx.builder.build_call(func, &vals, return_value_name).unwrap()
+    }
+}
--- a/nac3core/src/codegen/model/int.rs
+++ b/nac3core/src/codegen/model/int.rs
@ -0,0 +1,349 @@
+use std::fmt;
+
+use inkwell::{
+    context::Context,
+    types::{BasicType, IntType},
+    values::IntValue,
+    IntPredicate,
+};
+
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+use super::*;
+
+pub trait IntKind<'ctx>: fmt::Debug + Clone + Copy {
+    fn get_int_type<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &'ctx Context,
+    ) -> IntType<'ctx>;
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Bool;
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Byte;
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Int32;
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Int64;
+#[derive(Debug, Clone, Copy, Default)]
+pub struct SizeT;
+
+impl<'ctx> IntKind<'ctx> for Bool {
+    fn get_int_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        ctx: &'ctx Context,
+    ) -> IntType<'ctx> {
+        ctx.bool_type()
+    }
+}
+
+impl<'ctx> IntKind<'ctx> for Byte {
+    fn get_int_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        ctx: &'ctx Context,
+    ) -> IntType<'ctx> {
+        ctx.i8_type()
+    }
+}
+
+impl<'ctx> IntKind<'ctx> for Int32 {
+    fn get_int_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        ctx: &'ctx Context,
+    ) -> IntType<'ctx> {
+        ctx.i32_type()
+    }
+}
+
+impl<'ctx> IntKind<'ctx> for Int64 {
+    fn get_int_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        ctx: &'ctx Context,
+    ) -> IntType<'ctx> {
+        ctx.i64_type()
+    }
+}
+
+impl<'ctx> IntKind<'ctx> for SizeT {
+    fn get_int_type<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &'ctx Context,
+    ) -> IntType<'ctx> {
+        generator.get_size_type(ctx)
+    }
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct AnyInt<'ctx>(pub IntType<'ctx>);
+
+impl<'ctx> IntKind<'ctx> for AnyInt<'ctx> {
+    fn get_int_type<G: CodeGenerator + ?Sized>(
+        &self,
+        _generator: &G,
+        _ctx: &'ctx Context,
+    ) -> IntType<'ctx> {
+        self.0
+    }
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Int<N>(pub N);
+
+impl<'ctx, N: IntKind<'ctx>> Model<'ctx> for Int<N> {
+    type Value = IntValue<'ctx>;
+    type Type = IntType<'ctx>;
+
+    fn get_type<G: CodeGenerator + ?Sized>(&self, generator: &G, ctx: &'ctx Context) -> Self::Type {
+        self.0.get_int_type(generator, ctx)
+    }
+
+    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError> {
+        let ty = ty.as_basic_type_enum();
+        let Ok(ty) = IntType::try_from(ty) else {
+            return Err(ModelError(format!("Expecting IntType, but got {ty:?}")));
+        };
+
+        let exp_ty = self.0.get_int_type(generator, ctx);
+        if ty.get_bit_width() != exp_ty.get_bit_width() {
+            return Err(ModelError(format!(
+                "Expecting IntType to have {} bit(s), but got {} bit(s)",
+                exp_ty.get_bit_width(),
+                ty.get_bit_width()
+            )));
+        }
+
+        Ok(())
+    }
+}
+
+impl<'ctx, N: IntKind<'ctx>> Int<N> {
+    pub fn const_int<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        value: u64,
+    ) -> Instance<'ctx, Self> {
+        let value = self.get_type(generator, ctx).const_int(value, false);
+        self.believe_value(value)
+    }
+
+    pub fn const_0<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> Instance<'ctx, Self> {
+        let value = self.get_type(generator, ctx).const_zero();
+        self.believe_value(value)
+    }
+
+    pub fn const_1<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> Instance<'ctx, Self> {
+        self.const_int(generator, ctx, 1)
+    }
+
+    pub fn const_all_ones<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> Instance<'ctx, Self> {
+        let value = self.get_type(generator, ctx).const_all_ones();
+        self.believe_value(value)
+    }
+
+    pub fn s_extend_or_bit_cast<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> Instance<'ctx, Self> {
+        let value = ctx
+            .builder
+            .build_int_s_extend_or_bit_cast(value, self.get_type(generator, ctx.ctx), "")
+            .unwrap();
+        self.believe_value(value)
+    }
+
+    pub fn s_extend<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> Instance<'ctx, Self> {
+        let value =
+            ctx.builder.build_int_s_extend(value, self.get_type(generator, ctx.ctx), "").unwrap();
+        self.believe_value(value)
+    }
+
+    pub fn z_extend_or_bit_cast<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> Instance<'ctx, Self> {
+        let value = ctx
+            .builder
+            .build_int_z_extend_or_bit_cast(value, self.get_type(generator, ctx.ctx), "")
+            .unwrap();
+        self.believe_value(value)
+    }
+
+    pub fn z_extend<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> Instance<'ctx, Self> {
+        let value =
+            ctx.builder.build_int_z_extend(value, self.get_type(generator, ctx.ctx), "").unwrap();
+        self.believe_value(value)
+    }
+
+    pub fn truncate_or_bit_cast<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> Instance<'ctx, Self> {
+        let value = ctx
+            .builder
+            .build_int_truncate_or_bit_cast(value, self.get_type(generator, ctx.ctx), "")
+            .unwrap();
+        self.believe_value(value)
+    }
+
+    pub fn truncate<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+    ) -> Instance<'ctx, Self> {
+        let value =
+            ctx.builder.build_int_truncate(value, self.get_type(generator, ctx.ctx), "").unwrap();
+        self.believe_value(value)
+    }
+}
+
+impl Int<Bool> {
+    #[must_use]
+    pub fn const_false<'ctx, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> Instance<'ctx, Self> {
+        self.const_int(generator, ctx, 0)
+    }
+
+    #[must_use]
+    pub fn const_true<'ctx, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> Instance<'ctx, Self> {
+        self.const_int(generator, ctx, 1)
+    }
+}
+
+impl<'ctx, N: IntKind<'ctx>> Instance<'ctx, Int<N>> {
+    pub fn s_extend_or_bit_cast<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+    ) -> Instance<'ctx, Int<NewN>> {
+        Int(to_int_kind).s_extend_or_bit_cast(generator, ctx, self.value)
+    }
+
+    pub fn s_extend<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+    ) -> Instance<'ctx, Int<NewN>> {
+        Int(to_int_kind).s_extend(generator, ctx, self.value)
+    }
+
+    pub fn z_extend_or_bit_cast<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+    ) -> Instance<'ctx, Int<NewN>> {
+        Int(to_int_kind).z_extend_or_bit_cast(generator, ctx, self.value)
+    }
+
+    pub fn z_extend<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+    ) -> Instance<'ctx, Int<NewN>> {
+        Int(to_int_kind).z_extend(generator, ctx, self.value)
+    }
+
+    pub fn truncate_or_bit_cast<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+    ) -> Instance<'ctx, Int<NewN>> {
+        Int(to_int_kind).truncate_or_bit_cast(generator, ctx, self.value)
+    }
+
+    pub fn truncate<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+    ) -> Instance<'ctx, Int<NewN>> {
+        Int(to_int_kind).truncate(generator, ctx, self.value)
+    }
+
+    #[must_use]
+    pub fn add(&self, ctx: &CodeGenContext<'ctx, '_>, other: Self) -> Self {
+        let value = ctx.builder.build_int_add(self.value, other.value, "").unwrap();
+        self.model.believe_value(value)
+    }
+
+    #[must_use]
+    pub fn sub(&self, ctx: &CodeGenContext<'ctx, '_>, other: Self) -> Self {
+        let value = ctx.builder.build_int_sub(self.value, other.value, "").unwrap();
+        self.model.believe_value(value)
+    }
+
+    #[must_use]
+    pub fn mul(&self, ctx: &CodeGenContext<'ctx, '_>, other: Self) -> Self {
+        let value = ctx.builder.build_int_mul(self.value, other.value, "").unwrap();
+        self.model.believe_value(value)
+    }
+
+    pub fn compare(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        op: IntPredicate,
+        other: Self,
+    ) -> Instance<'ctx, Int<Bool>> {
+        let value = ctx.builder.build_int_compare(op, self.value, other.value, "").unwrap();
+        Int(Bool).believe_value(value)
+    }
+
+    #[must_use]
+    pub fn not(&self, ctx: &CodeGenContext<'ctx, '_>) -> Self {
+        let value = ctx.builder.build_not(self.value, "").unwrap();
+        self.model.believe_value(value)
+    }
+}
--- a/nac3core/src/codegen/model/mod.rs
+++ b/nac3core/src/codegen/model/mod.rs
@ -0,0 +1,17 @@
+mod any;
+mod array;
+mod core;
+mod float;
+pub mod function;
+mod int;
+mod ptr;
+mod structure;
+pub mod util;
+
+pub use any::*;
+pub use array::*;
+pub use core::*;
+pub use float::*;
+pub use int::*;
+pub use ptr::*;
+pub use structure::*;
--- a/nac3core/src/codegen/model/ptr.rs
+++ b/nac3core/src/codegen/model/ptr.rs
@ -0,0 +1,192 @@
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum, PointerType},
+    values::{IntValue, PointerValue},
+    AddressSpace,
+};
+
+use crate::codegen::{llvm_intrinsics::call_memcpy_generic, CodeGenContext, CodeGenerator};
+
+use super::*;
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Ptr<Item>(pub Item);
+
+impl<'ctx, Item: Model<'ctx>> Model<'ctx> for Ptr<Item> {
+    type Value = PointerValue<'ctx>;
+    type Type = PointerType<'ctx>;
+
+    fn get_type<G: CodeGenerator + ?Sized>(&self, generator: &G, ctx: &'ctx Context) -> Self::Type {
+        self.0.get_type(generator, ctx).ptr_type(AddressSpace::default())
+    }
+
+    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError> {
+        let ty = ty.as_basic_type_enum();
+        let Ok(ty) = PointerType::try_from(ty) else {
+            return Err(ModelError(format!("Expecting PointerType, but got {ty:?}")));
+        };
+
+        let elem_ty = ty.get_element_type();
+        let Ok(elem_ty) = BasicTypeEnum::try_from(elem_ty) else {
+            return Err(ModelError(format!(
+                "Expecting pointer element type to be a BasicTypeEnum, but got {elem_ty:?}"
+            )));
+        };
+
+        // TODO: inkwell `get_element_type()` will be deprecated.
+        // Remove the check for `get_element_type()` when the time comes.
+        self.0
+            .check_type(generator, ctx, elem_ty)
+            .map_err(|err| err.under_context("a PointerType"))?;
+
+        Ok(())
+    }
+}
+
+impl<'ctx, Element: Model<'ctx>> Ptr<Element> {
+    /// Return a ***constant*** nullptr.
+    pub fn nullptr<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> Instance<'ctx, Ptr<Element>> {
+        let ptr = self.get_type(generator, ctx).const_null();
+        self.believe_value(ptr)
+    }
+
+    /// Cast a pointer into this model with [`inkwell::builder::Builder::build_pointer_cast`]
+    pub fn pointer_cast<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        ptr: PointerValue<'ctx>,
+    ) -> Instance<'ctx, Ptr<Element>> {
+        let t = self.get_type(generator, ctx.ctx);
+        let ptr = ctx.builder.build_pointer_cast(ptr, t, "").unwrap();
+        self.believe_value(ptr)
+    }
+}
+
+impl<'ctx, Item: Model<'ctx>> Instance<'ctx, Ptr<Item>> {
+    /// Offset the pointer by [`inkwell::builder::Builder::build_in_bounds_gep`].
+    #[must_use]
+    pub fn offset(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        offset: IntValue<'ctx>,
+    ) -> Instance<'ctx, Ptr<Item>> {
+        let p = unsafe { ctx.builder.build_in_bounds_gep(self.value, &[offset], "").unwrap() };
+        self.model.believe_value(p)
+    }
+
+    /// Offset the pointer by [`inkwell::builder::Builder::build_in_bounds_gep`] by a constant offset.
+    #[must_use]
+    pub fn offset_const(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        offset: u64,
+    ) -> Instance<'ctx, Ptr<Item>> {
+        let offset = ctx.ctx.i32_type().const_int(offset, false);
+        self.offset(ctx, offset)
+    }
+
+    pub fn set_index(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        index: IntValue<'ctx>,
+        value: Instance<'ctx, Item>,
+    ) {
+        self.offset(ctx, index).store(ctx, value);
+    }
+
+    pub fn set_index_const(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        index: u64,
+        value: Instance<'ctx, Item>,
+    ) {
+        self.offset_const(ctx, index).store(ctx, value);
+    }
+
+    pub fn get_index<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        index: IntValue<'ctx>,
+    ) -> Instance<'ctx, Item> {
+        self.offset(ctx, index).load(generator, ctx)
+    }
+
+    pub fn get_index_const<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        index: u64,
+    ) -> Instance<'ctx, Item> {
+        self.offset_const(ctx, index).load(generator, ctx)
+    }
+
+    /// Load the value with [`inkwell::builder::Builder::build_load`].
+    pub fn load<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Item> {
+        let value = ctx.builder.build_load(self.value, "").unwrap();
+        self.model.0.check_value(generator, ctx.ctx, value).unwrap() // If unwrap() panics, there is a logic error.
+    }
+
+    /// Store a value with [`inkwell::builder::Builder::build_store`].
+    pub fn store(&self, ctx: &CodeGenContext<'ctx, '_>, value: Instance<'ctx, Item>) {
+        ctx.builder.build_store(self.value, value.value).unwrap();
+    }
+
+    /// Return a casted pointer of element type `NewElement` with [`inkwell::builder::Builder::build_pointer_cast`].
+    pub fn pointer_cast<NewItem: Model<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        new_item: NewItem,
+    ) -> Instance<'ctx, Ptr<NewItem>> {
+        Ptr(new_item).pointer_cast(generator, ctx, self.value)
+    }
+
+    /// Check if the pointer is null with [`inkwell::builder::Builder::build_is_null`].
+    pub fn is_null(&self, ctx: &CodeGenContext<'ctx, '_>) -> Instance<'ctx, Int<Bool>> {
+        let value = ctx.builder.build_is_null(self.value, "").unwrap();
+        Int(Bool).believe_value(value)
+    }
+
+    /// Check if the pointer is not null with [`inkwell::builder::Builder::build_is_not_null`].
+    pub fn is_not_null(&self, ctx: &CodeGenContext<'ctx, '_>) -> Instance<'ctx, Int<Bool>> {
+        let value = ctx.builder.build_is_not_null(self.value, "").unwrap();
+        Int(Bool).believe_value(value)
+    }
+
+    pub fn copy_from<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        source: Self,
+        num_items: IntValue<'ctx>,
+    ) {
+        let llvm_usize = generator.get_size_type(ctx.ctx);
+
+        // Force extend `num_items` and `itemsize` so their types would match.
+        let itemsize = self.model.sizeof(generator, ctx.ctx);
+        let itemsize =
+            ctx.builder.build_int_z_extend_or_bit_cast(itemsize, llvm_usize, "").unwrap();
+        let num_items =
+            ctx.builder.build_int_z_extend_or_bit_cast(num_items, llvm_usize, "").unwrap();
+
+        let totalsize = ctx.builder.build_int_mul(itemsize, num_items, "totalsize").unwrap();
+
+        let is_volatile = ctx.ctx.bool_type().const_zero(); // is_volatile = false
+        call_memcpy_generic(ctx, self.value, source.value, totalsize, is_volatile);
+    }
+}
--- a/nac3core/src/codegen/model/structure.rs
+++ b/nac3core/src/codegen/model/structure.rs
@ -0,0 +1,261 @@
+use std::fmt;
+
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum, StructType},
+    values::{BasicValueEnum, StructValue},
+};
+
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+use super::*;
+
+/// A traveral that traverses a Rust `struct` that is used to declare an LLVM's struct's field types.
+pub trait FieldTraversal<'ctx> {
+    /// Output type of [`FieldTraversal::add`].
+    type Out<M>;
+
+    /// Traverse through the type of a declared field and do something with it.
+    ///
+    /// * `name` - The cosmetic name of the LLVM field. Used for debugging.
+    /// * `model` - The [`Model`] representing the LLVM type of this field.
+    fn add<M: Model<'ctx>>(&mut self, name: &'static str, model: M) -> Self::Out<M>;
+
+    /// Like [`FieldTraversal::add`] but [`Model`] is automatically inferred from its [`Default`] trait.
+    fn add_auto<M: Model<'ctx> + Default>(&mut self, name: &'static str) -> Self::Out<M> {
+        self.add(name, M::default())
+    }
+}
+
+/// Descriptor of an LLVM struct field.
+#[derive(Debug, Clone, Copy)]
+pub struct GepField<M> {
+    /// The GEP index of this field. This is the index to use with `build_gep`.
+    pub gep_index: u64,
+    /// The cosmetic name of this field.
+    pub name: &'static str,
+    /// The [`Model`] of this field's type.
+    pub model: M,
+}
+
+/// A traversal to get the GEP index of fields.
+pub struct GepFieldTraversal {
+    /// The current GEP index.
+    gep_index_counter: u64,
+}
+
+impl<'ctx> FieldTraversal<'ctx> for GepFieldTraversal {
+    type Out<M> = GepField<M>;
+
+    fn add<M: Model<'ctx>>(&mut self, name: &'static str, model: M) -> Self::Out<M> {
+        let gep_index = self.gep_index_counter;
+        self.gep_index_counter += 1;
+        Self::Out { gep_index, name, model }
+    }
+}
+
+/// A traversal to collect the field types of a struct.
+///
+/// This is used to collect the field types for [`Context::struct_type`].
+struct TypeFieldTraversal<'ctx, 'a, G: CodeGenerator + ?Sized> {
+    generator: &'a G,
+    ctx: &'ctx Context,
+    /// The collected field types so far, in order.
+    field_types: Vec<BasicTypeEnum<'ctx>>,
+}
+
+impl<'ctx, 'a, G: CodeGenerator + ?Sized> FieldTraversal<'ctx> for TypeFieldTraversal<'ctx, 'a, G> {
+    type Out<M> = (); // Checking types return nothing.
+
+    fn add<M: Model<'ctx>>(&mut self, _name: &'static str, model: M) -> Self::Out<M> {
+        let t = model.get_type(self.generator, self.ctx).as_basic_type_enum();
+        self.field_types.push(t);
+    }
+}
+
+/// A traversal to check the types of a field for debug assertions.
+struct CheckTypeFieldTraversal<'ctx, 'a, G: CodeGenerator + ?Sized> {
+    generator: &'a mut G,
+    ctx: &'ctx Context,
+    /// The current GEP index, so we can tell the index of the field we are checking
+    /// and report the GEP index.
+    index: u32,
+    /// The [`StructType`] to check.
+    scrutinee: StructType<'ctx>,
+    /// A list of collected errors so far.
+    errors: Vec<ModelError>,
+}
+
+impl<'ctx, 'a, G: CodeGenerator + ?Sized> FieldTraversal<'ctx>
+    for CheckTypeFieldTraversal<'ctx, 'a, G>
+{
+    type Out<M> = (); // Checking types return nothing.
+
+    fn add<M: Model<'ctx>>(&mut self, name: &'static str, model: M) -> Self::Out<M> {
+        let i = self.index;
+        self.index += 1;
+
+        if let Some(t) = self.scrutinee.get_field_type_at_index(i) {
+            if let Err(err) = model.check_type(self.generator, self.ctx, t) {
+                self.errors.push(err.under_context(format!("field #{i} '{name}'").as_str()));
+            }
+        } // Otherwise, it will be caught by Struct's `check_type`.
+    }
+}
+
+pub trait StructKind<'ctx>: fmt::Debug + Clone + Copy {
+    type Fields<F: FieldTraversal<'ctx>>;
+
+    /// Traverse map through all fields of this [`StructKind`].
+    fn traverse_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F>;
+
+    /// Get a convenience structure to get a struct field's GEP index through its corresponding Rust field.
+    fn fields(&self) -> Self::Fields<GepFieldTraversal> {
+        self.traverse_fields(&mut GepFieldTraversal { gep_index_counter: 0 })
+    }
+
+    /// Get the LLVM [`StructType`] of this [`StructKind`].
+    fn get_struct_type<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &'ctx Context,
+    ) -> StructType<'ctx> {
+        let mut traversal = TypeFieldTraversal { generator, ctx, field_types: Vec::new() };
+        self.traverse_fields(&mut traversal);
+
+        ctx.struct_type(&traversal.field_types, false)
+    }
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Struct<S>(pub S);
+
+impl<'ctx, S: StructKind<'ctx>> Struct<S> {
+    /// Create a constant struct value.
+    ///
+    /// This function also validates `fields` and panic when there is something wrong.
+    pub fn const_struct<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        fields: &[BasicValueEnum<'ctx>],
+    ) -> Instance<'ctx, Self> {
+        // NOTE: There *could* have been a functor `F<M> = Instance<'ctx, M>` for `S::Fields<F>`
+        // to create a more user-friendly interface, but Rust's type system is not sophisticated enough
+        // and if you try doing that Rust would force you put lifetimes everywhere.
+        let val = ctx.const_struct(fields, false);
+        self.check_value(generator, ctx, val).unwrap()
+    }
+}
+
+impl<'ctx, S: StructKind<'ctx>> Model<'ctx> for Struct<S> {
+    type Value = StructValue<'ctx>;
+    type Type = StructType<'ctx>;
+
+    fn get_type<G: CodeGenerator + ?Sized>(&self, generator: &G, ctx: &'ctx Context) -> Self::Type {
+        self.0.get_struct_type(generator, ctx)
+    }
+
+    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError> {
+        let ty = ty.as_basic_type_enum();
+        let Ok(ty) = StructType::try_from(ty) else {
+            return Err(ModelError(format!("Expecting StructType, but got {ty:?}")));
+        };
+
+        let mut traversal =
+            CheckTypeFieldTraversal { generator, ctx, index: 0, errors: Vec::new(), scrutinee: ty };
+        self.0.traverse_fields(&mut traversal);
+
+        let exp_num_fields = traversal.index;
+        let got_num_fields = u32::try_from(ty.get_field_types().len()).unwrap();
+        if exp_num_fields != got_num_fields {
+            return Err(ModelError(format!(
+                "Expecting StructType with {exp_num_fields} field(s), but got {got_num_fields}"
+            )));
+        }
+
+        if !traversal.errors.is_empty() {
+            return Err(traversal.errors[0].clone()); // TODO: Return other errors as well
+        }
+
+        Ok(())
+    }
+}
+
+impl<'ctx, S: StructKind<'ctx>> Instance<'ctx, Struct<S>> {
+    /// Get a field with [`StructValue::get_field_at_index`].
+    pub fn get_field<G: CodeGenerator + ?Sized, M, GetField>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+        get_field: GetField,
+    ) -> Instance<'ctx, M>
+    where
+        M: Model<'ctx>,
+        GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
+    {
+        let field = get_field(self.model.0.fields());
+        let val = self.value.get_field_at_index(field.gep_index as u32).unwrap();
+        field.model.check_value(generator, ctx, val).unwrap()
+    }
+}
+
+impl<'ctx, S: StructKind<'ctx>> Instance<'ctx, Ptr<Struct<S>>> {
+    /// Get a pointer to a field with [`Builder::build_in_bounds_gep`].
+    pub fn gep<M, GetField>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        get_field: GetField,
+    ) -> Instance<'ctx, Ptr<M>>
+    where
+        M: Model<'ctx>,
+        GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
+    {
+        let field = get_field(self.model.0 .0.fields());
+        let llvm_i32 = ctx.ctx.i32_type(); // i64 would segfault
+
+        let ptr = unsafe {
+            ctx.builder
+                .build_in_bounds_gep(
+                    self.value,
+                    &[llvm_i32.const_zero(), llvm_i32.const_int(field.gep_index, false)],
+                    field.name,
+                )
+                .unwrap()
+        };
+
+        Ptr(field.model).believe_value(ptr)
+    }
+
+    /// Convenience function equivalent to `.gep(...).load(...)`.
+    pub fn get<M, GetField, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        get_field: GetField,
+    ) -> Instance<'ctx, M>
+    where
+        M: Model<'ctx>,
+        GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
+    {
+        self.gep(ctx, get_field).load(generator, ctx)
+    }
+
+    /// Convenience function equivalent to `.gep(...).store(...)`.
+    pub fn set<M, GetField>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        get_field: GetField,
+        value: Instance<'ctx, M>,
+    ) where
+        M: Model<'ctx>,
+        GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
+    {
+        self.gep(ctx, get_field).store(ctx, value);
+    }
+}
--- a/nac3core/src/codegen/model/util.rs
+++ b/nac3core/src/codegen/model/util.rs
@ -0,0 +1,40 @@
+use crate::codegen::{
+    stmt::{gen_for_callback_incrementing, BreakContinueHooks},
+    CodeGenContext, CodeGenerator,
+};
+
+use super::*;
+
+/// Like [`gen_for_callback_incrementing`] with [`Model`] abstractions.
+pub fn gen_for_model<'ctx, 'a, G, F, N>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, 'a>,
+    start: Instance<'ctx, Int<N>>,
+    stop: Instance<'ctx, Int<N>>,
+    step: Instance<'ctx, Int<N>>,
+    body: F,
+) -> Result<(), String>
+where
+    G: CodeGenerator + ?Sized,
+    F: FnOnce(
+        &mut G,
+        &mut CodeGenContext<'ctx, 'a>,
+        BreakContinueHooks<'ctx>,
+        Instance<'ctx, Int<N>>,
+    ) -> Result<(), String>,
+    N: IntKind<'ctx> + Default,
+{
+    let int_model = Int(N::default());
+    gen_for_callback_incrementing(
+        generator,
+        ctx,
+        None,
+        start.value,
+        (stop.value, false),
+        |g, ctx, hooks, i| {
+            let i = int_model.believe_value(i);
+            body(g, ctx, hooks, i)
+        },
+        step.value,
+    )
+}
--- a/nac3core/src/codegen/numpy.rs
+++ b/nac3core/src/codegen/numpy.rs
--- a/nac3core/src/codegen/object/any.rs
+++ b/nac3core/src/codegen/object/any.rs
@ -0,0 +1,12 @@
+use inkwell::values::BasicValueEnum;
+
+use crate::typecheck::typedef::Type;
+
+/// An NAC3 LLVM Python object.
+#[derive(Debug, Clone, Copy)]
+pub struct AnyObject<'ctx> {
+    /// Typechecker type of the object.
+    pub ty: Type,
+    /// LLVM value of the object.
+    pub value: BasicValueEnum<'ctx>,
+}
--- a/nac3core/src/codegen/object/list.rs
+++ b/nac3core/src/codegen/object/list.rs
@ -0,0 +1,150 @@
+use inkwell::types::BasicType;
+
+use crate::{
+    codegen::{model::*, CodeGenContext, CodeGenerator},
+    typecheck::typedef::{iter_type_vars, Type, TypeEnum},
+};
+
+use super::any::AnyObject;
+
+/// Fields of [`List`]
+pub struct ListFields<'ctx, F: FieldTraversal<'ctx>, Item: Model<'ctx>> {
+    /// Array pointer to content
+    pub items: F::Out<Ptr<Item>>,
+    /// Number of items in the array
+    pub len: F::Out<Int<SizeT>>,
+}
+
+/// A list in NAC3.
+#[derive(Debug, Clone, Copy, Default)]
+pub struct List<Item> {
+    /// Model of the list items
+    pub item: Item,
+}
+
+impl<'ctx, Item: Model<'ctx>> StructKind<'ctx> for List<Item> {
+    type Fields<F: FieldTraversal<'ctx>> = ListFields<'ctx, F, Item>;
+
+    fn traverse_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            items: traversal.add("items", Ptr(self.item)),
+            len: traversal.add_auto("len"),
+        }
+    }
+}
+
+/// A NAC3 Python List object.
+#[derive(Debug, Clone, Copy)]
+pub struct ListObject<'ctx> {
+    /// Typechecker type of the list items. Could be [`TypeEnum::TVar`] if unresolved (like
+    /// in the case of empty lists and the typechecker does not have enough hints).
+    pub item_type: Type,
+    pub instance: Instance<'ctx, Ptr<Struct<List<Any<'ctx>>>>>,
+}
+
+impl<'ctx> ListObject<'ctx> {
+    /// Create a [`ListObject`] from an LLVM value and its typechecker [`Type`].
+    pub fn from_object<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        object: AnyObject<'ctx>,
+    ) -> Self {
+        assert!(matches!(
+            &*ctx.unifier.get_ty(object.ty),
+            TypeEnum::TObj { obj_id, .. } if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap()
+        ));
+
+        // Check typechecker type and extract `item_type`
+        let item_type = match &*ctx.unifier.get_ty(object.ty) {
+            TypeEnum::TObj { obj_id, params, .. }
+                if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
+            {
+                iter_type_vars(params).next().unwrap().ty // Extract `item_type`
+            }
+            _ => {
+                panic!("Expecting type to be a list, but got {}", ctx.unifier.stringify(object.ty))
+            }
+        };
+
+        // If `item_type` is unresolved, the list's ptr will default to `size_t*`
+        // as a placeholder because there are no opaque pointers in LLVM 14.
+        let item_type_llvm = if let TypeEnum::TVar { .. } = &*ctx.unifier.get_ty(item_type) {
+            generator.get_size_type(ctx.ctx).as_basic_type_enum()
+        } else {
+            ctx.get_llvm_type(generator, item_type)
+        };
+
+        let plist = Ptr(Struct(List { item: Any(item_type_llvm) }));
+
+        // Create object
+        let value = plist.check_value(generator, ctx.ctx, object.value).unwrap();
+        ListObject { item_type, instance: value }
+    }
+
+    /// Get the `len()` of this list.
+    pub fn len<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<SizeT>> {
+        self.instance.get(generator, ctx, |f| f.len)
+    }
+
+    /// Get the `items` field as an opaque pointer.
+    pub fn get_opaque_items_ptr<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Ptr<Int<Byte>>> {
+        self.instance.get(generator, ctx, |f| f.items).pointer_cast(generator, ctx, Int(Byte))
+    }
+
+    /// Get the value of this [`ListObject`] as a list with opaque items.
+    ///
+    /// This function allocates on the stack to create the list, but the
+    /// reference to the `items` is preserved.
+    pub fn get_opaque_list_ptr<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Ptr<Struct<List<Int<Byte>>>>> {
+        let opaque_list = Struct(List { item: Int(Byte) }).alloca(generator, ctx);
+
+        // Copy items pointer
+        let items = self.get_opaque_items_ptr(generator, ctx);
+        opaque_list.set(ctx, |f| f.items, items);
+
+        // Copy len
+        let len = self.instance.get(generator, ctx, |f| f.len);
+        opaque_list.set(ctx, |f| f.len, len);
+
+        opaque_list
+    }
+
+    /// Allocate a list on the stack given its `item_type` and `len`.
+    ///
+    /// The returned list's content will be:
+    /// - `items`: allocated with an array of length `len` with uninitialized values.
+    /// - `len`: set to `len`.
+    pub fn alloca<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        item_type: Type,
+        len: Instance<'ctx, Int<SizeT>>,
+    ) -> Self {
+        // If `item_type` is unresolved, the list's ptr will default to `size_t*`
+        // as a placeholder because there are no opaque pointers in LLVM 14.
+        let item_type_llvm = if let TypeEnum::TVar { .. } = &*ctx.unifier.get_ty(item_type) {
+            generator.get_size_type(ctx.ctx).as_basic_type_enum()
+        } else {
+            ctx.get_llvm_type(generator, item_type)
+        };
+        let items = Any(item_type_llvm).array_alloca(generator, ctx, len.value);
+
+        let instance = Struct(List { item: Any(item_type_llvm) }).alloca(generator, ctx);
+        instance.set(ctx, |f| f.items, items);
+        instance.set(ctx, |f| f.len, len);
+
+        ListObject { item_type, instance }
+    }
+}
--- a/nac3core/src/codegen/object/mod.rs
+++ b/nac3core/src/codegen/object/mod.rs
@ -0,0 +1,5 @@
+pub mod any;
+pub mod list;
+pub mod ndarray;
+pub mod range;
+pub mod tuple;
--- a/nac3core/src/codegen/object/ndarray/array.rs
+++ b/nac3core/src/codegen/object/ndarray/array.rs
@ -0,0 +1,178 @@
+use super::NDArrayObject;
+use crate::{
+    codegen::{
+        irrt::{
+            call_nac3_ndarray_array_set_and_validate_list_shape,
+            call_nac3_ndarray_array_write_list_to_array,
+        },
+        model::*,
+        object::{any::AnyObject, list::ListObject},
+        stmt::gen_if_else_expr_callback,
+        CodeGenContext, CodeGenerator,
+    },
+    toplevel::helper::{arraylike_flatten_element_type, arraylike_get_ndims},
+    typecheck::typedef::{Type, TypeEnum},
+};
+
+fn get_list_object_dtype_and_ndims<'ctx>(
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    list: ListObject<'ctx>,
+) -> (Type, u64) {
+    let dtype = arraylike_flatten_element_type(&mut ctx.unifier, list.item_type);
+
+    let ndims = arraylike_get_ndims(&mut ctx.unifier, list.item_type);
+    let ndims = ndims + 1; // To count `list` itself.
+
+    (dtype, ndims)
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    fn make_np_array_list_copy_impl<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        list: ListObject<'ctx>,
+    ) -> Self {
+        let (dtype, ndims_int) = get_list_object_dtype_and_ndims(ctx, list);
+        let list_value = list.get_opaque_list_ptr(generator, ctx);
+
+        // Validate `list` has a consistent shape.
+        // Raise an exception if `list` is something abnormal like `[[1, 2], [3]]`.
+        // If `list` has a consistent shape, deduce the shape and write it to `shape`.
+        let ndims = Int(SizeT).const_int(generator, ctx.ctx, ndims_int);
+        let shape = Int(SizeT).array_alloca(generator, ctx, ndims.value);
+        call_nac3_ndarray_array_set_and_validate_list_shape(
+            generator, ctx, list_value, ndims, shape,
+        );
+
+        let ndarray = NDArrayObject::alloca(generator, ctx, dtype, ndims_int);
+        ndarray.copy_shape_from_array(generator, ctx, shape);
+        ndarray.create_data(generator, ctx);
+
+        // Copy all contents from the list.
+        call_nac3_ndarray_array_write_list_to_array(generator, ctx, list_value, ndarray.instance);
+
+        ndarray
+    }
+
+    fn make_np_array_list_try_no_copy_impl<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        list: ListObject<'ctx>,
+    ) -> Self {
+        // np_array without copying is only possible `list` is not nested.
+        //
+        // If `list` is `list[T]`, we can create an ndarray with `data` set
+        // to the array pointer of `list`.
+        //
+        // If `list` is `list[list[T]]` or worse, copy.
+
+        let (dtype, ndims) = get_list_object_dtype_and_ndims(ctx, list);
+        if ndims == 1 {
+            // `list` is not nested
+            let ndarray = NDArrayObject::alloca(generator, ctx, dtype, 1);
+
+            // Set data
+            let data = list.get_opaque_items_ptr(generator, ctx);
+            ndarray.instance.set(ctx, |f| f.data, data);
+
+            // ndarray->shape[0] = list->len;
+            let shape = ndarray.instance.get(generator, ctx, |f| f.shape);
+            let list_len = list.instance.get(generator, ctx, |f| f.len);
+            shape.set_index_const(ctx, 0, list_len);
+
+            // Set strides, the `data` is contiguous
+            ndarray.set_strides_contiguous(generator, ctx);
+
+            ndarray
+        } else {
+            // `list` is nested, copy
+            NDArrayObject::make_np_array_list_copy_impl(generator, ctx, list)
+        }
+    }
+
+    fn make_np_array_list_impl<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        list: ListObject<'ctx>,
+        copy: Instance<'ctx, Int<Bool>>,
+    ) -> Self {
+        let (dtype, ndims) = get_list_object_dtype_and_ndims(ctx, list);
+
+        let ndarray = gen_if_else_expr_callback(
+            generator,
+            ctx,
+            |_generator, _ctx| Ok(copy.value),
+            |generator, ctx| {
+                let ndarray = NDArrayObject::make_np_array_list_copy_impl(generator, ctx, list);
+                Ok(Some(ndarray.instance.value))
+            },
+            |generator, ctx| {
+                let ndarray =
+                    NDArrayObject::make_np_array_list_try_no_copy_impl(generator, ctx, list);
+                Ok(Some(ndarray.instance.value))
+            },
+        )
+        .unwrap()
+        .unwrap();
+
+        NDArrayObject::from_value_and_unpacked_types(generator, ctx, ndarray, dtype, ndims)
+    }
+
+    pub fn make_np_array_ndarray_impl<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndarray: NDArrayObject<'ctx>,
+        copy: Instance<'ctx, Int<Bool>>,
+    ) -> Self {
+        let ndarray_val = gen_if_else_expr_callback(
+            generator,
+            ctx,
+            |_generator, _ctx| Ok(copy.value),
+            |generator, ctx| {
+                let ndarray = ndarray.make_copy(generator, ctx); // Force copy
+                Ok(Some(ndarray.instance.value))
+            },
+            |_generator, _ctx| {
+                // No need to copy. Return `ndarray` itself.
+                Ok(Some(ndarray.instance.value))
+            },
+        )
+        .unwrap()
+        .unwrap();
+
+        NDArrayObject::from_value_and_unpacked_types(
+            generator,
+            ctx,
+            ndarray_val,
+            ndarray.dtype,
+            ndarray.ndims,
+        )
+    }
+
+    /// Create a new ndarray like `np.array()`.
+    ///
+    /// NOTE: The `ndmin` argument is not here. You may want to
+    /// do [`NDArrayObject::atleast_nd`] to achieve that.
+    pub fn make_np_array<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        object: AnyObject<'ctx>,
+        copy: Instance<'ctx, Int<Bool>>,
+    ) -> Self {
+        match &*ctx.unifier.get_ty(object.ty) {
+            TypeEnum::TObj { obj_id, .. }
+                if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
+            {
+                let list = ListObject::from_object(generator, ctx, object);
+                NDArrayObject::make_np_array_list_impl(generator, ctx, list, copy)
+            }
+            TypeEnum::TObj { obj_id, .. }
+                if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
+            {
+                let ndarray = NDArrayObject::from_object(generator, ctx, object);
+                NDArrayObject::make_np_array_ndarray_impl(generator, ctx, ndarray, copy)
+            }
+            _ => panic!("Unrecognized object type: {}", ctx.unifier.stringify(object.ty)), // Typechecker ensures this
+        }
+    }
+}
--- a/nac3core/src/codegen/object/ndarray/broadcast.rs
+++ b/nac3core/src/codegen/object/ndarray/broadcast.rs
@ -0,0 +1,135 @@
+use itertools::Itertools;
+
+use crate::codegen::{
+    irrt::{call_nac3_ndarray_broadcast_shapes, call_nac3_ndarray_broadcast_to},
+    model::*,
+    CodeGenContext, CodeGenerator,
+};
+
+use super::NDArrayObject;
+
+/// Fields of [`ShapeEntry`]
+pub struct ShapeEntryFields<'ctx, F: FieldTraversal<'ctx>> {
+    pub ndims: F::Out<Int<SizeT>>,
+    pub shape: F::Out<Ptr<Int<SizeT>>>,
+}
+
+/// An IRRT structure used in broadcasting.
+#[derive(Debug, Clone, Copy, Default)]
+pub struct ShapeEntry;
+
+impl<'ctx> StructKind<'ctx> for ShapeEntry {
+    type Fields<F: FieldTraversal<'ctx>> = ShapeEntryFields<'ctx, F>;
+
+    fn traverse_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+        Self::Fields { ndims: traversal.add_auto("ndims"), shape: traversal.add_auto("shape") }
+    }
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Create a broadcast view on this ndarray with a target shape.
+    ///
+    /// The input shape will be checked to make sure that it contains no negative values.
+    ///
+    /// * `target_ndims` - The ndims type after broadcasting to the given shape.
+    /// The caller has to figure this out for this function.
+    /// * `target_shape` - An array pointer pointing to the target shape.
+    #[must_use]
+    pub fn broadcast_to<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        target_ndims: u64,
+        target_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) -> Self {
+        let broadcast_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, target_ndims);
+        broadcast_ndarray.copy_shape_from_array(generator, ctx, target_shape);
+
+        call_nac3_ndarray_broadcast_to(generator, ctx, self.instance, broadcast_ndarray.instance);
+        broadcast_ndarray
+    }
+}
+/// A result produced by [`broadcast_all_ndarrays`]
+#[derive(Debug, Clone)]
+pub struct BroadcastAllResult<'ctx> {
+    /// The statically known `ndims` of the broadcast result.
+    pub ndims: u64,
+    /// The broadcasting shape.
+    pub shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    /// Broadcasted views on the inputs.
+    ///
+    /// All of them will have `shape` [`BroadcastAllResult::shape`] and
+    /// `ndims` [`BroadcastAllResult::ndims`]. The length of the vector
+    /// is the same as the input.
+    pub ndarrays: Vec<NDArrayObject<'ctx>>,
+}
+
+/// Helper function to call `call_nac3_ndarray_broadcast_shapes`
+fn broadcast_shapes<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    in_shape_entries: &[(Instance<'ctx, Ptr<Int<SizeT>>>, u64)], // (shape, shape's length/ndims)
+    broadcast_ndims: u64,
+    broadcast_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+) {
+    // Prepare input shape entries to be passed to `call_nac3_ndarray_broadcast_shapes`.
+    let num_shape_entries =
+        Int(SizeT).const_int(generator, ctx.ctx, u64::try_from(in_shape_entries.len()).unwrap());
+    let shape_entries = Struct(ShapeEntry).array_alloca(generator, ctx, num_shape_entries.value);
+    for (i, (in_shape, in_ndims)) in in_shape_entries.iter().enumerate() {
+        let pshape_entry = shape_entries.offset_const(ctx, i as u64);
+
+        let in_ndims = Int(SizeT).const_int(generator, ctx.ctx, *in_ndims);
+        pshape_entry.set(ctx, |f| f.ndims, in_ndims);
+
+        pshape_entry.set(ctx, |f| f.shape, *in_shape);
+    }
+
+    let broadcast_ndims = Int(SizeT).const_int(generator, ctx.ctx, broadcast_ndims);
+    call_nac3_ndarray_broadcast_shapes(
+        generator,
+        ctx,
+        num_shape_entries,
+        shape_entries,
+        broadcast_ndims,
+        broadcast_shape,
+    );
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Broadcast all ndarrays according to `np.broadcast()` and return a [`BroadcastAllResult`]
+    /// containing all the information of the result of the broadcast operation.
+    pub fn broadcast<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndarrays: &[Self],
+    ) -> BroadcastAllResult<'ctx> {
+        assert!(!ndarrays.is_empty());
+
+        // Infer the broadcast output ndims.
+        let broadcast_ndims_int = ndarrays.iter().map(|ndarray| ndarray.ndims).max().unwrap();
+
+        let broadcast_ndims = Int(SizeT).const_int(generator, ctx.ctx, broadcast_ndims_int);
+        let broadcast_shape = Int(SizeT).array_alloca(generator, ctx, broadcast_ndims.value);
+
+        let shape_entries = ndarrays
+            .iter()
+            .map(|ndarray| (ndarray.instance.get(generator, ctx, |f| f.shape), ndarray.ndims))
+            .collect_vec();
+        broadcast_shapes(generator, ctx, &shape_entries, broadcast_ndims_int, broadcast_shape);
+
+        // Broadcast all the inputs to shape `dst_shape`.
+        let broadcast_ndarrays: Vec<_> = ndarrays
+            .iter()
+            .map(|ndarray| {
+                ndarray.broadcast_to(generator, ctx, broadcast_ndims_int, broadcast_shape)
+            })
+            .collect_vec();
+
+        BroadcastAllResult {
+            ndims: broadcast_ndims_int,
+            shape: broadcast_shape,
+            ndarrays: broadcast_ndarrays,
+        }
+    }
+}
--- a/nac3core/src/codegen/object/ndarray/contiguous.rs
+++ b/nac3core/src/codegen/object/ndarray/contiguous.rs
@ -0,0 +1,134 @@
+use crate::{
+    codegen::{model::*, CodeGenContext, CodeGenerator},
+    typecheck::typedef::Type,
+};
+
+use super::NDArrayObject;
+
+/// Fields of [`ContiguousNDArray`]
+pub struct ContiguousNDArrayFields<'ctx, F: FieldTraversal<'ctx>, Item: Model<'ctx>> {
+    pub ndims: F::Out<Int<SizeT>>,
+    pub shape: F::Out<Ptr<Int<SizeT>>>,
+    pub data: F::Out<Ptr<Item>>,
+}
+
+/// An ndarray without strides and non-opaque `data` field in NAC3.
+#[derive(Debug, Clone, Copy)]
+pub struct ContiguousNDArray<M> {
+    /// [`Model`] of the items.
+    pub item: M,
+}
+
+impl<'ctx, Item: Model<'ctx>> StructKind<'ctx> for ContiguousNDArray<Item> {
+    type Fields<F: FieldTraversal<'ctx>> = ContiguousNDArrayFields<'ctx, F, Item>;
+
+    fn traverse_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            ndims: traversal.add_auto("ndims"),
+            shape: traversal.add_auto("shape"),
+            data: traversal.add("data", Ptr(self.item)),
+        }
+    }
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Create a [`ContiguousNDArray`] from the contents of this ndarray.
+    ///
+    /// This function may or may not be expensive depending on if this ndarray has contiguous data.
+    ///
+    /// If this ndarray is not C-contiguous, this function will allocate memory on the stack for the `data` field of
+    /// the returned [`ContiguousNDArray`] and copy contents of this ndarray to there.
+    ///
+    /// If this ndarray is C-contiguous, contents of this ndarray will not be copied. The created [`ContiguousNDArray`]
+    /// will share memory with this ndarray.
+    ///
+    /// The `item_model` sets the [`Model`] of the returned [`ContiguousNDArray`]'s `Item` model for type-safety, and
+    /// should match the `ctx.get_llvm_type()` of this ndarray's `dtype`. Otherwise this function panics. Use model [`Any`]
+    /// if you don't care/cannot know the [`Model`] in advance.
+    pub fn make_contiguous_ndarray<G: CodeGenerator + ?Sized, Item: Model<'ctx>>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        item_model: Item,
+    ) -> Instance<'ctx, Ptr<Struct<ContiguousNDArray<Item>>>> {
+        // Sanity check on `self.dtype` and `item_model`.
+        let dtype_llvm = ctx.get_llvm_type(generator, self.dtype);
+        item_model.check_type(generator, ctx.ctx, dtype_llvm).unwrap();
+
+        let cdarray_model = Struct(ContiguousNDArray { item: item_model });
+
+        let current_bb = ctx.builder.get_insert_block().unwrap();
+        let then_bb = ctx.ctx.insert_basic_block_after(current_bb, "then_bb");
+        let else_bb = ctx.ctx.insert_basic_block_after(then_bb, "else_bb");
+        let end_bb = ctx.ctx.insert_basic_block_after(else_bb, "end_bb");
+
+        // Allocate and setup the resulting [`ContiguousNDArray`].
+        let result = cdarray_model.alloca(generator, ctx);
+
+        // Set ndims and shape.
+        let ndims = self.ndims_llvm(generator, ctx.ctx);
+        result.set(ctx, |f| f.ndims, ndims);
+
+        let shape = self.instance.get(generator, ctx, |f| f.shape);
+        result.set(ctx, |f| f.shape, shape);
+
+        let is_contiguous = self.is_c_contiguous(generator, ctx);
+        ctx.builder.build_conditional_branch(is_contiguous.value, then_bb, else_bb).unwrap();
+
+        // Inserting into then_bb; This ndarray is contiguous.
+        ctx.builder.position_at_end(then_bb);
+        let data = self.instance.get(generator, ctx, |f| f.data);
+        let data = data.pointer_cast(generator, ctx, item_model);
+        result.set(ctx, |f| f.data, data);
+        ctx.builder.build_unconditional_branch(end_bb).unwrap();
+
+        // Inserting into else_bb; This ndarray is not contiguous. Do a full-copy on `data`.
+        // `make_copy` produces an ndarray with contiguous `data`.
+        ctx.builder.position_at_end(else_bb);
+        let copied_ndarray = self.make_copy(generator, ctx);
+        let data = copied_ndarray.instance.get(generator, ctx, |f| f.data);
+        let data = data.pointer_cast(generator, ctx, item_model);
+        result.set(ctx, |f| f.data, data);
+        ctx.builder.build_unconditional_branch(end_bb).unwrap();
+
+        // Reposition to end_bb for continuation
+        ctx.builder.position_at_end(end_bb);
+
+        result
+    }
+
+    /// Create an [`NDArrayObject`] from a [`ContiguousNDArray`].
+    ///
+    /// The operation is super cheap. The newly created [`NDArrayObject`] will share the
+    /// same memory as the [`ContiguousNDArray`].
+    ///
+    /// `ndims` has to be provided as [`NDArrayObject`] requires a statically known `ndims` value, despite
+    /// the fact that the information should be contained within the [`ContiguousNDArray`].
+    pub fn from_contiguous_ndarray<G: CodeGenerator + ?Sized, Item: Model<'ctx>>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        carray: Instance<'ctx, Ptr<Struct<ContiguousNDArray<Item>>>>,
+        dtype: Type,
+        ndims: u64,
+    ) -> Self {
+        // Sanity check on `dtype` and `contiguous_array`'s `Item` model.
+        let dtype_llvm = ctx.get_llvm_type(generator, dtype);
+        carray.model.0 .0.item.check_type(generator, ctx.ctx, dtype_llvm).unwrap();
+
+        // TODO: Debug assert `ndims == carray.ndims` to catch bugs.
+
+        // Allocate the resulting ndarray.
+        let ndarray = NDArrayObject::alloca(generator, ctx, dtype, ndims);
+
+        // Copy shape and update strides
+        let shape = carray.get(generator, ctx, |f| f.shape);
+        ndarray.copy_shape_from_array(generator, ctx, shape);
+        ndarray.set_strides_contiguous(generator, ctx);
+
+        // Share data
+        let data = carray.get(generator, ctx, |f| f.data).pointer_cast(generator, ctx, Int(Byte));
+        ndarray.instance.set(ctx, |f| f.data, data);
+
+        ndarray
+    }
+}
--- a/nac3core/src/codegen/object/ndarray/factory.rs
+++ b/nac3core/src/codegen/object/ndarray/factory.rs
@ -0,0 +1,176 @@
+use inkwell::{values::BasicValueEnum, IntPredicate};
+
+use crate::{
+    codegen::{
+        irrt::call_nac3_ndarray_util_assert_shape_no_negative, model::*, CodeGenContext,
+        CodeGenerator,
+    },
+    typecheck::typedef::Type,
+};
+
+use super::NDArrayObject;
+
+/// Get the zero value in `np.zeros()` of a `dtype`.
+fn ndarray_zero_value<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    dtype: Type,
+) -> BasicValueEnum<'ctx> {
+    if [ctx.primitives.int32, ctx.primitives.uint32]
+        .iter()
+        .any(|ty| ctx.unifier.unioned(dtype, *ty))
+    {
+        ctx.ctx.i32_type().const_zero().into()
+    } else if [ctx.primitives.int64, ctx.primitives.uint64]
+        .iter()
+        .any(|ty| ctx.unifier.unioned(dtype, *ty))
+    {
+        ctx.ctx.i64_type().const_zero().into()
+    } else if ctx.unifier.unioned(dtype, ctx.primitives.float) {
+        ctx.ctx.f64_type().const_zero().into()
+    } else if ctx.unifier.unioned(dtype, ctx.primitives.bool) {
+        ctx.ctx.bool_type().const_zero().into()
+    } else if ctx.unifier.unioned(dtype, ctx.primitives.str) {
+        ctx.gen_string(generator, "").into()
+    } else {
+        panic!("unrecognized dtype: {}", ctx.unifier.stringify(dtype));
+    }
+}
+
+/// Get the one value in `np.ones()` of a `dtype`.
+fn ndarray_one_value<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    dtype: Type,
+) -> BasicValueEnum<'ctx> {
+    if [ctx.primitives.int32, ctx.primitives.uint32]
+        .iter()
+        .any(|ty| ctx.unifier.unioned(dtype, *ty))
+    {
+        let is_signed = ctx.unifier.unioned(dtype, ctx.primitives.int32);
+        ctx.ctx.i32_type().const_int(1, is_signed).into()
+    } else if [ctx.primitives.int64, ctx.primitives.uint64]
+        .iter()
+        .any(|ty| ctx.unifier.unioned(dtype, *ty))
+    {
+        let is_signed = ctx.unifier.unioned(dtype, ctx.primitives.int64);
+        ctx.ctx.i64_type().const_int(1, is_signed).into()
+    } else if ctx.unifier.unioned(dtype, ctx.primitives.float) {
+        ctx.ctx.f64_type().const_float(1.0).into()
+    } else if ctx.unifier.unioned(dtype, ctx.primitives.bool) {
+        ctx.ctx.bool_type().const_int(1, false).into()
+    } else if ctx.unifier.unioned(dtype, ctx.primitives.str) {
+        ctx.gen_string(generator, "1").into()
+    } else {
+        panic!("unrecognized dtype: {}", ctx.unifier.stringify(dtype));
+    }
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Create an ndarray like `np.empty`.
+    pub fn make_np_empty<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        ndims: u64,
+        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) -> Self {
+        // Validate `shape`
+        let ndims_llvm = Int(SizeT).const_int(generator, ctx.ctx, ndims);
+        call_nac3_ndarray_util_assert_shape_no_negative(generator, ctx, ndims_llvm, shape);
+
+        let ndarray = NDArrayObject::alloca(generator, ctx, dtype, ndims);
+        ndarray.copy_shape_from_array(generator, ctx, shape);
+        ndarray.create_data(generator, ctx);
+
+        ndarray
+    }
+
+    /// Create an ndarray like `np.full`.
+    pub fn make_np_full<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        ndims: u64,
+        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+        fill_value: BasicValueEnum<'ctx>,
+    ) -> Self {
+        let ndarray = NDArrayObject::make_np_empty(generator, ctx, dtype, ndims, shape);
+        ndarray.fill(generator, ctx, fill_value);
+        ndarray
+    }
+
+    /// Create an ndarray like `np.zero`.
+    pub fn make_np_zeros<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        ndims: u64,
+        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) -> Self {
+        let fill_value = ndarray_zero_value(generator, ctx, dtype);
+        NDArrayObject::make_np_full(generator, ctx, dtype, ndims, shape, fill_value)
+    }
+
+    /// Create an ndarray like `np.ones`.
+    pub fn make_np_ones<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        ndims: u64,
+        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) -> Self {
+        let fill_value = ndarray_one_value(generator, ctx, dtype);
+        NDArrayObject::make_np_full(generator, ctx, dtype, ndims, shape, fill_value)
+    }
+
+    /// Create an ndarray like `np.eye`.
+    pub fn make_np_eye<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        nrows: Instance<'ctx, Int<SizeT>>,
+        ncols: Instance<'ctx, Int<SizeT>>,
+        offset: Instance<'ctx, Int<SizeT>>,
+    ) -> Self {
+        let ndzero = ndarray_zero_value(generator, ctx, dtype);
+        let ndone = ndarray_one_value(generator, ctx, dtype);
+
+        let ndarray = NDArrayObject::alloca_dynamic_shape(generator, ctx, dtype, &[nrows, ncols]);
+
+        // Create data and make the matrix like look np.eye()
+        ndarray.create_data(generator, ctx);
+        ndarray
+            .foreach(generator, ctx, |generator, ctx, _hooks, nditer| {
+                // NOTE: rows and cols can never be zero here, since this ndarray's `np.size` would be zero
+                // and this loop would not execute.
+
+                // Load up `row_i` and `col_i` from indices.
+                let row_i = nditer.get_indices().get_index_const(generator, ctx, 0);
+                let col_i = nditer.get_indices().get_index_const(generator, ctx, 1);
+
+                let be_one = row_i.add(ctx, offset).compare(ctx, IntPredicate::EQ, col_i);
+                let value = ctx.builder.build_select(be_one.value, ndone, ndzero, "value").unwrap();
+
+                let p = nditer.get_pointer(generator, ctx);
+                ctx.builder.build_store(p, value).unwrap();
+
+                Ok(())
+            })
+            .unwrap();
+
+        ndarray
+    }
+
+    /// Create an ndarray like `np.identity`.
+    pub fn make_np_identity<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        size: Instance<'ctx, Int<SizeT>>,
+    ) -> Self {
+        // Convenient implementation
+        let offset = Int(SizeT).const_0(generator, ctx.ctx);
+        NDArrayObject::make_np_eye(generator, ctx, dtype, size, size, offset)
+    }
+}
--- a/nac3core/src/codegen/object/ndarray/indexing.rs
+++ b/nac3core/src/codegen/object/ndarray/indexing.rs
@ -0,0 +1,295 @@
+use crate::codegen::{irrt::call_nac3_ndarray_index, model::*, CodeGenContext, CodeGenerator};
+
+use super::NDArrayObject;
+
+pub type NDIndexType = Byte;
+
+/// Fields of [`NDIndex`]
+#[derive(Debug, Clone, Copy)]
+pub struct NDIndexFields<'ctx, F: FieldTraversal<'ctx>> {
+    pub type_: F::Out<Int<NDIndexType>>, // Defined to be uint8_t in IRRT
+    pub data: F::Out<Ptr<Int<Byte>>>,
+}
+
+/// An IRRT representation of an ndarray subscript index.
+#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
+pub struct NDIndex;
+
+impl<'ctx> StructKind<'ctx> for NDIndex {
+    type Fields<F: FieldTraversal<'ctx>> = NDIndexFields<'ctx, F>;
+
+    fn traverse_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+        Self::Fields { type_: traversal.add_auto("type"), data: traversal.add_auto("data") }
+    }
+}
+
+/// Fields of [`Slice`]
+#[derive(Debug, Clone)]
+pub struct SliceFields<'ctx, F: FieldTraversal<'ctx>, N: IntKind<'ctx>> {
+    pub start_defined: F::Out<Int<Bool>>,
+    pub start: F::Out<Int<N>>,
+    pub stop_defined: F::Out<Int<Bool>>,
+    pub stop: F::Out<Int<N>>,
+    pub step_defined: F::Out<Int<Bool>>,
+    pub step: F::Out<Int<N>>,
+}
+
+/// An IRRT representation of an (unresolved) slice.
+#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
+pub struct Slice<N> {
+    int_kind: N,
+}
+
+impl<'ctx, N: IntKind<'ctx>> StructKind<'ctx> for Slice<N> {
+    type Fields<F: FieldTraversal<'ctx>> = SliceFields<'ctx, F, N>;
+
+    fn traverse_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            start_defined: traversal.add_auto("start_defined"),
+            start: traversal.add("start", Int(self.int_kind)),
+            stop_defined: traversal.add_auto("stop_defined"),
+            stop: traversal.add("stop", Int(self.int_kind)),
+            step_defined: traversal.add_auto("step_defined"),
+            step: traversal.add("step", Int(self.int_kind)),
+        }
+    }
+}
+
+/// A convenience structure to prepare a [`Slice`].
+#[derive(Debug, Clone)]
+pub struct RustSlice<'ctx, N: IntKind<'ctx>> {
+    pub start: Option<Instance<'ctx, Int<N>>>,
+    pub stop: Option<Instance<'ctx, Int<N>>>,
+    pub step: Option<Instance<'ctx, Int<N>>>,
+}
+
+impl<'ctx, N: IntKind<'ctx>> RustSlice<'ctx, N> {
+    /// Write the contents to an LLVM [`Slice`].
+    pub fn write_to_slice<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        dst_slice_ptr: Instance<'ctx, Ptr<Struct<Slice<N>>>>,
+    ) {
+        let false_ = Int(Bool).const_false(generator, ctx.ctx);
+        let true_ = Int(Bool).const_true(generator, ctx.ctx);
+
+        match self.start {
+            Some(start) => {
+                dst_slice_ptr.gep(ctx, |f| f.start_defined).store(ctx, true_);
+                dst_slice_ptr.gep(ctx, |f| f.start).store(ctx, start);
+            }
+            None => dst_slice_ptr.gep(ctx, |f| f.start_defined).store(ctx, false_),
+        }
+
+        match self.stop {
+            Some(stop) => {
+                dst_slice_ptr.gep(ctx, |f| f.stop_defined).store(ctx, true_);
+                dst_slice_ptr.gep(ctx, |f| f.stop).store(ctx, stop);
+            }
+            None => dst_slice_ptr.gep(ctx, |f| f.stop_defined).store(ctx, false_),
+        }
+
+        match self.step {
+            Some(step) => {
+                dst_slice_ptr.gep(ctx, |f| f.step_defined).store(ctx, true_);
+                dst_slice_ptr.gep(ctx, |f| f.step).store(ctx, step);
+            }
+            None => dst_slice_ptr.gep(ctx, |f| f.step_defined).store(ctx, false_),
+        }
+    }
+}
+
+// A convenience enum to prepare an [`NDIndex`].
+#[derive(Debug, Clone)]
+pub enum RustNDIndex<'ctx> {
+    SingleElement(Instance<'ctx, Int<Int32>>), // TODO: To be SizeT
+    Slice(RustSlice<'ctx, Int32>),
+    NewAxis,
+    Ellipsis,
+}
+
+impl<'ctx> RustNDIndex<'ctx> {
+    /// Get the value to set `NDIndex::type` for this variant.
+    fn get_type_id(&self) -> u64 {
+        // Defined in IRRT, must be in sync
+        match self {
+            RustNDIndex::SingleElement(_) => 0,
+            RustNDIndex::Slice(_) => 1,
+            RustNDIndex::NewAxis => 2,
+            RustNDIndex::Ellipsis => 3,
+        }
+    }
+
+    /// Write the contents to an LLVM [`NDIndex`].
+    fn write_to_ndindex<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        dst_ndindex_ptr: Instance<'ctx, Ptr<Struct<NDIndex>>>,
+    ) {
+        // Set `dst_ndindex_ptr->type`
+        dst_ndindex_ptr.gep(ctx, |f| f.type_).store(
+            ctx,
+            Int(NDIndexType::default()).const_int(generator, ctx.ctx, self.get_type_id()),
+        );
+
+        // Set `dst_ndindex_ptr->data`
+        match self {
+            RustNDIndex::SingleElement(in_index) => {
+                let index_ptr = Int(Int32).alloca(generator, ctx);
+                index_ptr.store(ctx, *in_index);
+
+                dst_ndindex_ptr
+                    .gep(ctx, |f| f.data)
+                    .store(ctx, index_ptr.pointer_cast(generator, ctx, Int(Byte)));
+            }
+            RustNDIndex::Slice(in_rust_slice) => {
+                let user_slice_ptr = Struct(Slice { int_kind: Int32 }).alloca(generator, ctx);
+                in_rust_slice.write_to_slice(generator, ctx, user_slice_ptr);
+
+                dst_ndindex_ptr
+                    .gep(ctx, |f| f.data)
+                    .store(ctx, user_slice_ptr.pointer_cast(generator, ctx, Int(Byte)));
+            }
+            RustNDIndex::NewAxis | RustNDIndex::Ellipsis => {}
+        }
+    }
+
+    /// Allocate an array of `NDIndex`es on the stack and return its stack pointer.
+    pub fn alloca_ndindices<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+        in_ndindices: &[RustNDIndex<'ctx>],
+    ) -> (Instance<'ctx, Int<SizeT>>, Instance<'ctx, Ptr<Struct<NDIndex>>>) {
+        let ndindex_model = Struct(NDIndex);
+
+        let num_ndindices = Int(SizeT).const_int(generator, ctx.ctx, in_ndindices.len() as u64);
+        let ndindices = ndindex_model.array_alloca(generator, ctx, num_ndindices.value);
+        for (i, in_ndindex) in in_ndindices.iter().enumerate() {
+            let pndindex = ndindices.offset_const(ctx, i as u64);
+            in_ndindex.write_to_ndindex(generator, ctx, pndindex);
+        }
+
+        (num_ndindices, ndindices)
+    }
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Get the ndims [`Type`] after indexing with a given slice.
+    #[must_use]
+    pub fn deduce_ndims_after_indexing_with(&self, indices: &[RustNDIndex<'ctx>]) -> u64 {
+        let mut ndims = self.ndims;
+        for index in indices {
+            match index {
+                RustNDIndex::SingleElement(_) => {
+                    ndims -= 1; // Single elements decrements ndims
+                }
+                RustNDIndex::NewAxis => {
+                    ndims += 1; // `np.newaxis` / `none` adds a new axis
+                }
+                RustNDIndex::Ellipsis | RustNDIndex::Slice(_) => {}
+            }
+        }
+        ndims
+    }
+
+    /// Index into the ndarray, and return a newly-allocated view on this ndarray.
+    ///
+    /// This function behaves like NumPy's ndarray indexing, but if the indices index
+    /// into a single element, an unsized ndarray is returned.
+    #[must_use]
+    pub fn index<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        indices: &[RustNDIndex<'ctx>],
+    ) -> Self {
+        let dst_ndims = self.deduce_ndims_after_indexing_with(indices);
+        let dst_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, dst_ndims);
+
+        let (num_indices, indices) = RustNDIndex::alloca_ndindices(generator, ctx, indices);
+        call_nac3_ndarray_index(
+            generator,
+            ctx,
+            num_indices,
+            indices,
+            self.instance,
+            dst_ndarray.instance,
+        );
+
+        dst_ndarray
+    }
+}
+
+pub mod util {
+    use itertools::Itertools;
+    use nac3parser::ast::{Expr, ExprKind};
+
+    use crate::{
+        codegen::{expr::gen_slice, model::*, CodeGenContext, CodeGenerator},
+        typecheck::typedef::Type,
+    };
+
+    use super::{RustNDIndex, RustSlice};
+
+    /// Generate LLVM code to transform an ndarray subscript expression to
+    /// its list of [`RustNDIndex`]
+    ///
+    /// i.e.,
+    /// ```python
+    /// my_ndarray[::3, 1, :2:]
+    ///            ^^^^^^^^^^^ Then these into a three `RustNDIndex`es
+    /// ```
+    pub fn gen_ndarray_subscript_ndindices<'ctx, G: CodeGenerator>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        subscript: &Expr<Option<Type>>,
+    ) -> Result<Vec<RustNDIndex<'ctx>>, String> {
+        // TODO: Support https://numpy.org/doc/stable/user/basics.indexing.html#dimensional-indexing-tools
+
+        // Annoying notes about `slice`
+        //  - `my_array[5]`
+        //    - slice is a `Constant`
+        //  - `my_array[:5]`
+        //    - slice is a `Slice`
+        //  - `my_array[:]`
+        //    - slice is a `Slice`, but lower upper step would all be `Option::None`
+        //  - `my_array[:, :]`
+        //    - slice is now a `Tuple` of two `Slice`-s
+        //
+        // In summary:
+        //  - when there is a comma "," within [], `slice` will be a `Tuple` of the entries.
+        //  - when there is not comma "," within [] (i.e., just a single entry), `slice` will be that entry itself.
+        //
+        // So we first "flatten" out the slice expression
+        let index_exprs = match &subscript.node {
+            ExprKind::Tuple { elts, .. } => elts.iter().collect_vec(),
+            _ => vec![subscript],
+        };
+
+        // Process all index expressions
+        let mut rust_ndindices: Vec<RustNDIndex> = Vec::with_capacity(index_exprs.len()); // Not using iterators here because `?` is used here.
+        for index_expr in index_exprs {
+            // NOTE: Currently nac3core's slices do not have an object representation,
+            // so the code/implementation looks awkward - we have to do pattern matching on the expression
+            let ndindex = if let ExprKind::Slice { lower, upper, step } = &index_expr.node {
+                // Handle slices
+                let (lower, upper, step) = gen_slice(generator, ctx, lower, upper, step)?;
+                RustNDIndex::Slice(RustSlice { start: lower, stop: upper, step })
+            } else {
+                // Treat and handle everything else as a single element index.
+                let index = generator.gen_expr(ctx, index_expr)?.unwrap().to_basic_value_enum(
+                    ctx,
+                    generator,
+                    ctx.primitives.int32, // Must be int32, this checks for illegal values
+                )?;
+                let index = Int(Int32).check_value(generator, ctx.ctx, index).unwrap();
+
+                RustNDIndex::SingleElement(index)
+            };
+            rust_ndindices.push(ndindex);
+        }
+        Ok(rust_ndindices)
+    }
+}
--- a/nac3core/src/codegen/object/ndarray/map.rs
+++ b/nac3core/src/codegen/object/ndarray/map.rs
@ -0,0 +1,220 @@
+use inkwell::values::BasicValueEnum;
+use itertools::Itertools;
+
+use crate::{
+    codegen::{
+        object::ndarray::{AnyObject, NDArrayObject},
+        stmt::gen_for_callback,
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::Type,
+};
+
+use super::{nditer::NDIterHandle, NDArrayOut, ScalarOrNDArray};
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Generate LLVM IR to broadcast `ndarray`s together, and starmap through them with `mapping` elementwise.
+    ///
+    /// `mapping` is an LLVM IR generator. The input of `mapping` is the list of elements when iterating through
+    /// the input `ndarrays` after broadcasting. The output of `mapping` is the result of the elementwise operation.
+    ///
+    /// `out` specifies whether the result should be a new ndarray or to be written an existing ndarray.
+    pub fn broadcast_starmap<'a, G, MappingFn>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        ndarrays: &[Self],
+        out: NDArrayOut<'ctx>,
+        mapping: MappingFn,
+    ) -> Result<Self, String>
+    where
+        G: CodeGenerator + ?Sized,
+        MappingFn: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            &[BasicValueEnum<'ctx>],
+        ) -> Result<BasicValueEnum<'ctx>, String>,
+    {
+        // Broadcast inputs
+        let broadcast_result = NDArrayObject::broadcast(generator, ctx, ndarrays);
+
+        let out_ndarray = match out {
+            NDArrayOut::NewNDArray { dtype } => {
+                // Create a new ndarray based on the broadcast shape.
+                let result_ndarray =
+                    NDArrayObject::alloca(generator, ctx, dtype, broadcast_result.ndims);
+                result_ndarray.copy_shape_from_array(generator, ctx, broadcast_result.shape);
+                result_ndarray.create_data(generator, ctx);
+                result_ndarray
+            }
+            NDArrayOut::WriteToNDArray { ndarray: result_ndarray } => {
+                // Use an existing ndarray.
+
+                // Check that its shape is compatible with the broadcast shape.
+                result_ndarray.assert_can_be_written_by_out(
+                    generator,
+                    ctx,
+                    broadcast_result.ndims,
+                    broadcast_result.shape,
+                );
+                result_ndarray
+            }
+        };
+
+        // Map element-wise and store results into `mapped_ndarray`.
+        let nditer = NDIterHandle::new(generator, ctx, out_ndarray);
+        gen_for_callback(
+            generator,
+            ctx,
+            Some("broadcast_starmap"),
+            |generator, ctx| {
+                // Create NDIters for all broadcasted input ndarrays.
+                let other_nditers = broadcast_result
+                    .ndarrays
+                    .iter()
+                    .map(|ndarray| NDIterHandle::new(generator, ctx, *ndarray))
+                    .collect_vec();
+                Ok((nditer, other_nditers))
+            },
+            |generator, ctx, (out_nditer, _in_nditers)| {
+                // We can simply use `out_nditer`'s `has_next()`.
+                // `in_nditers`' `has_next()`s should return the same value.
+                Ok(out_nditer.has_next(generator, ctx).value)
+            },
+            |generator, ctx, _hooks, (out_nditer, in_nditers)| {
+                // Get all the scalars from the broadcasted input ndarrays, pass them to `mapping`,
+                // and write to `out_ndarray`.
+
+                let in_scalars = in_nditers
+                    .iter()
+                    .map(|nditer| nditer.get_scalar(generator, ctx).value)
+                    .collect_vec();
+
+                let result = mapping(generator, ctx, &in_scalars)?;
+
+                let p = out_nditer.get_pointer(generator, ctx);
+                ctx.builder.build_store(p, result).unwrap();
+
+                Ok(())
+            },
+            |generator, ctx, (out_nditer, in_nditers)| {
+                // Advance all iterators
+                out_nditer.next(generator, ctx);
+                in_nditers.iter().for_each(|nditer| nditer.next(generator, ctx));
+                Ok(())
+            },
+        )?;
+
+        Ok(out_ndarray)
+    }
+
+    /// Map through this ndarray with an elementwise function.
+    pub fn map<'a, G, Mapping>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        out: NDArrayOut<'ctx>,
+        mapping: Mapping,
+    ) -> Result<Self, String>
+    where
+        G: CodeGenerator + ?Sized,
+        Mapping: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            BasicValueEnum<'ctx>,
+        ) -> Result<BasicValueEnum<'ctx>, String>,
+    {
+        NDArrayObject::broadcast_starmap(
+            generator,
+            ctx,
+            &[*self],
+            out,
+            |generator, ctx, scalars| mapping(generator, ctx, scalars[0]),
+        )
+    }
+}
+
+impl<'ctx> ScalarOrNDArray<'ctx> {
+    /// Starmap through a list of inputs using `mapping`, where an input could be an ndarray, a scalar.
+    ///
+    /// This function is very helpful when implementing NumPy functions that takes on either scalars or ndarrays or a mix of them
+    /// as their inputs and produces either an ndarray with broadcast, or a scalar if all its inputs are all scalars.
+    ///
+    /// For example ,this function can be used to implement `np.add`, which has the following behaviors:
+    /// - `np.add(3, 4) = 7` # (scalar, scalar) -> scalar
+    /// - `np.add(3, np.array([4, 5, 6]))` # (scalar, ndarray) -> ndarray; the first `scalar` is converted into an ndarray and broadcasted.
+    /// - `np.add(np.array([[1], [2], [3]]), np.array([[4, 5, 6]]))` # (ndarray, ndarray) -> ndarray; there is broadcasting.
+    ///
+    /// ## Details:
+    ///
+    /// If `inputs` are all [`ScalarOrNDArray::Scalar`], the output will be a [`ScalarOrNDArray::Scalar`] with type `ret_dtype`.
+    ///
+    /// Otherwise (if there are any [`ScalarOrNDArray::NDArray`] in `inputs`), all inputs will be 'as-ndarray'-ed into ndarrays,
+    /// then all inputs (now all ndarrays) will be passed to [`NDArrayObject::broadcasting_starmap`] and **create** a new ndarray
+    /// with dtype `ret_dtype`.
+    pub fn broadcasting_starmap<'a, G, MappingFn>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        inputs: &[ScalarOrNDArray<'ctx>],
+        ret_dtype: Type,
+        mapping: MappingFn,
+    ) -> Result<ScalarOrNDArray<'ctx>, String>
+    where
+        G: CodeGenerator + ?Sized,
+        MappingFn: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            &[BasicValueEnum<'ctx>],
+        ) -> Result<BasicValueEnum<'ctx>, String>,
+    {
+        // Check if all inputs are Scalars
+        let all_scalars: Option<Vec<_>> = inputs.iter().map(AnyObject::try_from).try_collect().ok();
+
+        if let Some(scalars) = all_scalars {
+            let scalars = scalars.iter().map(|scalar| scalar.value).collect_vec();
+            let value = mapping(generator, ctx, &scalars)?;
+
+            Ok(ScalarOrNDArray::Scalar(AnyObject { ty: ret_dtype, value }))
+        } else {
+            // Promote all input to ndarrays and map through them.
+            let inputs = inputs.iter().map(|input| input.to_ndarray(generator, ctx)).collect_vec();
+            let ndarray = NDArrayObject::broadcast_starmap(
+                generator,
+                ctx,
+                &inputs,
+                NDArrayOut::NewNDArray { dtype: ret_dtype },
+                mapping,
+            )?;
+            Ok(ScalarOrNDArray::NDArray(ndarray))
+        }
+    }
+
+    /// Map through this [`ScalarOrNDArray`] with an elementwise function.
+    ///
+    /// If this is a scalar, `mapping` will directly act on the scalar. This function will return a [`ScalarOrNDArray::Scalar`] of that result.
+    ///
+    /// If this is an ndarray, `mapping` will be applied to the elements of the ndarray. A new ndarray of the results will be created and
+    /// returned as a [`ScalarOrNDArray::NDArray`].
+    pub fn map<'a, G, Mapping>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        ret_dtype: Type,
+        mapping: Mapping,
+    ) -> Result<ScalarOrNDArray<'ctx>, String>
+    where
+        G: CodeGenerator + ?Sized,
+        Mapping: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            BasicValueEnum<'ctx>,
+        ) -> Result<BasicValueEnum<'ctx>, String>,
+    {
+        ScalarOrNDArray::broadcasting_starmap(
+            generator,
+            ctx,
+            &[*self],
+            ret_dtype,
+            |generator, ctx, scalars| mapping(generator, ctx, scalars[0]),
+        )
+    }
+}
--- a/nac3core/src/codegen/object/ndarray/matmul.rs
+++ b/nac3core/src/codegen/object/ndarray/matmul.rs
@ -0,0 +1,207 @@
+use std::cmp::max;
+
+use nac3parser::ast::Operator;
+use util::gen_for_model;
+
+use crate::{
+    codegen::{
+        expr::gen_binop_expr_with_values, irrt::call_nac3_ndarray_matmul_calculate_shapes,
+        model::*, object::ndarray::indexing::RustNDIndex, CodeGenContext, CodeGenerator,
+    },
+    typecheck::{magic_methods::Binop, typedef::Type},
+};
+
+use super::{NDArrayObject, NDArrayOut};
+
+/// Perform `np.einsum("...ij,...jk->...ik", in_a, in_b)`.
+///
+/// `dst_dtype` defines the dtype of the returned ndarray.
+fn matmul_at_least_2d<'ctx, G: CodeGenerator>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    dst_dtype: Type,
+    in_a: NDArrayObject<'ctx>,
+    in_b: NDArrayObject<'ctx>,
+) -> NDArrayObject<'ctx> {
+    assert!(in_a.ndims >= 2);
+    assert!(in_b.ndims >= 2);
+
+    // Deduce ndims of the result of matmul.
+    let ndims_int = max(in_a.ndims, in_b.ndims);
+    let ndims = Int(SizeT).const_int(generator, ctx.ctx, ndims_int);
+
+    let num_0 = Int(SizeT).const_int(generator, ctx.ctx, 0);
+    let num_1 = Int(SizeT).const_int(generator, ctx.ctx, 1);
+
+    // Broadcasts `in_a.shape[:-2]` and `in_b.shape[:-2]` together and allocate the
+    // destination ndarray to store the result of matmul.
+    let (a, b, dst) = {
+        let in_a_ndims = in_a.ndims_llvm(generator, ctx.ctx);
+        let in_a_shape = in_a.instance.get(generator, ctx, |f| f.shape);
+        let in_b_ndims = in_b.ndims_llvm(generator, ctx.ctx);
+        let in_b_shape = in_b.instance.get(generator, ctx, |f| f.shape);
+        let a_shape = Int(SizeT).array_alloca(generator, ctx, ndims.value);
+        let b_shape = Int(SizeT).array_alloca(generator, ctx, ndims.value);
+        let dst_shape = Int(SizeT).array_alloca(generator, ctx, ndims.value);
+
+        // Matmul dimension compatibility is checked here.
+        call_nac3_ndarray_matmul_calculate_shapes(
+            generator, ctx, in_a_ndims, in_a_shape, in_b_ndims, in_b_shape, ndims, a_shape,
+            b_shape, dst_shape,
+        );
+
+        let a = in_a.broadcast_to(generator, ctx, ndims_int, a_shape);
+        let b = in_b.broadcast_to(generator, ctx, ndims_int, b_shape);
+
+        let dst = NDArrayObject::alloca(generator, ctx, dst_dtype, ndims_int);
+        dst.copy_shape_from_array(generator, ctx, dst_shape);
+        dst.create_data(generator, ctx);
+
+        (a, b, dst)
+    };
+
+    let len =
+        a.instance.get(generator, ctx, |f| f.shape).get_index_const(generator, ctx, ndims_int - 1);
+
+    let at_row = ndims_int - 2;
+    let at_col = ndims_int - 1;
+
+    let dst_dtype_llvm = ctx.get_llvm_type(generator, dst_dtype);
+    let dst_zero = dst_dtype_llvm.const_zero();
+
+    dst.foreach(generator, ctx, |generator, ctx, _, hdl| {
+        let pdst_ij = hdl.get_pointer(generator, ctx);
+
+        ctx.builder.build_store(pdst_ij, dst_zero).unwrap();
+
+        let indices = hdl.get_indices();
+        let i = indices.get_index_const(generator, ctx, at_row);
+        let j = indices.get_index_const(generator, ctx, at_col);
+
+        gen_for_model(generator, ctx, num_0, len, num_1, |generator, ctx, _, k| {
+            // `indices` is modified to index into `a` and `b`, and restored.
+            indices.set_index_const(ctx, at_row, i);
+            indices.set_index_const(ctx, at_col, k);
+            let a_ik = a.get_scalar_by_indices(generator, ctx, indices);
+
+            indices.set_index_const(ctx, at_row, k);
+            indices.set_index_const(ctx, at_col, j);
+            let b_kj = b.get_scalar_by_indices(generator, ctx, indices);
+
+            // Restore `indices`.
+            indices.set_index_const(ctx, at_row, i);
+            indices.set_index_const(ctx, at_col, j);
+
+            // x = a_[...]ik * b_[...]kj
+            let x = gen_binop_expr_with_values(
+                generator,
+                ctx,
+                (&Some(a.dtype), a_ik.value),
+                Binop::normal(Operator::Mult),
+                (&Some(b.dtype), b_kj.value),
+                ctx.current_loc,
+            )?
+            .unwrap()
+            .to_basic_value_enum(ctx, generator, dst_dtype)?;
+
+            // dst_[...]ij += x
+            let dst_ij = ctx.builder.build_load(pdst_ij, "").unwrap();
+            let dst_ij = gen_binop_expr_with_values(
+                generator,
+                ctx,
+                (&Some(dst_dtype), dst_ij),
+                Binop::normal(Operator::Add),
+                (&Some(dst_dtype), x),
+                ctx.current_loc,
+            )?
+            .unwrap()
+            .to_basic_value_enum(ctx, generator, dst_dtype)?;
+            ctx.builder.build_store(pdst_ij, dst_ij).unwrap();
+
+            Ok(())
+        })
+    })
+    .unwrap();
+
+    dst
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Perform `np.matmul` according to the rules in
+    /// <https://numpy.org/doc/stable/reference/generated/numpy.matmul.html>.
+    ///
+    /// This function always return an [`NDArrayObject`]. You may want to use [`NDArrayObject::split_unsized`]
+    /// to handle when the output could be a scalar.
+    ///
+    /// `dst_dtype` defines the dtype of the returned ndarray.
+    pub fn matmul<G: CodeGenerator>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        a: Self,
+        b: Self,
+        out: NDArrayOut<'ctx>,
+    ) -> Self {
+        // Sanity check, but type inference should prevent this.
+        assert!(a.ndims > 0 && b.ndims > 0, "np.matmul disallows scalar input");
+
+        /*
+            If both arguments are 2-D they are multiplied like conventional matrices.
+            If either argument is N-D, N > 2, it is treated as a stack of matrices residing in the last two indices and broadcast accordingly.
+            If the first argument is 1-D, it is promoted to a matrix by prepending a 1 to its dimensions. After matrix multiplication the prepended 1 is removed.
+            If the second argument is 1-D, it is promoted to a matrix by appending a 1 to its dimensions. After matrix multiplication the appended 1 is removed.
+        */
+
+        let new_a = if a.ndims == 1 {
+            // Prepend 1 to its dimensions
+            a.index(generator, ctx, &[RustNDIndex::NewAxis, RustNDIndex::Ellipsis])
+        } else {
+            a
+        };
+
+        let new_b = if b.ndims == 1 {
+            // Append 1 to its dimensions
+            b.index(generator, ctx, &[RustNDIndex::Ellipsis, RustNDIndex::NewAxis])
+        } else {
+            b
+        };
+
+        // NOTE: `result` will always be a newly allocated ndarray.
+        // Current implementation cannot do in-place matrix muliplication.
+        let mut result = matmul_at_least_2d(generator, ctx, out.get_dtype(), new_a, new_b);
+
+        // Postprocessing on the result to remove prepended/appended axes.
+        let mut postindices = vec![];
+        let zero = Int(Int32).const_0(generator, ctx.ctx);
+
+        if a.ndims == 1 {
+            // Remove the prepended 1
+            postindices.push(RustNDIndex::SingleElement(zero));
+        }
+
+        if b.ndims == 1 {
+            // Remove the appended 1
+            postindices.push(RustNDIndex::Ellipsis);
+            postindices.push(RustNDIndex::SingleElement(zero));
+        }
+
+        if !postindices.is_empty() {
+            result = result.index(generator, ctx, &postindices);
+        }
+
+        match out {
+            NDArrayOut::NewNDArray { .. } => result,
+            NDArrayOut::WriteToNDArray { ndarray: out_ndarray } => {
+                let result_shape = result.instance.get(generator, ctx, |f| f.shape);
+                out_ndarray.assert_can_be_written_by_out(
+                    generator,
+                    ctx,
+                    result.ndims,
+                    result_shape,
+                );
+
+                out_ndarray.copy_data_from(generator, ctx, result);
+                out_ndarray
+            }
+        }
+    }
+}
--- a/nac3core/src/codegen/object/ndarray/mod.rs
+++ b/nac3core/src/codegen/object/ndarray/mod.rs
@ -0,0 +1,671 @@
+pub mod array;
+pub mod broadcast;
+pub mod contiguous;
+pub mod factory;
+pub mod indexing;
+pub mod map;
+pub mod matmul;
+pub mod nditer;
+pub mod shape_util;
+pub mod view;
+
+use inkwell::{
+    context::Context,
+    types::BasicType,
+    values::{BasicValue, BasicValueEnum, PointerValue},
+    AddressSpace,
+};
+
+use crate::{
+    codegen::{
+        irrt::{
+            call_nac3_ndarray_copy_data, call_nac3_ndarray_get_nth_pelement,
+            call_nac3_ndarray_get_pelement_by_indices, call_nac3_ndarray_is_c_contiguous,
+            call_nac3_ndarray_len, call_nac3_ndarray_nbytes,
+            call_nac3_ndarray_set_strides_by_shape, call_nac3_ndarray_size,
+            call_nac3_ndarray_util_assert_output_shape_same,
+        },
+        model::*,
+        CodeGenContext, CodeGenerator,
+    },
+    toplevel::{
+        helper::{create_ndims, extract_ndims},
+        numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
+    },
+    typecheck::typedef::{Type, TypeEnum},
+};
+
+use super::{any::AnyObject, tuple::TupleObject};
+
+/// Fields of [`NDArray`]
+pub struct NDArrayFields<'ctx, F: FieldTraversal<'ctx>> {
+    pub data: F::Out<Ptr<Int<Byte>>>,
+    pub itemsize: F::Out<Int<SizeT>>,
+    pub ndims: F::Out<Int<SizeT>>,
+    pub shape: F::Out<Ptr<Int<SizeT>>>,
+    pub strides: F::Out<Ptr<Int<SizeT>>>,
+}
+
+/// A strided ndarray in NAC3.
+///
+/// See IRRT implementation for details about its fields.
+#[derive(Debug, Clone, Copy, Default)]
+pub struct NDArray;
+
+impl<'ctx> StructKind<'ctx> for NDArray {
+    type Fields<F: FieldTraversal<'ctx>> = NDArrayFields<'ctx, F>;
+
+    fn traverse_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            data: traversal.add_auto("data"),
+            itemsize: traversal.add_auto("itemsize"),
+            ndims: traversal.add_auto("ndims"),
+            shape: traversal.add_auto("shape"),
+            strides: traversal.add_auto("strides"),
+        }
+    }
+}
+
+/// A NAC3 Python ndarray object.
+#[derive(Debug, Clone, Copy)]
+pub struct NDArrayObject<'ctx> {
+    pub dtype: Type,
+    pub ndims: u64,
+    pub instance: Instance<'ctx, Ptr<Struct<NDArray>>>,
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Attempt to convert an [`AnyObject`] into an [`NDArrayObject`].
+    pub fn from_object<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        object: AnyObject<'ctx>,
+    ) -> NDArrayObject<'ctx> {
+        let (dtype, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, object.ty);
+        let ndims = extract_ndims(&ctx.unifier, ndims);
+        Self::from_value_and_unpacked_types(generator, ctx, object.value, dtype, ndims)
+    }
+
+    /// Like [`NDArrayObject::from_object`] but you directly supply the ndarray's
+    /// `dtype` and `ndims`.
+    pub fn from_value_and_unpacked_types<V: BasicValue<'ctx>, G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        value: V,
+        dtype: Type,
+        ndims: u64,
+    ) -> Self {
+        let value = Ptr(Struct(NDArray)).check_value(generator, ctx.ctx, value).unwrap();
+        NDArrayObject { dtype, ndims, instance: value }
+    }
+
+    /// Get this ndarray's `ndims` as an LLVM constant.
+    pub fn ndims_llvm<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &'ctx Context,
+    ) -> Instance<'ctx, Int<SizeT>> {
+        Int(SizeT).const_int(generator, ctx, self.ndims)
+    }
+
+    /// Get the typechecker ndarray type of this [`NDArrayObject`].
+    pub fn get_type(&self, ctx: &mut CodeGenContext<'ctx, '_>) -> Type {
+        let ndims = create_ndims(&mut ctx.unifier, self.ndims);
+        make_ndarray_ty(&mut ctx.unifier, &ctx.primitives, Some(self.dtype), Some(ndims))
+    }
+
+    /// Forget that this is an ndarray and convert into an [`AnyObject`].
+    pub fn to_any(&self, ctx: &mut CodeGenContext<'ctx, '_>) -> AnyObject<'ctx> {
+        let ty = self.get_type(ctx);
+        AnyObject { value: self.instance.value.as_basic_value_enum(), ty }
+    }
+
+    /// Allocate an ndarray on the stack given its `ndims` and `dtype`.
+    ///
+    /// `shape` and `strides` will be automatically allocated on the stack.
+    //e
+    /// The returned ndarray's content will be:
+    /// - `data`: set to `nullptr`.
+    /// - `itemsize`: set to the `sizeof()` of `dtype`.
+    /// - `ndims`: set to the value of  `ndims`.
+    /// - `shape`: allocated with an array of length `ndims` with uninitialized values.
+    /// - `strides`: allocated with an array of length `ndims` with uninitialized values.
+    pub fn alloca<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        ndims: u64,
+    ) -> Self {
+        let ndarray = Struct(NDArray).alloca(generator, ctx);
+
+        let data = Ptr(Int(Byte)).nullptr(generator, ctx.ctx);
+        ndarray.set(ctx, |f| f.data, data);
+
+        let itemsize = ctx.get_llvm_type(generator, dtype).size_of().unwrap();
+        let itemsize = Int(SizeT).s_extend_or_bit_cast(generator, ctx, itemsize);
+        ndarray.set(ctx, |f| f.itemsize, itemsize);
+
+        let ndims_val = Int(SizeT).const_int(generator, ctx.ctx, ndims);
+        ndarray.set(ctx, |f| f.ndims, ndims_val);
+
+        let shape = Int(SizeT).array_alloca(generator, ctx, ndims_val.value);
+        ndarray.set(ctx, |f| f.shape, shape);
+
+        let strides = Int(SizeT).array_alloca(generator, ctx, ndims_val.value);
+        ndarray.set(ctx, |f| f.strides, strides);
+
+        NDArrayObject { dtype, ndims, instance: ndarray }
+    }
+
+    /// Convenience function. Allocate an [`NDArrayObject`] with a statically known shape.
+    ///
+    /// The returned [`NDArrayObject`]'s `data` and `strides` are uninitialized.
+    pub fn alloca_constant_shape<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        shape: &[u64],
+    ) -> Self {
+        let ndarray = NDArrayObject::alloca(generator, ctx, dtype, shape.len() as u64);
+
+        // Write shape
+        let dst_shape = ndarray.instance.get(generator, ctx, |f| f.shape);
+        for (i, dim) in shape.iter().enumerate() {
+            let dim = Int(SizeT).const_int(generator, ctx.ctx, *dim);
+            dst_shape.offset_const(ctx, i as u64).store(ctx, dim);
+        }
+
+        ndarray
+    }
+
+    /// Convenience function. Allocate an [`NDArrayObject`] with a dynamically known shape.
+    ///
+    /// The returned [`NDArrayObject`]'s `data` and `strides` are uninitialized.
+    pub fn alloca_dynamic_shape<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        shape: &[Instance<'ctx, Int<SizeT>>],
+    ) -> Self {
+        let ndarray = NDArrayObject::alloca(generator, ctx, dtype, shape.len() as u64);
+
+        // Write shape
+        let dst_shape = ndarray.instance.get(generator, ctx, |f| f.shape);
+        for (i, dim) in shape.iter().enumerate() {
+            dst_shape.offset_const(ctx, i as u64).store(ctx, *dim);
+        }
+
+        ndarray
+    }
+
+    /// Initialize an ndarray's `data` by allocating a buffer on the stack.
+    /// The allocated data buffer is considered to be *owned* by the ndarray.
+    ///
+    /// `strides` of the ndarray will also be updated with `set_strides_by_shape`.
+    ///
+    /// `shape` and `itemsize` of the ndarray ***must*** be initialized first.
+    pub fn create_data<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) {
+        let nbytes = self.nbytes(generator, ctx);
+
+        let data = Int(Byte).array_alloca(generator, ctx, nbytes.value);
+        self.instance.set(ctx, |f| f.data, data);
+
+        self.set_strides_contiguous(generator, ctx);
+    }
+
+    /// Copy shape dimensions from an array.
+    pub fn copy_shape_from_array<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) {
+        let num_items = self.ndims_llvm(generator, ctx.ctx).value;
+        self.instance.get(generator, ctx, |f| f.shape).copy_from(generator, ctx, shape, num_items);
+    }
+
+    /// Copy shape dimensions from an ndarray.
+    /// Panics if `ndims` mismatches.
+    pub fn copy_shape_from_ndarray<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        src_ndarray: NDArrayObject<'ctx>,
+    ) {
+        assert_eq!(self.ndims, src_ndarray.ndims);
+        let src_shape = src_ndarray.instance.get(generator, ctx, |f| f.shape);
+        self.copy_shape_from_array(generator, ctx, src_shape);
+    }
+
+    /// Copy strides dimensions from an array.
+    pub fn copy_strides_from_array<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        strides: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) {
+        let num_items = self.ndims_llvm(generator, ctx.ctx).value;
+        self.instance
+            .get(generator, ctx, |f| f.strides)
+            .copy_from(generator, ctx, strides, num_items);
+    }
+
+    /// Copy strides dimensions from an ndarray.
+    /// Panics if `ndims` mismatches.
+    pub fn copy_strides_from_ndarray<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        src_ndarray: NDArrayObject<'ctx>,
+    ) {
+        assert_eq!(self.ndims, src_ndarray.ndims);
+        let src_strides = src_ndarray.instance.get(generator, ctx, |f| f.strides);
+        self.copy_strides_from_array(generator, ctx, src_strides);
+    }
+
+    /// Get the `np.size()` of this ndarray.
+    pub fn size<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<SizeT>> {
+        call_nac3_ndarray_size(generator, ctx, self.instance)
+    }
+
+    /// Get the `ndarray.nbytes` of this ndarray.
+    pub fn nbytes<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<SizeT>> {
+        call_nac3_ndarray_nbytes(generator, ctx, self.instance)
+    }
+
+    /// Get the `len()` of this ndarray.
+    pub fn len<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<SizeT>> {
+        call_nac3_ndarray_len(generator, ctx, self.instance)
+    }
+
+    /// Check if this ndarray is C-contiguous.
+    ///
+    /// See NumPy's `flags["C_CONTIGUOUS"]`: <https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html#numpy.ndarray.flags>
+    pub fn is_c_contiguous<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<Bool>> {
+        call_nac3_ndarray_is_c_contiguous(generator, ctx, self.instance)
+    }
+
+    /// Get the pointer to the n-th (0-based) element.
+    ///
+    /// The returned pointer has the element type of the LLVM type of this ndarray's `dtype`.
+    pub fn get_nth_pelement<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        nth: Instance<'ctx, Int<SizeT>>,
+    ) -> PointerValue<'ctx> {
+        let elem_ty = ctx.get_llvm_type(generator, self.dtype);
+
+        let p = call_nac3_ndarray_get_nth_pelement(generator, ctx, self.instance, nth);
+        ctx.builder
+            .build_pointer_cast(p.value, elem_ty.ptr_type(AddressSpace::default()), "")
+            .unwrap()
+    }
+
+    /// Get the n-th (0-based) scalar.
+    pub fn get_nth_scalar<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        nth: Instance<'ctx, Int<SizeT>>,
+    ) -> AnyObject<'ctx> {
+        let ptr = self.get_nth_pelement(generator, ctx, nth);
+        let value = ctx.builder.build_load(ptr, "").unwrap();
+        AnyObject { ty: self.dtype, value }
+    }
+
+    /// Get the pointer to the element indexed by `indices`.
+    ///
+    /// The returned pointer has the element type of the LLVM type of this ndarray's `dtype`.
+    pub fn get_pelement_by_indices<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        indices: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) -> PointerValue<'ctx> {
+        let elem_ty = ctx.get_llvm_type(generator, self.dtype);
+
+        let p = call_nac3_ndarray_get_pelement_by_indices(generator, ctx, self.instance, indices);
+        ctx.builder
+            .build_pointer_cast(p.value, elem_ty.ptr_type(AddressSpace::default()), "")
+            .unwrap()
+    }
+
+    /// Get the scalar indexed by `indices`.
+    pub fn get_scalar_by_indices<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        indices: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) -> AnyObject<'ctx> {
+        let ptr = self.get_pelement_by_indices(generator, ctx, indices);
+        let value = ctx.builder.build_load(ptr, "").unwrap();
+        AnyObject { ty: self.dtype, value }
+    }
+
+    /// Call [`call_nac3_ndarray_set_strides_by_shape`] on this ndarray to update `strides`.
+    ///
+    /// Update the ndarray's strides to make the ndarray contiguous.
+    pub fn set_strides_contiguous<G: CodeGenerator + ?Sized>(
+        self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) {
+        call_nac3_ndarray_set_strides_by_shape(generator, ctx, self.instance);
+    }
+
+    /// Clone/Copy this ndarray - Allocate a new ndarray with the same shape as this ndarray and copy the contents over.
+    ///
+    /// The new ndarray will own its data and will be C-contiguous.
+    #[must_use]
+    pub fn make_copy<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Self {
+        let clone = NDArrayObject::alloca(generator, ctx, self.dtype, self.ndims);
+
+        let shape = self.instance.gep(ctx, |f| f.shape).load(generator, ctx);
+        clone.copy_shape_from_array(generator, ctx, shape);
+        clone.create_data(generator, ctx);
+        clone.copy_data_from(generator, ctx, *self);
+        clone
+    }
+
+    /// Copy data from another ndarray.
+    ///
+    /// This ndarray and `src` is that their `np.size()` should be the same. Their shapes
+    /// do not matter. The copying order is determined by how their flattened views look.
+    ///
+    /// Panics if the `dtype`s of ndarrays are different.
+    pub fn copy_data_from<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        src: NDArrayObject<'ctx>,
+    ) {
+        assert!(ctx.unifier.unioned(self.dtype, src.dtype), "self and src dtype should match");
+        call_nac3_ndarray_copy_data(generator, ctx, src.instance, self.instance);
+    }
+
+    /// Returns true if this ndarray is unsized - `ndims == 0` and only contains a scalar.
+    #[must_use]
+    pub fn is_unsized(&self) -> bool {
+        self.ndims == 0
+    }
+
+    /// If this ndarray is unsized, return its sole value as an [`AnyObject`].
+    /// Otherwise, do nothing and return the ndarray itself.
+    pub fn split_unsized<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> ScalarOrNDArray<'ctx> {
+        if self.is_unsized() {
+            // NOTE: `np.size(self) == 0` here is never possible.
+            let zero = Int(SizeT).const_0(generator, ctx.ctx);
+            let value = self.get_nth_scalar(generator, ctx, zero).value;
+
+            ScalarOrNDArray::Scalar(AnyObject { ty: self.dtype, value })
+        } else {
+            ScalarOrNDArray::NDArray(*self)
+        }
+    }
+
+    /// Fill the ndarray with a scalar.
+    ///
+    /// `fill_value` must have the same LLVM type as the `dtype` of this ndarray.
+    pub fn fill<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        value: BasicValueEnum<'ctx>,
+    ) {
+        self.foreach(generator, ctx, |generator, ctx, _hooks, nditer| {
+            let p = nditer.get_pointer(generator, ctx);
+            ctx.builder.build_store(p, value).unwrap();
+            Ok(())
+        })
+        .unwrap();
+    }
+
+    /// Create the shape tuple of this ndarray like `np.shape(<ndarray>)`.
+    ///
+    /// The returned integers in the tuple are in int32.
+    pub fn make_shape_tuple<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> TupleObject<'ctx> {
+        // TODO: Return a tuple of SizeT
+
+        let mut objects = Vec::with_capacity(self.ndims as usize);
+
+        for i in 0..self.ndims {
+            let dim = self
+                .instance
+                .get(generator, ctx, |f| f.shape)
+                .get_index_const(generator, ctx, i)
+                .truncate(generator, ctx, Int32);
+
+            objects.push(AnyObject {
+                ty: ctx.primitives.int32,
+                value: dim.value.as_basic_value_enum(),
+            });
+        }
+
+        TupleObject::from_objects(generator, ctx, objects)
+    }
+
+    /// Create the strides tuple of this ndarray like `np.strides(<ndarray>)`.
+    ///
+    /// The returned integers in the tuple are in int32.
+    pub fn make_strides_tuple<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> TupleObject<'ctx> {
+        // TODO: Return a tuple of SizeT.
+
+        let mut objects = Vec::with_capacity(self.ndims as usize);
+
+        for i in 0..self.ndims {
+            let dim = self
+                .instance
+                .get(generator, ctx, |f| f.strides)
+                .get_index_const(generator, ctx, i)
+                .truncate(generator, ctx, Int32);
+
+            objects.push(AnyObject {
+                ty: ctx.primitives.int32,
+                value: dim.value.as_basic_value_enum(),
+            });
+        }
+
+        TupleObject::from_objects(generator, ctx, objects)
+    }
+
+    /// Create an unsized ndarray to contain `object`.
+    pub fn make_unsized<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        object: AnyObject<'ctx>,
+    ) -> NDArrayObject<'ctx> {
+        // We have to put the value on the stack to get a data pointer.
+        let data = ctx.builder.build_alloca(object.value.get_type(), "make_unsized").unwrap();
+        ctx.builder.build_store(data, object.value).unwrap();
+        let data = Ptr(Int(Byte)).pointer_cast(generator, ctx, data);
+
+        let ndarray = NDArrayObject::alloca(generator, ctx, object.ty, 0);
+        ndarray.instance.set(ctx, |f| f.data, data);
+        ndarray
+    }
+    /// Check if this `NDArray` can be used as an `out` ndarray for an operation.
+    ///
+    /// Raise an exception if the shapes do not match.
+    pub fn assert_can_be_written_by_out<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        out_ndims: u64,
+        out_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) {
+        let ndarray_ndims = self.ndims_llvm(generator, ctx.ctx);
+        let ndarray_shape = self.instance.get(generator, ctx, |f| f.shape);
+
+        let output_ndims = Int(SizeT).const_int(generator, ctx.ctx, out_ndims);
+        let output_shape = out_shape;
+
+        call_nac3_ndarray_util_assert_output_shape_same(
+            generator,
+            ctx,
+            ndarray_ndims,
+            ndarray_shape,
+            output_ndims,
+            output_shape,
+        );
+    }
+}
+
+/// A convenience enum for implementing functions that acts on scalars or ndarrays or both.
+#[derive(Debug, Clone, Copy)]
+pub enum ScalarOrNDArray<'ctx> {
+    Scalar(AnyObject<'ctx>),
+    NDArray(NDArrayObject<'ctx>),
+}
+
+impl<'ctx> TryFrom<&ScalarOrNDArray<'ctx>> for AnyObject<'ctx> {
+    type Error = ();
+
+    fn try_from(value: &ScalarOrNDArray<'ctx>) -> Result<Self, Self::Error> {
+        match value {
+            ScalarOrNDArray::Scalar(scalar) => Ok(*scalar),
+            ScalarOrNDArray::NDArray(_ndarray) => Err(()),
+        }
+    }
+}
+
+impl<'ctx> TryFrom<&ScalarOrNDArray<'ctx>> for NDArrayObject<'ctx> {
+    type Error = ();
+
+    fn try_from(value: &ScalarOrNDArray<'ctx>) -> Result<Self, Self::Error> {
+        match value {
+            ScalarOrNDArray::Scalar(_scalar) => Err(()),
+            ScalarOrNDArray::NDArray(ndarray) => Ok(*ndarray),
+        }
+    }
+}
+
+impl<'ctx> ScalarOrNDArray<'ctx> {
+    /// Split on `object` either into a scalar or an ndarray.
+    ///
+    /// If `object` is an ndarray, [`ScalarOrNDArray::NDArray`].
+    ///
+    /// For everything else, it is wrapped with [`ScalarOrNDArray::Scalar`].
+    pub fn split_object<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        object: AnyObject<'ctx>,
+    ) -> ScalarOrNDArray<'ctx> {
+        match &*ctx.unifier.get_ty(object.ty) {
+            TypeEnum::TObj { obj_id, .. }
+                if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
+            {
+                let ndarray = NDArrayObject::from_object(generator, ctx, object);
+                ScalarOrNDArray::NDArray(ndarray)
+            }
+            _ => ScalarOrNDArray::Scalar(object),
+        }
+    }
+
+    /// Get the underlying [`BasicValueEnum<'ctx>`] of this [`ScalarOrNDArray`].
+    #[must_use]
+    pub fn to_basic_value_enum(self) -> BasicValueEnum<'ctx> {
+        match self {
+            ScalarOrNDArray::Scalar(scalar) => scalar.value,
+            ScalarOrNDArray::NDArray(ndarray) => ndarray.instance.value.as_basic_value_enum(),
+        }
+    }
+
+    /// Convert this [`ScalarOrNDArray`] to an ndarray - behaves like `np.asarray`.
+    /// - If this is an ndarray, the ndarray is returned.
+    /// - If this is a scalar, this function returns new ndarray created with [`NDArrayObject::make_unsized`].
+    pub fn to_ndarray<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> NDArrayObject<'ctx> {
+        match self {
+            ScalarOrNDArray::NDArray(ndarray) => *ndarray,
+            ScalarOrNDArray::Scalar(scalar) => NDArrayObject::make_unsized(generator, ctx, *scalar),
+        }
+    }
+
+    /// Get the dtype of the ndarray created if this were called with [`ScalarOrNDArray::to_ndarray`].
+    #[must_use]
+    pub fn get_dtype(&self) -> Type {
+        match self {
+            ScalarOrNDArray::NDArray(ndarray) => ndarray.dtype,
+            ScalarOrNDArray::Scalar(scalar) => scalar.ty,
+        }
+    }
+}
+
+/// An helper enum specifying how a function should produce its output.
+///
+/// Many functions in NumPy has an optional `out` parameter (e.g., `matmul`). If `out` is specified
+/// with an ndarray, the result of a function will be written to `out`. If `out` is not specified, a function will
+/// create a new ndarray and store the result in it.
+#[derive(Debug, Clone, Copy)]
+pub enum NDArrayOut<'ctx> {
+    /// Tell a function should create a new ndarray with the expected element type `dtype`.
+    NewNDArray { dtype: Type },
+    /// Tell a function to write the result to `ndarray`.
+    WriteToNDArray { ndarray: NDArrayObject<'ctx> },
+}
+
+impl<'ctx> NDArrayOut<'ctx> {
+    /// Get the dtype of this output.
+    #[must_use]
+    pub fn get_dtype(&self) -> Type {
+        match self {
+            NDArrayOut::NewNDArray { dtype } => *dtype,
+            NDArrayOut::WriteToNDArray { ndarray } => ndarray.dtype,
+        }
+    }
+}
+
+/// A version of [`call_nac3_ndarray_set_strides_by_shape`] in Rust.
+///
+/// This function is used generating strides for globally defined contiguous ndarrays.
+#[must_use]
+pub fn make_contiguous_strides(itemsize: u64, ndims: u64, shape: &[u64]) -> Vec<u64> {
+    let mut strides = Vec::with_capacity(ndims as usize);
+    let mut stride_product = 1u64;
+    for i in 0..ndims {
+        let axis = ndims - i - 1;
+        strides[axis as usize] = stride_product * itemsize;
+        stride_product *= shape[axis as usize];
+    }
+    strides
+}
--- a/nac3core/src/codegen/object/ndarray/nditer.rs
+++ b/nac3core/src/codegen/object/ndarray/nditer.rs
@ -0,0 +1,168 @@
+use inkwell::{types::BasicType, values::PointerValue, AddressSpace};
+
+use crate::codegen::{
+    irrt::{call_nac3_nditer_has_next, call_nac3_nditer_initialize, call_nac3_nditer_next},
+    model::*,
+    object::any::AnyObject,
+    stmt::{gen_for_callback, BreakContinueHooks},
+    CodeGenContext, CodeGenerator,
+};
+
+use super::NDArrayObject;
+
+/// Fields of [`NDIter`]
+pub struct NDIterFields<'ctx, F: FieldTraversal<'ctx>> {
+    pub ndims: F::Out<Int<SizeT>>,
+    pub shape: F::Out<Ptr<Int<SizeT>>>,
+    pub strides: F::Out<Ptr<Int<SizeT>>>,
+
+    pub indices: F::Out<Ptr<Int<SizeT>>>,
+    pub nth: F::Out<Int<SizeT>>,
+    pub element: F::Out<Ptr<Int<Byte>>>,
+
+    pub size: F::Out<Int<SizeT>>,
+}
+
+/// An IRRT helper structure used to iterate through an ndarray.
+#[derive(Debug, Clone, Copy, Default)]
+pub struct NDIter;
+
+impl<'ctx> StructKind<'ctx> for NDIter {
+    type Fields<F: FieldTraversal<'ctx>> = NDIterFields<'ctx, F>;
+
+    fn traverse_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            ndims: traversal.add_auto("ndims"),
+            shape: traversal.add_auto("shape"),
+            strides: traversal.add_auto("strides"),
+
+            indices: traversal.add_auto("indices"),
+            nth: traversal.add_auto("nth"),
+            element: traversal.add_auto("element"),
+
+            size: traversal.add_auto("size"),
+        }
+    }
+}
+
+/// A helper structure containing extra details of an [`NDIter`].
+#[derive(Debug, Clone)]
+pub struct NDIterHandle<'ctx> {
+    instance: Instance<'ctx, Ptr<Struct<NDIter>>>,
+    /// The ndarray this [`NDIter`] to iterating over.
+    ndarray: NDArrayObject<'ctx>,
+    /// The current indices of [`NDIter`].
+    indices: Instance<'ctx, Ptr<Int<SizeT>>>,
+}
+
+impl<'ctx> NDIterHandle<'ctx> {
+    /// Allocate an [`NDIter`] that iterates through an ndarray.
+    pub fn new<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndarray: NDArrayObject<'ctx>,
+    ) -> Self {
+        let nditer = Struct(NDIter).alloca(generator, ctx);
+        let ndims = ndarray.ndims_llvm(generator, ctx.ctx);
+
+        // The caller has the responsibility to allocate 'indices' for `NDIter`.
+        let indices = Int(SizeT).array_alloca(generator, ctx, ndims.value);
+        call_nac3_nditer_initialize(generator, ctx, nditer, ndarray.instance, indices);
+
+        NDIterHandle { ndarray, instance: nditer, indices }
+    }
+
+    #[must_use]
+    pub fn has_next<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<Bool>> {
+        call_nac3_nditer_has_next(generator, ctx, self.instance)
+    }
+
+    pub fn next<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) {
+        call_nac3_nditer_next(generator, ctx, self.instance);
+    }
+
+    /// Get pointer to the current element.
+    #[must_use]
+    pub fn get_pointer<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> PointerValue<'ctx> {
+        let elem_ty = ctx.get_llvm_type(generator, self.ndarray.dtype);
+
+        let p = self.instance.get(generator, ctx, |f| f.element);
+        ctx.builder
+            .build_pointer_cast(p.value, elem_ty.ptr_type(AddressSpace::default()), "element")
+            .unwrap()
+    }
+
+    /// Get the value of the current element.
+    #[must_use]
+    pub fn get_scalar<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> AnyObject<'ctx> {
+        let p = self.get_pointer(generator, ctx);
+        let value = ctx.builder.build_load(p, "value").unwrap();
+        AnyObject { ty: self.ndarray.dtype, value }
+    }
+
+    /// Get the index of the current element.
+    #[must_use]
+    pub fn get_index<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<SizeT>> {
+        self.instance.get(generator, ctx, |f| f.nth)
+    }
+
+    /// Get the indices of the current element.
+    #[must_use]
+    pub fn get_indices(&self) -> Instance<'ctx, Ptr<Int<SizeT>>> {
+        self.indices
+    }
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Iterate through every element in the ndarray.
+    ///
+    /// `body` also access to [`BreakContinueHooks`] to short-circuit.
+    pub fn foreach<'a, G, F>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        body: F,
+    ) -> Result<(), String>
+    where
+        G: CodeGenerator + ?Sized,
+        F: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            BreakContinueHooks<'ctx>,
+            NDIterHandle<'ctx>,
+        ) -> Result<(), String>,
+    {
+        gen_for_callback(
+            generator,
+            ctx,
+            Some("ndarray_foreach"),
+            |generator, ctx| Ok(NDIterHandle::new(generator, ctx, *self)),
+            |generator, ctx, nditer| Ok(nditer.has_next(generator, ctx).value),
+            |generator, ctx, hooks, nditer| body(generator, ctx, hooks, nditer),
+            |generator, ctx, nditer| {
+                nditer.next(generator, ctx);
+                Ok(())
+            },
+        )
+    }
+}
--- a/nac3core/src/codegen/object/ndarray/shape_util.rs
+++ b/nac3core/src/codegen/object/ndarray/shape_util.rs
@ -0,0 +1,105 @@
+use util::gen_for_model;
+
+use crate::{
+    codegen::{
+        model::*,
+        object::{any::AnyObject, list::ListObject, tuple::TupleObject},
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::TypeEnum,
+};
+
+/// Parse a NumPy-like "int sequence" input and return the int sequence as an array and its length.
+///
+/// * `sequence` - The `sequence` parameter.
+/// * `sequence_ty` - The typechecker type of `sequence`
+///
+/// The `sequence` argument type may only be one of the following:
+///   1. A list of `int32`;   e.g., `np.empty([600, 800, 3])`
+///   2. A tuple of `int32`;  e.g., `np.empty((600, 800, 3))`
+///   3. A scalar `int32`;    e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
+///
+/// All `int32` values will be sign-extended to `SizeT`.
+pub fn parse_numpy_int_sequence<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    input_sequence: AnyObject<'ctx>,
+) -> (Instance<'ctx, Int<SizeT>>, Instance<'ctx, Ptr<Int<SizeT>>>) {
+    let zero = Int(SizeT).const_0(generator, ctx.ctx);
+    let one = Int(SizeT).const_1(generator, ctx.ctx);
+
+    // The result `list` to return.
+    match &*ctx.unifier.get_ty(input_sequence.ty) {
+        TypeEnum::TObj { obj_id, .. }
+            if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
+        {
+            // 1. A list of `int32`; e.g., `np.empty([600, 800, 3])`
+
+            // Check `input_sequence`
+            let input_sequence = ListObject::from_object(generator, ctx, input_sequence);
+
+            let len = input_sequence.instance.get(generator, ctx, |f| f.len);
+            let result = Int(SizeT).array_alloca(generator, ctx, len.value);
+
+            // Load all the `int32`s from the input_sequence, cast them to `SizeT`, and store them into `result`
+            gen_for_model(generator, ctx, zero, len, one, |generator, ctx, _hooks, i| {
+                // Load the i-th int32 in the input sequence
+                let int = input_sequence
+                    .instance
+                    .get(generator, ctx, |f| f.items)
+                    .get_index(generator, ctx, i.value)
+                    .value
+                    .into_int_value();
+
+                // Cast to SizeT
+                let int = Int(SizeT).s_extend_or_bit_cast(generator, ctx, int);
+
+                // Store
+                result.set_index(ctx, i.value, int);
+
+                Ok(())
+            })
+            .unwrap();
+
+            (len, result)
+        }
+        TypeEnum::TTuple { .. } => {
+            // 2. A tuple of ints; e.g., `np.empty((600, 800, 3))`
+
+            let input_sequence = TupleObject::from_object(ctx, input_sequence);
+
+            let len = input_sequence.len(generator, ctx);
+
+            let result = Int(SizeT).array_alloca(generator, ctx, len.value);
+
+            for i in 0..input_sequence.num_elements() {
+                // Get the i-th element off of the tuple and load it into `result`.
+                let int = input_sequence.index(ctx, i).value.into_int_value();
+                let int = Int(SizeT).s_extend_or_bit_cast(generator, ctx, int);
+
+                result.set_index_const(ctx, i as u64, int);
+            }
+
+            (len, result)
+        }
+        TypeEnum::TObj { obj_id, .. }
+            if *obj_id == ctx.primitives.int32.obj_id(&ctx.unifier).unwrap() =>
+        {
+            // 3. A scalar int; e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
+            let input_int = input_sequence.value.into_int_value();
+
+            let len = Int(SizeT).const_1(generator, ctx.ctx);
+            let result = Int(SizeT).array_alloca(generator, ctx, len.value);
+            let int = Int(SizeT).s_extend_or_bit_cast(generator, ctx, input_int);
+
+            // Storing into result[0]
+            result.store(ctx, int);
+
+            (len, result)
+        }
+        _ => panic!(
+            "encountered unknown sequence type: {}",
+            ctx.unifier.stringify(input_sequence.ty)
+        ),
+    }
+}
--- a/nac3core/src/codegen/object/ndarray/view.rs
+++ b/nac3core/src/codegen/object/ndarray/view.rs
@ -0,0 +1,119 @@
+use crate::codegen::{
+    irrt::{call_nac3_ndarray_reshape_resolve_and_check_new_shape, call_nac3_ndarray_transpose},
+    model::*,
+    CodeGenContext, CodeGenerator,
+};
+
+use super::{indexing::RustNDIndex, NDArrayObject};
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Make sure the ndarray is at least `ndmin`-dimensional.
+    ///
+    /// If this ndarray's `ndims` is less than `ndmin`, a view is created on this with 1s prepended to the shape.
+    /// If this ndarray's `ndims` is not less than `ndmin`, this function does nothing and return this ndarray.
+    #[must_use]
+    pub fn atleast_nd<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndmin: u64,
+    ) -> Self {
+        if self.ndims < ndmin {
+            // return this_ndarray[np.newaxis, np.newaxis, and more, ...]
+            let mut indices = vec![];
+            for _ in self.ndims..ndmin {
+                indices.push(RustNDIndex::NewAxis);
+            }
+            indices.push(RustNDIndex::Ellipsis);
+            self.index(generator, ctx, &indices)
+        } else {
+            *self
+        }
+    }
+
+    /// Create a reshaped view on this ndarray like `np.reshape()`.
+    ///
+    /// If there is a `-1` in `new_shape`, it will be resolved; `new_shape` would **NOT** be modified as a result.
+    ///
+    /// If reshape without copying is impossible, this function will allocate a new ndarray and copy contents.
+    ///
+    /// * `new_ndims` - The number of dimensions of `new_shape` as a [`Type`].
+    /// * `new_shape` - The target shape to do `np.reshape()`.
+    #[must_use]
+    pub fn reshape_or_copy<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        new_ndims: u64,
+        new_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
+    ) -> Self {
+        // TODO: The current criterion for whether to do a full copy or not is by checking `is_c_contiguous`,
+        // but this is not optimal - there are cases when the ndarray is not contiguous but could be reshaped
+        // without copying data. Look into how numpy does it.
+
+        let current_bb = ctx.builder.get_insert_block().unwrap();
+        let then_bb = ctx.ctx.insert_basic_block_after(current_bb, "then_bb");
+        let else_bb = ctx.ctx.insert_basic_block_after(then_bb, "else_bb");
+        let end_bb = ctx.ctx.insert_basic_block_after(else_bb, "end_bb");
+
+        let dst_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, new_ndims);
+        dst_ndarray.copy_shape_from_array(generator, ctx, new_shape);
+
+        // Reolsve negative indices
+        let size = self.size(generator, ctx);
+        let dst_ndims = dst_ndarray.ndims_llvm(generator, ctx.ctx);
+        let dst_shape = dst_ndarray.instance.get(generator, ctx, |f| f.shape);
+        call_nac3_ndarray_reshape_resolve_and_check_new_shape(
+            generator, ctx, size, dst_ndims, dst_shape,
+        );
+
+        let is_c_contiguous = self.is_c_contiguous(generator, ctx);
+        ctx.builder.build_conditional_branch(is_c_contiguous.value, then_bb, else_bb).unwrap();
+
+        // Inserting into then_bb: reshape is possible without copying
+        ctx.builder.position_at_end(then_bb);
+        dst_ndarray.set_strides_contiguous(generator, ctx);
+        dst_ndarray.instance.set(ctx, |f| f.data, self.instance.get(generator, ctx, |f| f.data));
+        ctx.builder.build_unconditional_branch(end_bb).unwrap();
+
+        // Inserting into else_bb: reshape is impossible without copying
+        ctx.builder.position_at_end(else_bb);
+        dst_ndarray.create_data(generator, ctx);
+        dst_ndarray.copy_data_from(generator, ctx, *self);
+        ctx.builder.build_unconditional_branch(end_bb).unwrap();
+
+        // Reposition for continuation
+        ctx.builder.position_at_end(end_bb);
+
+        dst_ndarray
+    }
+
+    /// Create a transposed view on this ndarray like `np.transpose(<ndarray>, <axes> = None)`.
+    /// * `axes` - If specified, should be an array of the permutation (negative indices are **allowed**).
+    #[must_use]
+    pub fn transpose<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        axes: Option<Instance<'ctx, Ptr<Int<SizeT>>>>,
+    ) -> Self {
+        // Define models
+        let transposed_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, self.ndims);
+
+        let num_axes = self.ndims_llvm(generator, ctx.ctx);
+
+        // `axes = nullptr` if `axes` is unspecified.
+        let axes = axes.unwrap_or_else(|| Ptr(Int(SizeT)).nullptr(generator, ctx.ctx));
+
+        call_nac3_ndarray_transpose(
+            generator,
+            ctx,
+            self.instance,
+            transposed_ndarray.instance,
+            num_axes,
+            axes,
+        );
+
+        transposed_ndarray
+    }
+}
--- a/nac3core/src/codegen/object/range.rs
+++ b/nac3core/src/codegen/object/range.rs
@ -0,0 +1,70 @@
+use crate::codegen::{irrt::call_nac3_range_len_i32, model::*, CodeGenContext, CodeGenerator};
+
+use super::any::AnyObject;
+
+/// A range in NAC3.
+pub type Range<N> = Array<Len<3>, Int<N>>;
+
+impl<'ctx, N: IntKind<'ctx>> Instance<'ctx, Ptr<Range<N>>> {
+    /// Get GEP to `range.start`.
+    pub fn start(&self, ctx: &CodeGenContext<'ctx, '_>) -> Instance<'ctx, Ptr<Int<N>>> {
+        self.gep_const(ctx, 0)
+    }
+
+    /// Get GEP to `range.stop`.
+    pub fn stop(&self, ctx: &CodeGenContext<'ctx, '_>) -> Instance<'ctx, Ptr<Int<N>>> {
+        self.gep_const(ctx, 1)
+    }
+
+    /// Get GEP to `range.step`.
+    pub fn step(&self, ctx: &CodeGenContext<'ctx, '_>) -> Instance<'ctx, Ptr<Int<N>>> {
+        self.gep_const(ctx, 2)
+    }
+
+    /// Convenience function to get the load the `(start, stop, step)` of this range.
+    #[allow(clippy::type_complexity)]
+    pub fn destructure<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> (Instance<'ctx, Int<N>>, Instance<'ctx, Int<N>>, Instance<'ctx, Int<N>>) {
+        let start = self.start(ctx).load(generator, ctx);
+        let stop = self.stop(ctx).load(generator, ctx);
+        let step = self.step(ctx).load(generator, ctx);
+        (start, stop, step)
+    }
+}
+
+// TODO: `RangeObject` in the future will have range32, range64
+
+/// A NAC3 Python range object.
+#[derive(Debug, Clone, Copy)]
+pub struct RangeObject<'ctx> {
+    pub instance: Instance<'ctx, Ptr<Range<Int32>>>,
+}
+
+impl<'ctx> RangeObject<'ctx> {
+    /// Attempt to convert an [`AnyObject`] into a [`RangeObject`].
+    pub fn from_object<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        object: AnyObject<'ctx>,
+    ) -> RangeObject<'ctx> {
+        assert!(ctx.unifier.unioned(object.ty, ctx.primitives.range));
+
+        let instance = Ptr(Range::default()).check_value(generator, ctx.ctx, object.value).unwrap();
+        RangeObject { instance }
+    }
+
+    /// Get the `len()` of this range.
+    pub fn len<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<Int32>> {
+        let start = self.instance.start(ctx).load(generator, ctx);
+        let stop = self.instance.stop(ctx).load(generator, ctx);
+        let step = self.instance.step(ctx).load(generator, ctx);
+        call_nac3_range_len_i32(generator, ctx, start, stop, step)
+    }
+}
--- a/nac3core/src/codegen/object/tuple.rs
+++ b/nac3core/src/codegen/object/tuple.rs
@ -0,0 +1,101 @@
+use inkwell::values::StructValue;
+use itertools::Itertools;
+
+use crate::{
+    codegen::{model::*, CodeGenContext, CodeGenerator},
+    typecheck::typedef::{Type, TypeEnum},
+};
+
+use super::any::AnyObject;
+
+/// A NAC3 tuple object.
+///
+/// NOTE: This struct has no copy trait.
+#[derive(Debug, Clone)]
+pub struct TupleObject<'ctx> {
+    /// The type of the tuple.
+    pub tys: Vec<Type>,
+    /// The underlying LLVM struct value of this tuple.
+    pub value: StructValue<'ctx>,
+}
+
+impl<'ctx> TupleObject<'ctx> {
+    pub fn from_object(ctx: &mut CodeGenContext<'ctx, '_>, object: AnyObject<'ctx>) -> Self {
+        // TODO: Keep `is_vararg_ctx` from TTuple?
+
+        assert!(matches!(&*ctx.unifier.get_ty(object.ty), TypeEnum::TTuple { .. }));
+
+        // Sanity check on object type.
+        let TypeEnum::TTuple { ty: tys, .. } = &*ctx.unifier.get_ty(object.ty) else {
+            panic!(
+                "Expected type to be a TypeEnum::TTuple, got {}",
+                ctx.unifier.stringify(object.ty)
+            );
+        };
+
+        // Check number of fields
+        let value = object.value.into_struct_value();
+        let value_num_fields = value.get_type().count_fields() as usize;
+        assert!(
+            value_num_fields == tys.len(),
+            "Tuple type has {} item(s), but the LLVM struct value has {} field(s)",
+            tys.len(),
+            value_num_fields
+        );
+
+        TupleObject { tys: tys.clone(), value }
+    }
+
+    /// Convenience function. Create a [`TupleObject`] from an iterator of objects.
+    pub fn from_objects<I, G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        objects: I,
+    ) -> Self
+    where
+        I: IntoIterator<Item = AnyObject<'ctx>>,
+    {
+        let (values, tys): (Vec<_>, Vec<_>) =
+            objects.into_iter().map(|object| (object.value, object.ty)).unzip();
+
+        let llvm_tys = tys.iter().map(|ty| ctx.get_llvm_type(generator, *ty)).collect_vec();
+        let llvm_tuple_ty = ctx.ctx.struct_type(&llvm_tys, false);
+
+        let pllvm_tuple = ctx.builder.build_alloca(llvm_tuple_ty, "tuple").unwrap();
+        for (i, val) in values.into_iter().enumerate() {
+            let pval = ctx.builder.build_struct_gep(pllvm_tuple, i as u32, "value").unwrap();
+            ctx.builder.build_store(pval, val).unwrap();
+        }
+
+        let value = ctx.builder.build_load(pllvm_tuple, "").unwrap().into_struct_value();
+        TupleObject { tys, value }
+    }
+
+    #[must_use]
+    pub fn num_elements(&self) -> usize {
+        self.tys.len()
+    }
+
+    /// Get the `len()` of this tuple.
+    #[must_use]
+    pub fn len<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Instance<'ctx, Int<SizeT>> {
+        Int(SizeT).const_int(generator, ctx.ctx, self.num_elements() as u64)
+    }
+
+    /// Get the `i`-th (0-based) object in this tuple.
+    pub fn index(&self, ctx: &mut CodeGenContext<'ctx, '_>, i: usize) -> AnyObject<'ctx> {
+        assert!(
+            i < self.num_elements(),
+            "Tuple object with length {} have index {i}",
+            self.num_elements()
+        );
+
+        let value = ctx.builder.build_extract_value(self.value, i as u32, "tuple[{i}]").unwrap();
+        let ty = self.tys[i];
+        AnyObject { ty, value }
+    }
+}
--- a/nac3core/src/codegen/stmt.rs
+++ b/nac3core/src/codegen/stmt.rs
@ -1,3 +1,24 @@
+use super::{
+    super::symbol_resolver::ValueEnum,
+    irrt::{handle_slice_indices, list_slice_assignment},
+    object::{
+        any::AnyObject,
+        list::ListObject,
+        ndarray::{
+            indexing::util::gen_ndarray_subscript_ndindices, NDArrayObject, ScalarOrNDArray,
+        },
+        range::RangeObject,
+    },
+    CodeGenContext, CodeGenerator,
+};
+use crate::{
+    codegen::{classes::ArraySliceValue, expr::gen_binop_expr, gen_in_range_check, model::*},
+    toplevel::{DefinitionId, TopLevelDef},
+    typecheck::{
+        magic_methods::Binop,
+        typedef::{iter_type_vars, FunSignature, Type, TypeEnum},
+    },
+};
 use inkwell::{
    attributes::{Attribute, AttributeLoc},
    basic_block::BasicBlock,
@ -6,28 +27,10 @@ use inkwell::{
    IntPredicate,
 };
 use itertools::{izip, Itertools};
-
 use nac3parser::ast::{
    Constant, ExcepthandlerKind, Expr, ExprKind, Location, Stmt, StmtKind, StrRef,
 };

-use super::{
-    classes::{ArrayLikeIndexer, ArraySliceValue, ListValue, RangeValue},
-    expr::{destructure_range, gen_binop_expr},
-    gen_in_range_check,
-    irrt::{handle_slice_indices, list_slice_assignment},
-    macros::codegen_unreachable,
-    CodeGenContext, CodeGenerator,
-};
-use crate::{
-    symbol_resolver::ValueEnum,
-    toplevel::{DefinitionId, TopLevelDef},
-    typecheck::{
-        magic_methods::Binop,
-        typedef::{iter_type_vars, FunSignature, Type, TypeEnum},
-    },
-};
-
 /// See [`CodeGenerator::gen_var_alloc`].
 pub fn gen_var<'ctx>(
    ctx: &mut CodeGenContext<'ctx, '_>,
@ -121,7 +124,7 @@ pub fn gen_store_target<'ctx, G: CodeGenerator>(
                return Ok(None);
            };
            let BasicValueEnum::PointerValue(ptr) = val else {
-                codegen_unreachable!(ctx);
+                unreachable!();
            };
            unsafe {
                ctx.builder.build_in_bounds_gep(
@ -135,7 +138,7 @@ pub fn gen_store_target<'ctx, G: CodeGenerator>(
            }
            .unwrap()
        }
-        _ => codegen_unreachable!(ctx),
+        _ => unreachable!(),
    }))
 }

@ -176,14 +179,6 @@ pub fn gen_assign<'ctx, G: CodeGenerator>(
                }
            }
            let val = value.to_basic_value_enum(ctx, generator, target.custom.unwrap())?;
-
-            // Perform i1 <-> i8 conversion as needed
-            let val = if ctx.unifier.unioned(target.custom.unwrap(), ctx.primitives.bool) {
-                generator.bool_to_i8(ctx, val.into_int_value()).into()
-            } else {
-                val
-            };
-
            ctx.builder.build_store(ptr, val).unwrap();
        }
    };
@ -201,12 +196,12 @@ pub fn gen_assign_target_list<'ctx, G: CodeGenerator>(
    // Deconstruct the tuple `value`
    let BasicValueEnum::StructValue(tuple) = value.to_basic_value_enum(ctx, generator, value_ty)?
    else {
-        codegen_unreachable!(ctx)
+        unreachable!()
    };

    // NOTE: Currently, RHS's type is forced to be a Tuple by the type inferencer.
    let TypeEnum::TTuple { ty: tuple_tys, .. } = &*ctx.unifier.get_ty(value_ty) else {
-        codegen_unreachable!(ctx);
+        unreachable!();
    };

    assert_eq!(tuple.get_type().count_fields() as usize, tuple_tys.len());
@ -266,7 +261,7 @@ pub fn gen_assign_target_list<'ctx, G: CodeGenerator>(
            // Now assign with that sub-tuple to the starred target.
            generator.gen_assign(ctx, target, ValueEnum::Dynamic(sub_tuple_val), sub_tuple_ty)?;
        } else {
-            codegen_unreachable!(ctx) // The typechecker ensures this
+            unreachable!() // The typechecker ensures this
        }

        // Handle assignment after the starred target
@ -298,65 +293,56 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
    let key_ty = key.custom.unwrap();

    match &*ctx.unifier.get_ty(target_ty) {
-        TypeEnum::TObj { obj_id, params: list_params, .. }
+        TypeEnum::TObj { obj_id, .. }
            if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
        {
            // Handle list item assignment
-            let llvm_usize = generator.get_size_type(ctx.ctx);
-            let target_item_ty = iter_type_vars(list_params).next().unwrap().ty;
-
            let target = generator
                .gen_expr(ctx, target)?
                .unwrap()
-                .to_basic_value_enum(ctx, generator, target_ty)?
-                .into_pointer_value();
-            let target = ListValue::from_ptr_val(target, llvm_usize, None);
+                .to_basic_value_enum(ctx, generator, target_ty)?;
+
+            let target = AnyObject { ty: target_ty, value: target };
+            let target = ListObject::from_object(generator, ctx, target);
+
+            let target_len = target.instance.get(generator, ctx, |f| f.len);
+            let target_item_type_llvm = ctx.get_llvm_type(generator, target.item_type);

            if let ExprKind::Slice { .. } = &key.node {
                // Handle assigning to a slice
-                let ExprKind::Slice { lower, upper, step } = &key.node else {
-                    codegen_unreachable!(ctx)
-                };
-                let Some((start, end, step)) = handle_slice_indices(
-                    lower,
-                    upper,
-                    step,
-                    ctx,
-                    generator,
-                    target.load_size(ctx, None),
-                )?
+                let ExprKind::Slice { lower, upper, step } = &key.node else { unreachable!() };
+                let Some((start, end, step)) =
+                    handle_slice_indices(lower, upper, step, ctx, generator, target_len.value)?
                else {
                    return Ok(());
                };

-                let value =
-                    value.to_basic_value_enum(ctx, generator, value_ty)?.into_pointer_value();
-                let value = ListValue::from_ptr_val(value, llvm_usize, None);
+                let value = value.to_basic_value_enum(ctx, generator, value_ty)?;

-                let target_item_ty = ctx.get_llvm_type(generator, target_item_ty);
-                let Some(src_ind) = handle_slice_indices(
-                    &None,
-                    &None,
-                    &None,
-                    ctx,
-                    generator,
-                    value.load_size(ctx, None),
-                )?
+                let value = AnyObject { ty: value_ty, value };
+                let value = ListObject::from_object(generator, ctx, value);
+
+                let value_len = value.instance.get(generator, ctx, |f| f.len);
+
+                let Some(src_ind) =
+                    handle_slice_indices(&None, &None, &None, ctx, generator, value_len.value)?
                else {
                    return Ok(());
                };
                list_slice_assignment(
                    generator,
                    ctx,
-                    target_item_ty,
-                    target,
+                    target_item_type_llvm,
+                    target.instance,
                    (start, end, step),
-                    value,
+                    value.instance,
                    src_ind,
                );
            } else {
                // Handle assigning to an index
-                let len = target.load_size(ctx, Some("len"));
+                let value = value.to_basic_value_enum(ctx, generator, value_ty)?;
+                let value =
+                    Any(target_item_type_llvm).check_value(generator, ctx.ctx, value).unwrap();

                let index = generator
                    .gen_expr(ctx, key)?
@ -378,7 +364,8 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
                        "is_neg",
                    )
                    .unwrap();
-                let adjusted = ctx.builder.build_int_add(index, len, "adjusted").unwrap();
+                let adjusted =
+                    ctx.builder.build_int_add(index, target_len.value, "adjusted").unwrap();
                let index = ctx
                    .builder
                    .build_select(is_negative, adjusted, index, "index")
@ -389,29 +376,70 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
                // bigger than the length (for unsigned cmp)
                let bound_check = ctx
                    .builder
-                    .build_int_compare(IntPredicate::ULT, index, len, "inbound")
+                    .build_int_compare(IntPredicate::ULT, index, target_len.value, "inbound")
                    .unwrap();
                ctx.make_assert(
                    generator,
                    bound_check,
                    "0:IndexError",
                    "index {0} out of bounds 0:{1}",
-                    [Some(index), Some(len), None],
+                    [Some(index), Some(target_len.value), None],
                    key.location,
                );

                // Write value to index on list
-                let item_ptr =
-                    target.data().ptr_offset(ctx, generator, &index, Some("list_item_ptr"));
-                let value = value.to_basic_value_enum(ctx, generator, value_ty)?;
-                ctx.builder.build_store(item_ptr, value).unwrap();
+                target
+                    .instance
+                    .get(generator, ctx, |f| f.items)
+                    .offset(ctx, index)
+                    .store(ctx, value);
            }
        }
        TypeEnum::TObj { obj_id, .. }
            if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
        {
            // Handle NDArray item assignment
-            todo!("ndarray subscript assignment is not yet implemented");
+            // Process target
+            let target = generator
+                .gen_expr(ctx, target)?
+                .unwrap()
+                .to_basic_value_enum(ctx, generator, target_ty)?;
+            let target = AnyObject { value: target, ty: target_ty };
+
+            // Process key
+            let key = gen_ndarray_subscript_ndindices(generator, ctx, key)?;
+
+            // Process value
+            let value = value.to_basic_value_enum(ctx, generator, value_ty)?;
+            let value = AnyObject { value, ty: value_ty };
+
+            /*
+                Reference code:
+                ```python
+                target = target[key]
+                value = np.asarray(value)
+
+                shape = np.broadcast_shape((target, value))
+
+                target = np.broadcast_to(target, shape)
+                value = np.broadcast_to(value, shape)
+
+                ...and finally copy 1-1 from value to target.
+                ```
+            */
+
+            let target = NDArrayObject::from_object(generator, ctx, target);
+            let target = target.index(generator, ctx, &key);
+
+            let value =
+                ScalarOrNDArray::split_object(generator, ctx, value).to_ndarray(generator, ctx);
+
+            let broadcast_result = NDArrayObject::broadcast(generator, ctx, &[target, value]);
+
+            let target = broadcast_result.ndarrays[0];
+            let value = broadcast_result.ndarrays[1];
+
+            target.copy_data_from(generator, ctx, value);
        }
        _ => {
            panic!("encountered unknown target type: {}", ctx.unifier.stringify(target_ty));
@ -426,9 +454,7 @@ pub fn gen_for<G: CodeGenerator>(
    ctx: &mut CodeGenContext<'_, '_>,
    stmt: &Stmt<Option<Type>>,
 ) -> Result<(), String> {
-    let StmtKind::For { iter, target, body, orelse, .. } = &stmt.node else {
-        codegen_unreachable!(ctx)
-    };
+    let StmtKind::For { iter, target, body, orelse, .. } = &stmt.node else { unreachable!() };

    // var_assignment static values may be changed in another branch
    // if so, remove the static value as it may not be correct in this branch
@ -463,16 +489,22 @@ pub fn gen_for<G: CodeGenerator>(
        TypeEnum::TObj { obj_id, .. }
            if *obj_id == ctx.primitives.range.obj_id(&ctx.unifier).unwrap() =>
        {
-            let iter_val = RangeValue::from_ptr_val(iter_val.into_pointer_value(), Some("range"));
+            let range = AnyObject { value: iter_val, ty: iter_ty };
+            let range = RangeObject::from_object(generator, ctx, range);
+
+            let (start, stop, step) = range.instance.destructure(generator, ctx);
+            let start = start.value;
+            let stop = stop.value;
+            let step = step.value;
+
            // Internal variable for loop; Cannot be assigned
            let i = generator.gen_var_alloc(ctx, int32.into(), Some("for.i.addr"))?;
            // Variable declared in "target" expression of the loop; Can be reassigned *or* shadowed
            let Some(target_i) =
                generator.gen_store_target(ctx, target, Some("for.target.addr"))?
            else {
-                codegen_unreachable!(ctx)
+                unreachable!()
            };
-            let (start, stop, step) = destructure_range(ctx, iter_val);

            ctx.builder.build_store(i, start).unwrap();

@ -913,7 +945,7 @@ pub fn gen_while<G: CodeGenerator>(
    ctx: &mut CodeGenContext<'_, '_>,
    stmt: &Stmt<Option<Type>>,
 ) -> Result<(), String> {
-    let StmtKind::While { test, body, orelse, .. } = &stmt.node else { codegen_unreachable!(ctx) };
+    let StmtKind::While { test, body, orelse, .. } = &stmt.node else { unreachable!() };

    // var_assignment static values may be changed in another branch
    // if so, remove the static value as it may not be correct in this branch
@ -943,7 +975,7 @@ pub fn gen_while<G: CodeGenerator>(

        return Ok(());
    };
-    let BasicValueEnum::IntValue(test) = test else { codegen_unreachable!(ctx) };
+    let BasicValueEnum::IntValue(test) = test else { unreachable!() };

    ctx.builder
        .build_conditional_branch(generator.bool_to_i1(ctx, test), body_bb, orelse_bb)
@ -1091,7 +1123,7 @@ pub fn gen_if<G: CodeGenerator>(
    ctx: &mut CodeGenContext<'_, '_>,
    stmt: &Stmt<Option<Type>>,
 ) -> Result<(), String> {
-    let StmtKind::If { test, body, orelse, .. } = &stmt.node else { codegen_unreachable!(ctx) };
+    let StmtKind::If { test, body, orelse, .. } = &stmt.node else { unreachable!() };

    // var_assignment static values may be changed in another branch
    // if so, remove the static value as it may not be correct in this branch
@ -1214,11 +1246,11 @@ pub fn exn_constructor<'ctx>(
    let zelf_id = if let TypeEnum::TObj { obj_id, .. } = &*ctx.unifier.get_ty(zelf_ty) {
        obj_id.0
    } else {
-        codegen_unreachable!(ctx)
+        unreachable!()
    };
    let defs = ctx.top_level.definitions.read();
    let def = defs[zelf_id].read();
-    let TopLevelDef::Class { name: zelf_name, .. } = &*def else { codegen_unreachable!(ctx) };
+    let TopLevelDef::Class { name: zelf_name, .. } = &*def else { unreachable!() };
    let exception_name = format!("{}:{}", ctx.resolver.get_exception_id(zelf_id), zelf_name);
    unsafe {
        let id_ptr = ctx.builder.build_in_bounds_gep(zelf, &[zero, zero], "exn.id").unwrap();
@ -1326,7 +1358,7 @@ pub fn gen_try<'ctx, 'a, G: CodeGenerator>(
    target: &Stmt<Option<Type>>,
 ) -> Result<(), String> {
    let StmtKind::Try { body, handlers, orelse, finalbody, .. } = &target.node else {
-        codegen_unreachable!(ctx)
+        unreachable!()
    };

    // if we need to generate anything related to exception, we must have personality defined
@ -1403,7 +1435,7 @@ pub fn gen_try<'ctx, 'a, G: CodeGenerator>(
            if let TypeEnum::TObj { obj_id, .. } = &*ctx.unifier.get_ty(type_.custom.unwrap()) {
                *obj_id
            } else {
-                codegen_unreachable!(ctx)
+                unreachable!()
            };
        let exception_name = format!("{}:{}", ctx.resolver.get_exception_id(obj_id.0), exn_name);
        let exn_id = ctx.resolver.get_string_id(&exception_name);
@ -1675,23 +1707,6 @@ pub fn gen_return<G: CodeGenerator>(
    } else {
        None
    };
-
-    // Remap boolean return type into i1
-    let value = value.map(|ret_val| {
-        // The "return type" of a sret function is in the first parameter
-        let expected_ty = if ctx.need_sret {
-            func.get_type().get_param_types()[0]
-        } else {
-            func.get_type().get_return_type().unwrap()
-        };
-
-        if matches!(expected_ty, BasicTypeEnum::IntType(ty) if ty.get_bit_width() == 1) {
-            generator.bool_to_i1(ctx, ret_val.into_int_value()).into()
-        } else {
-            ret_val
-        }
-    });
-
    if let Some(return_target) = ctx.return_target {
        if let Some(value) = value {
            ctx.builder.build_store(ctx.return_buffer.unwrap(), value).unwrap();
@ -1702,6 +1717,25 @@ pub fn gen_return<G: CodeGenerator>(
        ctx.builder.build_store(ctx.return_buffer.unwrap(), value.unwrap()).unwrap();
        ctx.builder.build_return(None).unwrap();
    } else {
+        // Remap boolean return type into i1
+        let value = value.map(|v| {
+            let expected_ty = func.get_type().get_return_type().unwrap();
+            let ret_val = v.as_basic_value_enum();
+
+            if expected_ty.is_int_type() && ret_val.is_int_value() {
+                let ret_type = expected_ty.into_int_type();
+                let ret_val = ret_val.into_int_value();
+
+                if ret_type.get_bit_width() == 1 && ret_val.get_type().get_bit_width() != 1 {
+                    generator.bool_to_i1(ctx, ret_val)
+                } else {
+                    ret_val
+                }
+                .into()
+            } else {
+                ret_val
+            }
+        });
        let value = value.as_ref().map(|v| v as &dyn BasicValue);
        ctx.builder.build_return(value).unwrap();
    }
@ -1770,30 +1804,7 @@ pub fn gen_stmt<G: CodeGenerator>(
        StmtKind::Try { .. } => gen_try(generator, ctx, stmt)?,
        StmtKind::Raise { exc, .. } => {
            if let Some(exc) = exc {
-                let exn = if let ExprKind::Name { id, .. } = &exc.node {
-                    // Handle "raise Exception" short form
-                    let def_id = ctx.resolver.get_identifier_def(*id).map_err(|e| {
-                        format!("{} (at {})", e.iter().next().unwrap(), exc.location)
-                    })?;
-                    let def = ctx.top_level.definitions.read();
-                    let TopLevelDef::Class { constructor, .. } = *def[def_id.0].read() else {
-                        return Err(format!("Failed to resolve symbol {id} (at {})", exc.location));
-                    };
-
-                    let TypeEnum::TFunc(signature) =
-                        ctx.unifier.get_ty(constructor.unwrap()).as_ref().clone()
-                    else {
-                        return Err(format!("Failed to resolve symbol {id} (at {})", exc.location));
-                    };
-
-                    generator
-                        .gen_call(ctx, None, (&signature, def_id), Vec::default())?
-                        .map(Into::into)
-                } else {
-                    generator.gen_expr(ctx, exc)?
-                };
-
-                let exc = if let Some(v) = exn {
+                let exc = if let Some(v) = generator.gen_expr(ctx, exc)? {
                    v.to_basic_value_enum(ctx, generator, exc.custom.unwrap())?
                } else {
                    return Ok(());
@ -1828,37 +1839,6 @@ pub fn gen_stmt<G: CodeGenerator>(
                stmt.location,
            );
        }
-        StmtKind::Global { names, .. } => {
-            let registered_globals = ctx
-                .top_level
-                .definitions
-                .read()
-                .iter()
-                .filter_map(|def| {
-                    if let TopLevelDef::Variable { simple_name, ty, .. } = &*def.read() {
-                        Some((*simple_name, *ty))
-                    } else {
-                        None
-                    }
-                })
-                .collect_vec();
-
-            for id in names {
-                let Some((_, ty)) = registered_globals.iter().find(|(name, _)| name == id) else {
-                    return Err(format!("{id} is not a global at {}", stmt.location));
-                };
-
-                let resolver = ctx.resolver.clone();
-                let ptr = resolver
-                    .get_symbol_value(*id, ctx, generator)
-                    .map(|val| val.to_basic_value_enum(ctx, generator, *ty))
-                    .transpose()?
-                    .map(BasicValueEnum::into_pointer_value)
-                    .unwrap();
-
-                ctx.var_assignment.insert(*id, (ptr, None, 0));
-            }
-        }
        _ => unimplemented!(),
    };
    Ok(())
--- a/nac3core/src/codegen/test.rs
+++ b/nac3core/src/codegen/test.rs
@ -1,37 +1,32 @@
-use std::{
-    collections::{HashMap, HashSet},
-    sync::Arc,
-};
-
-use indexmap::IndexMap;
-use indoc::indoc;
-use inkwell::{
-    targets::{InitializationConfig, Target},
-    OptimizationLevel,
-};
-use nac3parser::{
-    ast::{fold::Fold, FileName, StrRef},
-    parser::parse_program,
-};
-use parking_lot::RwLock;
-
-use super::{
-    classes::{ListType, NDArrayType, ProxyType, RangeType},
-    concrete_type::ConcreteTypeStore,
-    CodeGenContext, CodeGenLLVMOptions, CodeGenTargetMachineOptions, CodeGenTask, CodeGenerator,
-    DefaultCodeGenerator, WithCall, WorkerRegistry,
-};
 use crate::{
+    codegen::{
+        concrete_type::ConcreteTypeStore, CodeGenContext, CodeGenLLVMOptions,
+        CodeGenTargetMachineOptions, CodeGenTask, DefaultCodeGenerator, WithCall, WorkerRegistry,
+    },
    symbol_resolver::{SymbolResolver, ValueEnum},
    toplevel::{
        composer::{ComposerConfig, TopLevelComposer},
        DefinitionId, FunInstance, TopLevelContext, TopLevelDef,
    },
    typecheck::{
-        type_inferencer::{FunctionData, IdentifierInfo, Inferencer, PrimitiveStore},
+        type_inferencer::{FunctionData, Inferencer, PrimitiveStore},
        typedef::{FunSignature, FuncArg, Type, TypeEnum, Unifier, VarMap},
    },
 };
+use indexmap::IndexMap;
+use indoc::indoc;
+use inkwell::{
+    targets::{InitializationConfig, Target},
+    OptimizationLevel,
+};
+use nac3parser::ast::FileName;
+use nac3parser::{
+    ast::{fold::Fold, StrRef},
+    parser::parse_program,
+};
+use parking_lot::RwLock;
+use std::collections::{HashMap, HashSet};
+use std::sync::Arc;

 struct Resolver {
    id_to_type: HashMap<StrRef, Type>,
@ -67,7 +62,6 @@ impl SymbolResolver for Resolver {
        &self,
        _: StrRef,
        _: &mut CodeGenContext<'ctx, '_>,
-        _: &mut dyn CodeGenerator,
    ) -> Option<ValueEnum<'ctx>> {
        unimplemented!()
    }
@ -142,8 +136,7 @@ fn test_primitives() {
    };
    let mut virtual_checks = Vec::new();
    let mut calls = HashMap::new();
-    let mut identifiers: HashMap<_, _> =
-        ["a".into(), "b".into()].map(|id| (id, IdentifierInfo::default())).into();
+    let mut identifiers: HashSet<_> = ["a".into(), "b".into()].into();
    let mut inferencer = Inferencer {
        top_level: &top_level,
        function_data: &mut function_data,
@ -322,8 +315,7 @@ fn test_simple_call() {
    };
    let mut virtual_checks = Vec::new();
    let mut calls = HashMap::new();
-    let mut identifiers: HashMap<_, _> =
-        ["a".into(), "foo".into()].map(|id| (id, IdentifierInfo::default())).into();
+    let mut identifiers: HashSet<_> = ["a".into(), "foo".into()].into();
    let mut inferencer = Inferencer {
        top_level: &top_level,
        function_data: &mut function_data,
@ -442,35 +434,3 @@ fn test_simple_call() {
    registry.add_task(task);
    registry.wait_tasks_complete(handles);
 }
-
-#[test]
-fn test_classes_list_type_new() {
-    let ctx = inkwell::context::Context::create();
-    let generator = DefaultCodeGenerator::new(String::new(), 64);
-
-    let llvm_i32 = ctx.i32_type();
-    let llvm_usize = generator.get_size_type(&ctx);
-
-    let llvm_list = ListType::new(&generator, &ctx, llvm_i32.into());
-    assert!(ListType::is_type(llvm_list.as_base_type(), llvm_usize).is_ok());
-}
-
-#[test]
-fn test_classes_range_type_new() {
-    let ctx = inkwell::context::Context::create();
-
-    let llvm_range = RangeType::new(&ctx);
-    assert!(RangeType::is_type(llvm_range.as_base_type()).is_ok());
-}
-
-#[test]
-fn test_classes_ndarray_type_new() {
-    let ctx = inkwell::context::Context::create();
-    let generator = DefaultCodeGenerator::new(String::new(), 64);
-
-    let llvm_i32 = ctx.i32_type();
-    let llvm_usize = generator.get_size_type(&ctx);
-
-    let llvm_ndarray = NDArrayType::new(&generator, &ctx, llvm_i32.into());
-    assert!(NDArrayType::is_type(llvm_ndarray.as_base_type(), llvm_usize).is_ok());
-}
--- a/nac3core/src/lib.rs
+++ b/nac3core/src/lib.rs
@ -19,10 +19,6 @@
    clippy::wildcard_imports
 )]

-// users of nac3core need to use the same version of these dependencies, so expose them as nac3core::*
-pub use inkwell;
-pub use nac3parser;
-
 pub mod codegen;
 pub mod symbol_resolver;
 pub mod toplevel;
--- a/nac3core/src/symbol_resolver.rs
+++ b/nac3core/src/symbol_resolver.rs
@ -1,15 +1,7 @@
-use std::{
-    collections::{HashMap, HashSet},
-    fmt::{Debug, Display},
-    rc::Rc,
-    sync::Arc,
-};
-
-use inkwell::values::{BasicValueEnum, FloatValue, IntValue, PointerValue, StructValue};
-use itertools::{chain, izip, Itertools};
-use parking_lot::RwLock;
-
-use nac3parser::ast::{Constant, Expr, Location, StrRef};
+use std::fmt::Debug;
+use std::rc::Rc;
+use std::sync::Arc;
+use std::{collections::HashMap, collections::HashSet, fmt::Display};

 use crate::{
    codegen::{CodeGenContext, CodeGenerator},
@ -19,6 +11,10 @@ use crate::{
        typedef::{Type, TypeEnum, Unifier, VarMap},
    },
 };
+use inkwell::values::{BasicValueEnum, FloatValue, IntValue, PointerValue, StructValue};
+use itertools::{chain, izip, Itertools};
+use nac3parser::ast::{Constant, Expr, Location, StrRef};
+use parking_lot::RwLock;

 #[derive(Clone, PartialEq, Debug)]
 pub enum SymbolValue {
@ -369,7 +365,6 @@ pub trait SymbolResolver {
        &self,
        str: StrRef,
        ctx: &mut CodeGenContext<'ctx, '_>,
-        generator: &mut dyn CodeGenerator,
    ) -> Option<ValueEnum<'ctx>>;

    fn get_default_param_value(&self, expr: &Expr) -> Option<SymbolValue>;
--- a/nac3core/src/toplevel/builtins.rs
+++ b/nac3core/src/toplevel/builtins.rs
@ -1,5 +1,6 @@
 use std::iter::once;

+use helper::{debug_assert_prim_is_allowed, extract_ndims, make_exception_fields, PrimDefDetails};
 use indexmap::IndexMap;
 use inkwell::{
    attributes::{Attribute, AttributeLoc},
@ -8,24 +9,28 @@ use inkwell::{
    IntPredicate,
 };
 use itertools::Either;
+use numpy::unpack_ndarray_var_tys;
 use strum::IntoEnumIterator;

-use super::{
-    helper::{debug_assert_prim_is_allowed, make_exception_fields, PrimDef, PrimDefDetails},
-    numpy::make_ndarray_ty,
-    *,
-};
 use crate::{
    codegen::{
        builtin_fns,
-        classes::{ProxyValue, RangeValue},
+        model::*,
        numpy::*,
+        object::{
+            any::AnyObject,
+            ndarray::{shape_util::parse_numpy_int_sequence, NDArrayObject},
+            range::RangeObject,
+        },
        stmt::exn_constructor,
    },
    symbol_resolver::SymbolValue,
+    toplevel::{helper::PrimDef, numpy::make_ndarray_ty},
    typecheck::typedef::{into_var_map, iter_type_vars, TypeVar, VarMap},
 };

+use super::*;
+
 type BuiltinInfo = Vec<(Arc<RwLock<TopLevelDef>>, Option<Stmt>)>;

 pub fn get_exn_constructor(
@ -512,6 +517,14 @@ impl<'a> BuiltinBuilder<'a> {
            | PrimDef::FunNpEye
            | PrimDef::FunNpIdentity => self.build_ndarray_other_factory_function(prim),

+            PrimDef::FunNpSize | PrimDef::FunNpShape | PrimDef::FunNpStrides => {
+                self.build_ndarray_property_getter_function(prim)
+            }
+
+            PrimDef::FunNpBroadcastTo | PrimDef::FunNpTranspose | PrimDef::FunNpReshape => {
+                self.build_ndarray_view_function(prim)
+            }
+
            PrimDef::FunStr => self.build_str_function(),

            PrimDef::FunFloor | PrimDef::FunFloor64 | PrimDef::FunCeil | PrimDef::FunCeil64 => {
@ -577,10 +590,6 @@ impl<'a> BuiltinBuilder<'a> {
            | PrimDef::FunNpHypot
            | PrimDef::FunNpNextAfter => self.build_np_2ary_function(prim),

-            PrimDef::FunNpTranspose | PrimDef::FunNpReshape => {
-                self.build_np_sp_ndarray_function(prim)
-            }
-
            PrimDef::FunNpDot
            | PrimDef::FunNpLinalgCholesky
            | PrimDef::FunNpLinalgQr
@ -708,9 +717,10 @@ impl<'a> BuiltinBuilder<'a> {
                codegen_callback: Some(Arc::new(GenCall::new(Box::new(
                    |ctx, obj, _, args, generator| {
                        let (zelf_ty, zelf) = obj.unwrap();
-                        let zelf =
-                            zelf.to_basic_value_enum(ctx, generator, zelf_ty)?.into_pointer_value();
-                        let zelf = RangeValue::from_ptr_val(zelf, Some("range"));
+                        let zelf = zelf.to_basic_value_enum(ctx, generator, zelf_ty)?;
+
+                        let zelf = AnyObject { ty: zelf_ty, value: zelf };
+                        let zelf = RangeObject::from_object(generator, ctx, zelf);

                        let mut start = None;
                        let mut stop = None;
@ -793,11 +803,14 @@ impl<'a> BuiltinBuilder<'a> {
                        });
                        let start = start.unwrap_or_else(|| int32.const_zero());

-                        zelf.store_start(ctx, start);
-                        zelf.store_end(ctx, stop);
-                        zelf.store_step(ctx, step);
+                        let start = Int(Int32).believe_value(start);
+                        let stop = Int(Int32).believe_value(stop);
+                        let step = Int(Int32).believe_value(step);
+                        zelf.instance.start(ctx).store(ctx, start);
+                        zelf.instance.stop(ctx).store(ctx, stop);
+                        zelf.instance.step(ctx).store(ctx, step);

-                        Ok(Some(zelf.as_base_value().into()))
+                        Ok(Some(zelf.instance.value.as_basic_value_enum()))
                    },
                )))),
                loc: None,
@ -1386,6 +1399,169 @@ impl<'a> BuiltinBuilder<'a> {
        }
    }

+    fn build_ndarray_property_getter_function(&mut self, prim: PrimDef) -> TopLevelDef {
+        debug_assert_prim_is_allowed(
+            prim,
+            &[PrimDef::FunNpSize, PrimDef::FunNpShape, PrimDef::FunNpStrides],
+        );
+
+        let mut var_map = self.num_var_map.clone();
+        var_map.insert(self.ndarray_dtype_tvar.id, self.ndarray_dtype_tvar.ty);
+
+        let in_ndarray_ty = self.unifier.get_fresh_var_with_range(
+            &[self.primitives.ndarray],
+            Some("T".into()),
+            None,
+        );
+
+        match prim {
+            PrimDef::FunNpSize => create_fn_by_codegen(
+                self.unifier,
+                &VarMap::new(),
+                prim.name(),
+                self.primitives.int32,
+                &[(in_ndarray_ty.ty, "a")],
+                Box::new(|ctx, obj, fun, args, generator| {
+                    assert!(obj.is_none());
+                    assert_eq!(args.len(), 1);
+
+                    let ndarray_ty = fun.0.args[0].ty;
+                    let ndarray =
+                        args[0].1.clone().to_basic_value_enum(ctx, generator, ndarray_ty)?;
+                    let ndarray = AnyObject { ty: ndarray_ty, value: ndarray };
+                    let ndarray = NDArrayObject::from_object(generator, ctx, ndarray);
+
+                    let size = ndarray.size(generator, ctx).truncate(generator, ctx, Int32);
+                    Ok(Some(size.value.as_basic_value_enum()))
+                }),
+            ),
+            PrimDef::FunNpShape | PrimDef::FunNpStrides => {
+                // The fnuction signatures of `np_shape` an `np_size` are the same.
+
+                // The return type is a tuple of variable length depending on the ndims of the input ndarray.
+                let ret_ty = self.unifier.get_dummy_var().ty; // Handled by special folding
+
+                create_fn_by_codegen(
+                    self.unifier,
+                    &VarMap::new(),
+                    prim.name(),
+                    ret_ty,
+                    &[(in_ndarray_ty.ty, "a")],
+                    Box::new(move |ctx, obj, fun, args, generator| {
+                        assert!(obj.is_none());
+                        assert_eq!(args.len(), 1);
+
+                        let ndarray_ty = fun.0.args[0].ty;
+                        let ndarray =
+                            args[0].1.clone().to_basic_value_enum(ctx, generator, ndarray_ty)?;
+
+                        let ndarray = AnyObject { ty: ndarray_ty, value: ndarray };
+                        let ndarray = NDArrayObject::from_object(generator, ctx, ndarray);
+
+                        let result_tuple = match prim {
+                            PrimDef::FunNpShape => ndarray.make_shape_tuple(generator, ctx),
+                            PrimDef::FunNpStrides => ndarray.make_strides_tuple(generator, ctx),
+                            _ => unreachable!(),
+                        };
+
+                        Ok(Some(result_tuple.value.as_basic_value_enum()))
+                    }),
+                )
+            }
+            _ => unreachable!(),
+        }
+    }
+
+    /// Build np/sp functions that take as input `NDArray` only
+    fn build_ndarray_view_function(&mut self, prim: PrimDef) -> TopLevelDef {
+        debug_assert_prim_is_allowed(
+            prim,
+            &[PrimDef::FunNpBroadcastTo, PrimDef::FunNpTranspose, PrimDef::FunNpReshape],
+        );
+
+        let in_ndarray_ty = self.unifier.get_fresh_var_with_range(
+            &[self.primitives.ndarray],
+            Some("T".into()),
+            None,
+        );
+
+        match prim {
+            PrimDef::FunNpTranspose => {
+                create_fn_by_codegen(
+                    self.unifier,
+                    &VarMap::new(),
+                    prim.name(),
+                    in_ndarray_ty.ty,
+                    &[(in_ndarray_ty.ty, "x")],
+                    Box::new(move |ctx, _, fun, args, generator| {
+                        let arg_ty = fun.0.args[0].ty;
+                        let arg_val =
+                            args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
+
+                        let arg = AnyObject { ty: arg_ty, value: arg_val };
+                        let ndarray = NDArrayObject::from_object(generator, ctx, arg);
+
+                        let ndarray = ndarray.transpose(generator, ctx, None); // TODO: Add axes argument
+                        Ok(Some(ndarray.instance.value.as_basic_value_enum()))
+                    }),
+                )
+            }
+
+            // NOTE: on `ndarray_factory_fn_shape_arg_tvar` and
+            // the `param_ty` for `create_fn_by_codegen`.
+            //
+            // Similar to `build_ndarray_from_shape_factory_function` we delegate the responsibility of typechecking
+            // to [`typecheck::type_inferencer::Inferencer::fold_numpy_function_call_shape_argument`],
+            // and use a dummy [`TypeVar`] `ndarray_factory_fn_shape_arg_tvar` as a placeholder for `param_ty`.
+            PrimDef::FunNpBroadcastTo | PrimDef::FunNpReshape => {
+                let ret_ty = self.unifier.get_dummy_var().ty; // Handled by special holding
+
+                create_fn_by_codegen(
+                    self.unifier,
+                    &VarMap::new(),
+                    prim.name(),
+                    ret_ty,
+                    &[
+                        (in_ndarray_ty.ty, "x"),
+                        (self.ndarray_factory_fn_shape_arg_tvar.ty, "shape"), // Handled by special folding
+                    ],
+                    Box::new(move |ctx, _, fun, args, generator| {
+                        let ndarray_ty = fun.0.args[0].ty;
+                        let ndarray_val =
+                            args[0].1.clone().to_basic_value_enum(ctx, generator, ndarray_ty)?;
+
+                        let shape_ty = fun.0.args[1].ty;
+                        let shape_val =
+                            args[1].1.clone().to_basic_value_enum(ctx, generator, shape_ty)?;
+
+                        let ndarray = AnyObject { value: ndarray_val, ty: ndarray_ty };
+                        let ndarray = NDArrayObject::from_object(generator, ctx, ndarray);
+
+                        let shape = AnyObject { value: shape_val, ty: shape_ty };
+                        let (_, shape) = parse_numpy_int_sequence(generator, ctx, shape);
+
+                        // The ndims after reshaping is gotten from the return type of the call.
+                        let (_, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, fun.0.ret);
+                        let ndims = extract_ndims(&ctx.unifier, ndims);
+
+                        let new_ndarray = match prim {
+                            PrimDef::FunNpBroadcastTo => {
+                                ndarray.broadcast_to(generator, ctx, ndims, shape)
+                            }
+                            PrimDef::FunNpReshape => {
+                                ndarray.reshape_or_copy(generator, ctx, ndims, shape)
+                            }
+                            _ => unreachable!(),
+                        };
+                        Ok(Some(new_ndarray.instance.value.as_basic_value_enum()))
+                    }),
+                )
+            }
+
+            _ => unreachable!(),
+        }
+    }
+
    /// Build the `str()` function.
    fn build_str_function(&mut self) -> TopLevelDef {
        let prim = PrimDef::FunStr;
@ -1873,57 +2049,6 @@ impl<'a> BuiltinBuilder<'a> {
        }
    }

-    /// Build np/sp functions that take as input `NDArray` only
-    fn build_np_sp_ndarray_function(&mut self, prim: PrimDef) -> TopLevelDef {
-        debug_assert_prim_is_allowed(prim, &[PrimDef::FunNpTranspose, PrimDef::FunNpReshape]);
-
-        match prim {
-            PrimDef::FunNpTranspose => {
-                let ndarray_ty = self.unifier.get_fresh_var_with_range(
-                    &[self.ndarray_num_ty],
-                    Some("T".into()),
-                    None,
-                );
-                create_fn_by_codegen(
-                    self.unifier,
-                    &into_var_map([ndarray_ty]),
-                    prim.name(),
-                    ndarray_ty.ty,
-                    &[(ndarray_ty.ty, "x")],
-                    Box::new(move |ctx, _, fun, args, generator| {
-                        let arg_ty = fun.0.args[0].ty;
-                        let arg_val =
-                            args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
-                        Ok(Some(ndarray_transpose(generator, ctx, (arg_ty, arg_val))?))
-                    }),
-                )
-            }
-
-            // NOTE: on `ndarray_factory_fn_shape_arg_tvar` and
-            // the `param_ty` for `create_fn_by_codegen`.
-            //
-            // Similar to `build_ndarray_from_shape_factory_function` we delegate the responsibility of typechecking
-            // to [`typecheck::type_inferencer::Inferencer::fold_numpy_function_call_shape_argument`],
-            // and use a dummy [`TypeVar`] `ndarray_factory_fn_shape_arg_tvar` as a placeholder for `param_ty`.
-            PrimDef::FunNpReshape => create_fn_by_codegen(
-                self.unifier,
-                &VarMap::new(),
-                prim.name(),
-                self.ndarray_num_ty,
-                &[(self.ndarray_num_ty, "x"), (self.ndarray_factory_fn_shape_arg_tvar.ty, "shape")],
-                Box::new(move |ctx, _, fun, args, generator| {
-                    let x1_ty = fun.0.args[0].ty;
-                    let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
-                    let x2_ty = fun.0.args[1].ty;
-                    let x2_val = args[1].1.clone().to_basic_value_enum(ctx, generator, x2_ty)?;
-                    Ok(Some(ndarray_reshape(generator, ctx, (x1_ty, x1_val), (x2_ty, x2_val))?))
-                }),
-            ),
-
-            _ => unreachable!(),
-        }
-    }
-
    /// Build `np_linalg` and `sp_linalg` functions
    ///
    /// The input to these functions must be floating point `NDArray`
@ -1955,10 +2080,12 @@ impl<'a> BuiltinBuilder<'a> {
                Box::new(move |ctx, _, fun, args, generator| {
                    let x1_ty = fun.0.args[0].ty;
                    let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
+
                    let x2_ty = fun.0.args[1].ty;
                    let x2_val = args[1].1.clone().to_basic_value_enum(ctx, generator, x2_ty)?;

-                    Ok(Some(ndarray_dot(generator, ctx, (x1_ty, x1_val), (x2_ty, x2_val))?))
+                    let result = ndarray_dot(generator, ctx, (x1_ty, x1_val), (x2_ty, x2_val))?;
+                    Ok(Some(result))
                }),
            ),

--- a/nac3core/src/toplevel/composer.rs
+++ b/nac3core/src/toplevel/composer.rs
@ -1,17 +1,17 @@
+use nac3parser::ast::fold::Fold;
 use std::rc::Rc;

-use nac3parser::ast::{fold::Fold, ExprKind, Ident};
-
-use super::*;
 use crate::{
    codegen::{expr::get_subst_key, stmt::exn_constructor},
    symbol_resolver::SymbolValue,
    typecheck::{
-        type_inferencer::{FunctionData, IdentifierInfo, Inferencer},
+        type_inferencer::{FunctionData, Inferencer},
        typedef::{TypeVar, VarMap},
    },
 };

+use super::*;
+
 pub struct ComposerConfig {
    pub kernel_ann: Option<&'static str>,
    pub kernel_invariant_ann: &'static str,
@ -23,7 +23,7 @@ impl Default for ComposerConfig {
    }
 }

-pub type DefAst = (Arc<RwLock<TopLevelDef>>, Option<Stmt<()>>);
+type DefAst = (Arc<RwLock<TopLevelDef>>, Option<Stmt<()>>);
 pub struct TopLevelComposer {
    // list of top level definitions, same as top level context
    pub definition_ast_list: Vec<DefAst>,
@ -101,8 +101,7 @@ impl TopLevelComposer {
            .iter()
            .map(|def_ast| match *def_ast.0.read() {
                TopLevelDef::Class { name, .. } => name.to_string(),
-                TopLevelDef::Function { simple_name, .. }
-                | TopLevelDef::Variable { simple_name, .. } => simple_name.to_string(),
+                TopLevelDef::Function { simple_name, .. } => simple_name.to_string(),
            })
            .collect_vec();

@ -382,87 +381,13 @@ impl TopLevelComposer {
                ))
            }

-            ast::StmtKind::Assign { .. } => {
-                // Assignment statements can assign to (and therefore create) more than one 
-                // variable, but this function only allows returning one set of symbol information.
-                // We want to avoid changing this to return a `Vec` of symbol info, as this would 
-                // require `iter().next().unwrap()` on every variable created from a non-Assign 
-                // statement.
-                //
-                // Make callers use `register_top_level_var` instead, as it provides more
-                // fine-grained control over which symbols to register, while also simplifying the
-                // usage of this function.
-                panic!("Registration of top-level Assign statements must use TopLevelComposer::register_top_level_var (at {})", ast.location);
-            }
-
-            ast::StmtKind::AnnAssign { target, annotation, .. } => {
-                let ExprKind::Name { id: name, .. } = target.node else {
-                    return Err(format!(
-                        "global variable declaration must be an identifier (at {})",
-                        target.location
-                    ));
-                };
-
-                self.register_top_level_var(
-                    name,
-                    Some(annotation.as_ref().clone()),
-                    resolver,
-                    mod_path,
-                    target.location,
-                )
-            }
-
            _ => Err(format!(
-                "registrations of constructs other than top level classes/functions/variables are not supported (at {})",
+                "registrations of constructs other than top level classes/functions are not supported (at {})",
                ast.location
            )),
        }
    }

-    /// Registers a top-level variable with the given `name` into the composer.
-    ///
-    /// `annotation` - The type annotation of the top-level variable, or [`None`] if no type
-    /// annotation is provided.
-    /// `location` - The location of the top-level variable.
-    pub fn register_top_level_var(
-        &mut self,
-        name: Ident,
-        annotation: Option<Expr>,
-        resolver: Option<Arc<dyn SymbolResolver + Send + Sync>>,
-        mod_path: &str,
-        location: Location,
-    ) -> Result<(StrRef, DefinitionId, Option<Type>), String> {
-        if self.keyword_list.contains(&name) {
-            return Err(format!("cannot use keyword `{name}` as a class name (at {location})"));
-        }
-
-        let global_var_name =
-            if mod_path.is_empty() { name.to_string() } else { format!("{mod_path}.{name}") };
-
-        if !self.defined_names.insert(global_var_name.clone()) {
-            return Err(format!(
-                "global variable `{global_var_name}` defined twice (at {location})"
-            ));
-        }
-
-        let ty_to_be_unified = self.unifier.get_dummy_var().ty;
-        self.definition_ast_list.push((
-            RwLock::new(Self::make_top_level_variable_def(
-                global_var_name,
-                name,
-                // dummy here, unify with correct type later,
-                ty_to_be_unified,
-                annotation,
-                resolver,
-                Some(location),
-            ))
-            .into(),
-            None,
-        ));
-
-        Ok((name, DefinitionId(self.definition_ast_list.len() - 1), Some(ty_to_be_unified)))
-    }
-
    pub fn start_analysis(&mut self, inference: bool) -> Result<(), HashSet<String>> {
        self.analyze_top_level_class_type_var()?;
        self.analyze_top_level_class_bases()?;
@ -471,7 +396,6 @@ impl TopLevelComposer {
        if inference {
            self.analyze_function_instance()?;
        }
-        self.analyze_top_level_variables()?;
        Ok(())
    }

@ -509,7 +433,7 @@ impl TopLevelComposer {
                    // things like `class A(Generic[T, V, ImportedModule.T])` is not supported
                    // i.e. only simple names are allowed in the subscript
                    // should update the TopLevelDef::Class.typevars and the TypeEnum::TObj.params
-                    ExprKind::Subscript { value, slice, .. }
+                    ast::ExprKind::Subscript { value, slice, .. }
                        if {
                            matches!(
                                &value.node,
@ -525,9 +449,9 @@ impl TopLevelComposer {
                        }
                        is_generic = true;

-                        let type_var_list: Vec<&Expr<()>>;
+                        let type_var_list: Vec<&ast::Expr<()>>;
                        // if `class A(Generic[T, V, G])`
-                        if let ExprKind::Tuple { elts, .. } = &slice.node {
+                        if let ast::ExprKind::Tuple { elts, .. } = &slice.node {
                            type_var_list = elts.iter().collect_vec();
                        // `class A(Generic[T])`
                        } else {
@ -576,7 +500,6 @@ impl TopLevelComposer {
            }
            Ok(())
        };
-
        let mut errors = HashSet::new();
        for (class_def, class_ast) in def_list.iter().skip(self.builtin_num) {
            if class_ast.is_none() {
@ -930,6 +853,7 @@ impl TopLevelComposer {
        let unifier = self.unifier.borrow_mut();
        let primitives_store = &self.primitives_ty;

+        let mut errors = HashSet::new();
        let mut analyze = |function_def: &Arc<RwLock<TopLevelDef>>, function_ast: &Option<Stmt>| {
            let mut function_def = function_def.write();
            let function_def = &mut *function_def;
@ -1038,18 +962,18 @@ impl TopLevelComposer {
                    }
                }

-                let arg_with_default: Vec<(&ast::Located<ast::ArgData<()>>, Option<&Expr>)> = args
-                    .args
-                    .iter()
-                    .rev()
-                    .zip(
-                        args.defaults
-                            .iter()
-                            .rev()
-                            .map(|x| -> Option<&Expr> { Some(x) })
-                            .chain(std::iter::repeat(None)),
-                    )
-                    .collect_vec();
+                let arg_with_default: Vec<(&ast::Located<ast::ArgData<()>>, Option<&ast::Expr>)> =
+                    args.args
+                        .iter()
+                        .rev()
+                        .zip(
+                            args.defaults
+                                .iter()
+                                .rev()
+                                .map(|x| -> Option<&ast::Expr> { Some(x) })
+                                .chain(std::iter::repeat(None)),
+                        )
+                        .collect_vec();

                arg_with_default
                    .iter()
@ -1204,8 +1128,6 @@ impl TopLevelComposer {
            })?;
            Ok(())
        };
-
-        let mut errors = HashSet::new();
        for (function_def, function_ast) in def_list.iter().skip(self.builtin_num) {
            if function_ast.is_none() {
                continue;
@ -1307,7 +1229,7 @@ impl TopLevelComposer {

                        let arg_with_default: Vec<(
                            &ast::Located<ast::ArgData<()>>,
-                            Option<&Expr>,
+                            Option<&ast::Expr>,
                        )> = args
                            .args
                            .iter()
@ -1316,7 +1238,7 @@ impl TopLevelComposer {
                                args.defaults
                                    .iter()
                                    .rev()
-                                    .map(|x| -> Option<&Expr> { Some(x) })
+                                    .map(|x| -> Option<&ast::Expr> { Some(x) })
                                    .chain(std::iter::repeat(None)),
                            )
                            .collect_vec();
@ -1473,7 +1395,7 @@ impl TopLevelComposer {
                        .map_err(|e| HashSet::from([e.to_display(unifier).to_string()]))?;
                }
                ast::StmtKind::AnnAssign { target, annotation, value, .. } => {
-                    if let ExprKind::Name { id: attr, .. } = &target.node {
+                    if let ast::ExprKind::Name { id: attr, .. } = &target.node {
                        if defined_fields.insert(attr.to_string()) {
                            let dummy_field_type = unifier.get_dummy_var().ty;

@ -1481,7 +1403,7 @@ impl TopLevelComposer {
                                None => {
                                    // handle Kernel[T], KernelInvariant[T]
                                    let (annotation, mutable) = match &annotation.node {
-                                        ExprKind::Subscript { value, slice, .. }
+                                        ast::ExprKind::Subscript { value, slice, .. }
                                            if matches!(
                                                &value.node,
                                                ast::ExprKind::Name { id, .. } if id == &core_config.kernel_invariant_ann.into()
@ -1489,7 +1411,7 @@ impl TopLevelComposer {
                                        {
                                            (slice, false)
                                        }
-                                        ExprKind::Subscript { value, slice, .. }
+                                        ast::ExprKind::Subscript { value, slice, .. }
                                            if matches!(
                                                &value.node,
                                                ast::ExprKind::Name { id, .. } if core_config.kernel_ann.map_or(false, |c| id == &c.into())
@ -1507,13 +1429,13 @@ impl TopLevelComposer {
                                Some(boxed_expr) => {
                                    // Class attributes are set as immutable regardless
                                    let (annotation, _) = match &annotation.node {
-                                        ExprKind::Subscript { slice, .. } => (slice, false),
+                                        ast::ExprKind::Subscript { slice, .. } => (slice, false),
                                        _ if core_config.kernel_ann.is_none() => (annotation, false),
                                        _ => continue,
                                    };

                                    match &**boxed_expr {
-                                        ast::Located {location: _, custom: (), node: ExprKind::Constant { value: v, kind: _ }} => {
+                                        ast::Located {location: _, custom: (), node: ast::ExprKind::Constant { value: v, kind: _ }} => {
                                            // Restricting the types allowed to be defined as class attributes
                                            match v {
                                                ast::Constant::Bool(_) | ast::Constant::Str(_) | ast::Constant::Int(_) | ast::Constant::Float(_) => {}
@ -1780,6 +1702,7 @@ impl TopLevelComposer {
            }
        }

+        let mut errors = HashSet::new();
        let mut analyze = |i, def: &Arc<RwLock<TopLevelDef>>, ast: &Option<Stmt>| {
            let class_def = def.read();
            if let TopLevelDef::Class {
@ -1899,12 +1822,7 @@ impl TopLevelComposer {
                        if *name != init_str_id {
                            unreachable!("must be init function here")
                        }
-
-                        let all_inited = Self::get_all_assigned_field(
-                            object_id.0,
-                            definition_ast_list,
-                            body.as_slice(),
-                        )?;
+                        let all_inited = Self::get_all_assigned_field(body.as_slice())?;
                        for (f, _, _) in fields {
                            if !all_inited.contains(f) {
                                return Err(HashSet::from([
@ -1922,8 +1840,6 @@ impl TopLevelComposer {
            }
            Ok(())
        };
-
-        let mut errors = HashSet::new();
        for (i, (def, ast)) in definition_ast_list.iter().enumerate().skip(self.builtin_num) {
            if ast.is_none() {
                continue;
@ -1961,296 +1877,272 @@ impl TopLevelComposer {
            if ast.is_none() {
                return Ok(());
            }
-
-            let (name, simple_name, signature, resolver) = {
-                let function_def = def.read();
-                let TopLevelDef::Function { name, simple_name, signature, resolver, .. } =
-                    &*function_def
+            let mut function_def = def.write();
+            if let TopLevelDef::Function {
+                instance_to_stmt,
+                instance_to_symbol,
+                name,
+                simple_name,
+                signature,
+                resolver,
+                ..
+            } = &mut *function_def
+            {
+                let signature_ty_enum = unifier.get_ty(*signature);
+                let TypeEnum::TFunc(FunSignature { args, ret, vars }) = signature_ty_enum.as_ref()
                else {
-                    return Ok(());
+                    unreachable!("must be typeenum::tfunc")
                };

-                (name.clone(), *simple_name, *signature, resolver.clone())
-            };
+                let mut vars = vars.clone();
+                // None if is not class method
+                let uninst_self_type = {
+                    if let Some(class_id) = method_class.get(&DefinitionId(id)) {
+                        let class_def = definition_ast_list.get(class_id.0).unwrap();
+                        let class_def = class_def.0.read();
+                        let TopLevelDef::Class { type_vars, .. } = &*class_def else {
+                            unreachable!("must be class def")
+                        };

-            let signature_ty_enum = unifier.get_ty(signature);
-            let TypeEnum::TFunc(FunSignature { args, ret, vars, .. }) = signature_ty_enum.as_ref()
-            else {
-                unreachable!("must be typeenum::tfunc")
-            };
+                        let ty_ann = make_self_type_annotation(type_vars, *class_id);
+                        let self_ty = get_type_from_type_annotation_kinds(
+                            &def_list,
+                            unifier,
+                            primitives_ty,
+                            &ty_ann,
+                            &mut None,
+                        )?;
+                        vars.extend(type_vars.iter().map(|ty| {
+                            let TypeEnum::TVar { id, .. } = &*unifier.get_ty(*ty) else {
+                                unreachable!()
+                            };

-            let mut vars = vars.clone();
-            // None if is not class method
-            let uninst_self_type = {
-                if let Some(class_id) = method_class.get(&DefinitionId(id)) {
-                    let class_def = definition_ast_list.get(class_id.0).unwrap();
-                    let class_def = class_def.0.read();
-                    let TopLevelDef::Class { type_vars, .. } = &*class_def else {
-                        unreachable!("must be class def")
+                            (*id, *ty)
+                        }));
+                        Some((self_ty, type_vars.clone()))
+                    } else {
+                        None
+                    }
+                };
+                // carefully handle those with bounds, without bounds and no typevars
+                // if class methods, `vars` also contains all class typevars here
+                let (type_var_subst_comb, no_range_vars) = {
+                    let mut no_ranges: Vec<Type> = Vec::new();
+                    let var_combs = vars
+                        .values()
+                        .map(|ty| {
+                            unifier.get_instantiations(*ty).unwrap_or_else(|| {
+                                let TypeEnum::TVar { name, loc, is_const_generic: false, .. } =
+                                    &*unifier.get_ty(*ty)
+                                else {
+                                    unreachable!()
+                                };
+
+                                let rigid = unifier.get_fresh_rigid_var(*name, *loc).ty;
+                                no_ranges.push(rigid);
+                                vec![rigid]
+                            })
+                        })
+                        .multi_cartesian_product()
+                        .collect_vec();
+                    let mut result: Vec<VarMap> = Vec::default();
+                    for comb in var_combs {
+                        result.push(vars.keys().copied().zip(comb).collect());
+                    }
+                    // NOTE: if is empty, means no type var, append a empty subst, ok to do this?
+                    if result.is_empty() {
+                        result.push(VarMap::new());
+                    }
+                    (result, no_ranges)
+                };
+
+                for subst in type_var_subst_comb {
+                    // for each instance
+                    let inst_ret = unifier.subst(*ret, &subst).unwrap_or(*ret);
+                    let inst_args = {
+                        args.iter()
+                            .map(|a| FuncArg {
+                                name: a.name,
+                                ty: unifier.subst(a.ty, &subst).unwrap_or(a.ty),
+                                default_value: a.default_value.clone(),
+                                is_vararg: false,
+                            })
+                            .collect_vec()
+                    };
+                    let self_type = {
+                        uninst_self_type.clone().map(|(self_type, type_vars)| {
+                            let subst_for_self = {
+                                let class_ty_var_ids = type_vars
+                                    .iter()
+                                    .map(|x| {
+                                        if let TypeEnum::TVar { id, .. } = &*unifier.get_ty(*x) {
+                                            *id
+                                        } else {
+                                            unreachable!("must be type var here");
+                                        }
+                                    })
+                                    .collect::<HashSet<_>>();
+                                subst
+                                    .iter()
+                                    .filter_map(|(ty_var_id, ty_var_target)| {
+                                        if class_ty_var_ids.contains(ty_var_id) {
+                                            Some((*ty_var_id, *ty_var_target))
+                                        } else {
+                                            None
+                                        }
+                                    })
+                                    .collect::<VarMap>()
+                            };
+                            unifier.subst(self_type, &subst_for_self).unwrap_or(self_type)
+                        })
+                    };
+                    let mut identifiers = {
+                        let mut result: HashSet<_> = HashSet::new();
+                        if self_type.is_some() {
+                            result.insert("self".into());
+                        }
+                        result.extend(inst_args.iter().map(|x| x.name));
+                        result
+                    };
+                    let mut calls: HashMap<CodeLocation, CallId> = HashMap::new();
+                    let mut inferencer = Inferencer {
+                        top_level: ctx.as_ref(),
+                        defined_identifiers: identifiers.clone(),
+                        function_data: &mut FunctionData {
+                            resolver: resolver.as_ref().unwrap().clone(),
+                            return_type: if unifier.unioned(inst_ret, primitives_ty.none) {
+                                None
+                            } else {
+                                Some(inst_ret)
+                            },
+                            // NOTE: allowed type vars
+                            bound_variables: no_range_vars.clone(),
+                        },
+                        unifier,
+                        variable_mapping: {
+                            let mut result: HashMap<StrRef, Type> = HashMap::new();
+                            if let Some(self_ty) = self_type {
+                                result.insert("self".into(), self_ty);
+                            }
+                            result.extend(inst_args.iter().map(|x| (x.name, x.ty)));
+                            result
+                        },
+                        primitives: primitives_ty,
+                        virtual_checks: &mut Vec::new(),
+                        calls: &mut calls,
+                        in_handler: false,
                    };

-                    let ty_ann = make_self_type_annotation(type_vars, *class_id);
-                    let self_ty = get_type_from_type_annotation_kinds(
-                        &def_list,
-                        unifier,
-                        primitives_ty,
-                        &ty_ann,
-                        &mut None,
-                    )?;
-                    vars.extend(type_vars.iter().map(|ty| {
-                        let TypeEnum::TVar { id, .. } = &*unifier.get_ty(*ty) else {
-                            unreachable!()
-                        };
-
-                        (*id, *ty)
-                    }));
-                    Some((self_ty, type_vars.clone()))
-                } else {
-                    None
-                }
-            };
-            // carefully handle those with bounds, without bounds and no typevars
-            // if class methods, `vars` also contains all class typevars here
-            let (type_var_subst_comb, no_range_vars) = {
-                let mut no_ranges: Vec<Type> = Vec::new();
-                let var_combs = vars
-                    .values()
-                    .map(|ty| {
-                        unifier.get_instantiations(*ty).unwrap_or_else(|| {
-                            let TypeEnum::TVar { name, loc, is_const_generic: false, .. } =
-                                &*unifier.get_ty(*ty)
-                            else {
-                                unreachable!()
-                            };
-
-                            let rigid = unifier.get_fresh_rigid_var(*name, *loc).ty;
-                            no_ranges.push(rigid);
-                            vec![rigid]
-                        })
-                    })
-                    .multi_cartesian_product()
-                    .collect_vec();
-                let mut result: Vec<VarMap> = Vec::default();
-                for comb in var_combs {
-                    result.push(vars.keys().copied().zip(comb).collect());
-                }
-                // NOTE: if is empty, means no type var, append a empty subst, ok to do this?
-                if result.is_empty() {
-                    result.push(VarMap::new());
-                }
-                (result, no_ranges)
-            };
-
-            for subst in type_var_subst_comb {
-                // for each instance
-                let inst_ret = unifier.subst(*ret, &subst).unwrap_or(*ret);
-                let inst_args = {
-                    args.iter()
-                        .map(|a| FuncArg {
-                            name: a.name,
-                            ty: unifier.subst(a.ty, &subst).unwrap_or(a.ty),
-                            default_value: a.default_value.clone(),
-                            is_vararg: false,
-                        })
-                        .collect_vec()
-                };
-                let self_type = {
-                    uninst_self_type.clone().map(|(self_type, type_vars)| {
-                        let subst_for_self = {
-                            let class_ty_var_ids = type_vars
-                                .iter()
-                                .map(|x| {
-                                    if let TypeEnum::TVar { id, .. } = &*unifier.get_ty(*x) {
-                                        *id
-                                    } else {
-                                        unreachable!("must be type var here");
-                                    }
-                                })
-                                .collect::<HashSet<_>>();
-                            subst
-                                .iter()
-                                .filter_map(|(ty_var_id, ty_var_target)| {
-                                    if class_ty_var_ids.contains(ty_var_id) {
-                                        Some((*ty_var_id, *ty_var_target))
-                                    } else {
-                                        None
-                                    }
-                                })
-                                .collect::<VarMap>()
-                        };
-                        unifier.subst(self_type, &subst_for_self).unwrap_or(self_type)
-                    })
-                };
-                let mut identifiers = {
-                    let mut result = HashMap::new();
-                    if self_type.is_some() {
-                        result.insert("self".into(), IdentifierInfo::default());
-                    }
-                    result.extend(inst_args.iter().map(|x| (x.name, IdentifierInfo::default())));
-                    result
-                };
-                let mut calls: HashMap<CodeLocation, CallId> = HashMap::new();
-                let mut inferencer = Inferencer {
-                    top_level: ctx.as_ref(),
-                    defined_identifiers: identifiers.clone(),
-                    function_data: &mut FunctionData {
-                        resolver: resolver.as_ref().unwrap().clone(),
-                        return_type: if unifier.unioned(inst_ret, primitives_ty.none) {
-                            None
-                        } else {
-                            Some(inst_ret)
-                        },
-                        // NOTE: allowed type vars
-                        bound_variables: no_range_vars.clone(),
-                    },
-                    unifier,
-                    variable_mapping: {
-                        let mut result: HashMap<StrRef, Type> = HashMap::new();
-                        if let Some(self_ty) = self_type {
-                            result.insert("self".into(), self_ty);
-                        }
-                        result.extend(inst_args.iter().map(|x| (x.name, x.ty)));
-                        result
-                    },
-                    primitives: primitives_ty,
-                    virtual_checks: &mut Vec::new(),
-                    calls: &mut calls,
-                    in_handler: false,
-                };
-
-                let ast::StmtKind::FunctionDef { body, decorator_list, .. } =
-                    ast.clone().unwrap().node
-                else {
-                    unreachable!("must be function def ast")
-                };
-
-                if !decorator_list.is_empty() {
-                    if matches!(&decorator_list[0].node, ExprKind::Name { id, .. } if id == &"extern".into())
+                    let ast::StmtKind::FunctionDef { body, decorator_list, .. } =
+                        ast.clone().unwrap().node
+                    else {
+                        unreachable!("must be function def ast")
+                    };
+                    if !decorator_list.is_empty()
+                        && matches!(&decorator_list[0].node,
+                            ast::ExprKind::Name{ id, .. } if id == &"extern".into())
+                    {
+                        instance_to_symbol.insert(String::new(), simple_name.to_string());
+                        continue;
+                    }
+                    if !decorator_list.is_empty()
+                        && matches!(&decorator_list[0].node,
+                            ast::ExprKind::Name{ id, .. } if id == &"rpc".into())
                    {
-                        let TopLevelDef::Function { instance_to_symbol, .. } = &mut *def.write()
-                        else {
-                            unreachable!()
-                        };
                        instance_to_symbol.insert(String::new(), simple_name.to_string());
                        continue;
                    }

-                    if matches!(&decorator_list[0].node, ExprKind::Name { id, .. } if id == &"rpc".into())
-                    {
-                        let TopLevelDef::Function { instance_to_symbol, .. } = &mut *def.write()
-                        else {
-                            unreachable!()
-                        };
-                        instance_to_symbol.insert(String::new(), simple_name.to_string());
-                        continue;
-                    }
-
-                    if let ExprKind::Call { func, .. } = &decorator_list[0].node {
-                        if matches!(&func.node, ExprKind::Name { id, .. } if id == &"rpc".into()) {
-                            let TopLevelDef::Function { instance_to_symbol, .. } =
-                                &mut *def.write()
-                            else {
-                                unreachable!()
-                            };
-                            instance_to_symbol.insert(String::new(), simple_name.to_string());
-                            continue;
-                        }
-                    }
-                }
-
-                let fun_body =
-                    body.into_iter()
+                    let fun_body = body
+                        .into_iter()
                        .map(|b| inferencer.fold_stmt(b))
                        .collect::<Result<Vec<_>, _>>()?;

-                let returned = inferencer.check_block(fun_body.as_slice(), &mut identifiers)?;
-                {
-                    // check virtuals
-                    let defs = ctx.definitions.read();
-                    for (subtype, base, loc) in &*inferencer.virtual_checks {
-                        let base_id = {
-                            let base = inferencer.unifier.get_ty(*base);
-                            if let TypeEnum::TObj { obj_id, .. } = &*base {
-                                *obj_id
-                            } else {
-                                return Err(HashSet::from([format!(
-                                    "Base type should be a class (at {loc})"
-                                )]));
-                            }
-                        };
-                        let subtype_id = {
-                            let ty = inferencer.unifier.get_ty(*subtype);
-                            if let TypeEnum::TObj { obj_id, .. } = &*ty {
-                                *obj_id
-                            } else {
+                    let returned = inferencer.check_block(fun_body.as_slice(), &mut identifiers)?;
+                    {
+                        // check virtuals
+                        let defs = ctx.definitions.read();
+                        for (subtype, base, loc) in &*inferencer.virtual_checks {
+                            let base_id = {
+                                let base = inferencer.unifier.get_ty(*base);
+                                if let TypeEnum::TObj { obj_id, .. } = &*base {
+                                    *obj_id
+                                } else {
+                                    return Err(HashSet::from([format!(
+                                        "Base type should be a class (at {loc})"
+                                    )]));
+                                }
+                            };
+                            let subtype_id = {
+                                let ty = inferencer.unifier.get_ty(*subtype);
+                                if let TypeEnum::TObj { obj_id, .. } = &*ty {
+                                    *obj_id
+                                } else {
+                                    let base_repr = inferencer.unifier.stringify(*base);
+                                    let subtype_repr = inferencer.unifier.stringify(*subtype);
+                                    return Err(HashSet::from([format!(
+                                        "Expected a subtype of {base_repr}, but got {subtype_repr} (at {loc})"),
+                                    ]));
+                                }
+                            };
+                            let subtype_entry = defs[subtype_id.0].read();
+                            let TopLevelDef::Class { ancestors, .. } = &*subtype_entry else {
+                                unreachable!()
+                            };
+
+                            let m = ancestors.iter()
+                                .find(|kind| matches!(kind, TypeAnnotation::CustomClass { id, .. } if *id == base_id));
+                            if m.is_none() {
                                let base_repr = inferencer.unifier.stringify(*base);
                                let subtype_repr = inferencer.unifier.stringify(*subtype);
                                return Err(HashSet::from([format!(
                                    "Expected a subtype of {base_repr}, but got {subtype_repr} (at {loc})"),
                                ]));
                            }
-                        };
-                        let subtype_entry = defs[subtype_id.0].read();
-                        let TopLevelDef::Class { ancestors, .. } = &*subtype_entry else {
-                            unreachable!()
-                        };
-
-                        let m = ancestors.iter()
-                            .find(|kind| matches!(kind, TypeAnnotation::CustomClass { id, .. } if *id == base_id));
-                        if m.is_none() {
-                            let base_repr = inferencer.unifier.stringify(*base);
-                            let subtype_repr = inferencer.unifier.stringify(*subtype);
-                            return Err(HashSet::from([format!(
-                                "Expected a subtype of {base_repr}, but got {subtype_repr} (at {loc})"),
-                            ]));
                        }
                    }
-                }
-                if !unifier.unioned(inst_ret, primitives_ty.none) && !returned {
-                    let def_ast_list = &definition_ast_list;
-                    let ret_str = unifier.internal_stringify(
-                        inst_ret,
-                        &mut |id| {
-                            let TopLevelDef::Class { name, .. } = &*def_ast_list[id].0.read()
-                            else {
-                                unreachable!("must be class id here")
-                            };
+                    if !unifier.unioned(inst_ret, primitives_ty.none) && !returned {
+                        let def_ast_list = &definition_ast_list;
+                        let ret_str = unifier.internal_stringify(
+                            inst_ret,
+                            &mut |id| {
+                                let TopLevelDef::Class { name, .. } = &*def_ast_list[id].0.read()
+                                else {
+                                    unreachable!("must be class id here")
+                                };

-                            name.to_string()
+                                name.to_string()
+                            },
+                            &mut |id| format!("typevar{id}"),
+                            &mut None,
+                        );
+                        return Err(HashSet::from([format!(
+                            "expected return type of `{}` in function `{}` (at {})",
+                            ret_str,
+                            name,
+                            ast.as_ref().unwrap().location
+                        )]));
+                    }
+
+                    instance_to_stmt.insert(
+                        get_subst_key(
+                            unifier,
+                            self_type,
+                            &subst,
+                            Some(&vars.keys().copied().collect()),
+                        ),
+                        FunInstance {
+                            body: Arc::new(fun_body),
+                            unifier_id: 0,
+                            calls: Arc::new(calls),
+                            subst,
                        },
-                        &mut |id| format!("typevar{id}"),
-                        &mut None,
                    );
-                    return Err(HashSet::from([format!(
-                        "expected return type of `{}` in function `{}` (at {})",
-                        ret_str,
-                        name,
-                        ast.as_ref().unwrap().location
-                    )]));
                }
-
-                let TopLevelDef::Function { instance_to_stmt, .. } = &mut *def.write() else {
-                    unreachable!()
-                };
-                instance_to_stmt.insert(
-                    get_subst_key(
-                        unifier,
-                        self_type,
-                        &subst,
-                        Some(&vars.keys().copied().collect()),
-                    ),
-                    FunInstance {
-                        body: Arc::new(fun_body),
-                        unifier_id: 0,
-                        calls: Arc::new(calls),
-                        subst,
-                    },
-                );
            }

            Ok(())
        };
-
        for (id, (def, ast)) in self.definition_ast_list.iter().enumerate().skip(self.builtin_num) {
            if ast.is_none() {
                continue;
@ -2264,59 +2156,4 @@ impl TopLevelComposer {
        }
        Ok(())
    }
-
-    /// Step 6. Analyze and populate the types of global variables.
-    fn analyze_top_level_variables(&mut self) -> Result<(), HashSet<String>> {
-        let def_list = &self.definition_ast_list;
-        let temp_def_list = self.extract_def_list();
-        let unifier = &mut self.unifier;
-        let primitives_store = &self.primitives_ty;
-
-        let mut analyze = |variable_def: &Arc<RwLock<TopLevelDef>>| -> Result<_, HashSet<String>> {
-            let TopLevelDef::Variable { ty: dummy_ty, ty_decl, resolver, loc, .. } =
-                &*variable_def.read()
-            else {
-                // not top level variable def, skip
-                return Ok(());
-            };
-
-            let resolver = &**resolver.as_ref().unwrap();
-
-            if let Some(ty_decl) = ty_decl {
-                let ty_annotation = parse_ast_to_type_annotation_kinds(
-                    resolver,
-                    &temp_def_list,
-                    unifier,
-                    primitives_store,
-                    ty_decl,
-                    HashMap::new(),
-                )?;
-                let ty_from_ty_annotation = get_type_from_type_annotation_kinds(
-                    &temp_def_list,
-                    unifier,
-                    primitives_store,
-                    &ty_annotation,
-                    &mut None,
-                )?;
-
-                unifier.unify(*dummy_ty, ty_from_ty_annotation).map_err(|e| {
-                    HashSet::from([e.at(Some(loc.unwrap())).to_display(unifier).to_string()])
-                })?;
-            }
-
-            Ok(())
-        };
-
-        let mut errors = HashSet::new();
-        for (variable_def, _) in def_list.iter().skip(self.builtin_num) {
-            if let Err(e) = analyze(variable_def) {
-                errors.extend(e);
-            }
-        }
-        if !errors.is_empty() {
-            return Err(errors);
-        }
-
-        Ok(())
-    }
 }
--- a/nac3core/src/toplevel/helper.rs
+++ b/nac3core/src/toplevel/helper.rs
@ -1,15 +1,13 @@
 use std::convert::TryInto;

+use crate::symbol_resolver::SymbolValue;
+use crate::toplevel::numpy::unpack_ndarray_var_tys;
+use crate::typecheck::typedef::{into_var_map, iter_type_vars, Mapping, TypeVarId, VarMap};
+use nac3parser::ast::{Constant, Location};
 use strum::IntoEnumIterator;
 use strum_macros::EnumIter;

-use nac3parser::ast::{Constant, ExprKind, Location};
-
-use super::{numpy::unpack_ndarray_var_tys, *};
-use crate::{
-    symbol_resolver::SymbolValue,
-    typecheck::typedef::{into_var_map, iter_type_vars, Mapping, TypeVarId, VarMap},
-};
+use super::*;

 /// All primitive types and functions in nac3core.
 #[derive(Clone, Copy, Debug, EnumIter, PartialEq, Eq)]
@ -54,6 +52,16 @@ pub enum PrimDef {
    FunNpEye,
    FunNpIdentity,

+    // NumPy ndarray property getters
+    FunNpSize,
+    FunNpShape,
+    FunNpStrides,
+
+    // NumPy ndarray view functions
+    FunNpBroadcastTo,
+    FunNpTranspose,
+    FunNpReshape,
+
    // Miscellaneous NumPy & SciPy functions
    FunNpRound,
    FunNpFloor,
@ -101,8 +109,6 @@ pub enum PrimDef {
    FunNpLdExp,
    FunNpHypot,
    FunNpNextAfter,
-    FunNpTranspose,
-    FunNpReshape,

    // Linalg functions
    FunNpDot,
@ -240,6 +246,16 @@ impl PrimDef {
            PrimDef::FunNpEye => fun("np_eye", None),
            PrimDef::FunNpIdentity => fun("np_identity", None),

+            // NumPy NDArray property getters,
+            PrimDef::FunNpSize => fun("np_size", None),
+            PrimDef::FunNpShape => fun("np_shape", None),
+            PrimDef::FunNpStrides => fun("np_strides", None),
+
+            // NumPy NDArray view functions
+            PrimDef::FunNpBroadcastTo => fun("np_broadcast_to", None),
+            PrimDef::FunNpTranspose => fun("np_transpose", None),
+            PrimDef::FunNpReshape => fun("np_reshape", None),
+
            // Miscellaneous NumPy & SciPy functions
            PrimDef::FunNpRound => fun("np_round", None),
            PrimDef::FunNpFloor => fun("np_floor", None),
@ -287,8 +303,6 @@ impl PrimDef {
            PrimDef::FunNpLdExp => fun("np_ldexp", None),
            PrimDef::FunNpHypot => fun("np_hypot", None),
            PrimDef::FunNpNextAfter => fun("np_nextafter", None),
-            PrimDef::FunNpTranspose => fun("np_transpose", None),
-            PrimDef::FunNpReshape => fun("np_reshape", None),

            // Linalg functions
            PrimDef::FunNpDot => fun("np_dot", None),
@ -389,9 +403,6 @@ impl TopLevelDef {
                    r
                }
            ),
-            TopLevelDef::Variable { name, ty, .. } => {
-                format!("Variable {{ name: {name:?}, ty: {:?} }}", unifier.stringify(*ty),)
-            }
        }
    }
 }
@ -593,18 +604,6 @@ impl TopLevelComposer {
        }
    }

-    #[must_use]
-    pub fn make_top_level_variable_def(
-        name: String,
-        simple_name: StrRef,
-        ty: Type,
-        ty_decl: Option<Expr>,
-        resolver: Option<Arc<dyn SymbolResolver + Send + Sync>>,
-        loc: Option<Location>,
-    ) -> TopLevelDef {
-        TopLevelDef::Variable { name, simple_name, ty, ty_decl, resolver, loc }
-    }
-
    #[must_use]
    pub fn make_class_method_name(mut class_name: String, method_name: &str) -> String {
        class_name.push('.');
@ -750,16 +749,7 @@ impl TopLevelComposer {
        )
    }

-    /// This function returns the fields that have been initialized in the `__init__` function of a class
-    /// The function takes as input:
-    ///  * `class_id`: The `object_id` of the class whose function is being evaluated (check `TopLevelDef::Class`)
-    ///  * `definition_ast_list`: A list of ast definitions and statements defined in `TopLevelComposer`
-    ///  * `stmts`: The body of function being parsed. Each statment is analyzed to check varaible initialization statements
-    pub fn get_all_assigned_field(
-        class_id: usize,
-        definition_ast_list: &Vec<DefAst>,
-        stmts: &[Stmt<()>],
-    ) -> Result<HashSet<StrRef>, HashSet<String>> {
+    pub fn get_all_assigned_field(stmts: &[Stmt<()>]) -> Result<HashSet<StrRef>, HashSet<String>> {
        let mut result = HashSet::new();
        for s in stmts {
            match &s.node {
@ -795,138 +785,30 @@ impl TopLevelComposer {
                // TODO: do not check for For and While?
                ast::StmtKind::For { body, orelse, .. }
                | ast::StmtKind::While { body, orelse, .. } => {
-                    result.extend(Self::get_all_assigned_field(
-                        class_id,
-                        definition_ast_list,
-                        body.as_slice(),
-                    )?);
-                    result.extend(Self::get_all_assigned_field(
-                        class_id,
-                        definition_ast_list,
-                        orelse.as_slice(),
-                    )?);
+                    result.extend(Self::get_all_assigned_field(body.as_slice())?);
+                    result.extend(Self::get_all_assigned_field(orelse.as_slice())?);
                }
                ast::StmtKind::If { body, orelse, .. } => {
-                    let inited_for_sure = Self::get_all_assigned_field(
-                        class_id,
-                        definition_ast_list,
-                        body.as_slice(),
-                    )?
-                    .intersection(&Self::get_all_assigned_field(
-                        class_id,
-                        definition_ast_list,
-                        orelse.as_slice(),
-                    )?)
-                    .copied()
-                    .collect::<HashSet<_>>();
+                    let inited_for_sure = Self::get_all_assigned_field(body.as_slice())?
+                        .intersection(&Self::get_all_assigned_field(orelse.as_slice())?)
+                        .copied()
+                        .collect::<HashSet<_>>();
                    result.extend(inited_for_sure);
                }
                ast::StmtKind::Try { body, orelse, finalbody, .. } => {
-                    let inited_for_sure = Self::get_all_assigned_field(
-                        class_id,
-                        definition_ast_list,
-                        body.as_slice(),
-                    )?
-                    .intersection(&Self::get_all_assigned_field(
-                        class_id,
-                        definition_ast_list,
-                        orelse.as_slice(),
-                    )?)
-                    .copied()
-                    .collect::<HashSet<_>>();
+                    let inited_for_sure = Self::get_all_assigned_field(body.as_slice())?
+                        .intersection(&Self::get_all_assigned_field(orelse.as_slice())?)
+                        .copied()
+                        .collect::<HashSet<_>>();
                    result.extend(inited_for_sure);
-                    result.extend(Self::get_all_assigned_field(
-                        class_id,
-                        definition_ast_list,
-                        finalbody.as_slice(),
-                    )?);
+                    result.extend(Self::get_all_assigned_field(finalbody.as_slice())?);
                }
                ast::StmtKind::With { body, .. } => {
-                    result.extend(Self::get_all_assigned_field(
-                        class_id,
-                        definition_ast_list,
-                        body.as_slice(),
-                    )?);
-                }
-                // Variables Initialized in function calls
-                ast::StmtKind::Expr { value, .. } => {
-                    let ExprKind::Call { func, .. } = &value.node else {
-                        continue;
-                    };
-                    let ExprKind::Attribute { value, attr, .. } = &func.node else {
-                        continue;
-                    };
-                    let ExprKind::Name { id, .. } = &value.node else {
-                        continue;
-                    };
-                    // Need to consider the two cases:
-                    //  Case 1) Call to class function i.e. id = `self`
-                    //  Case 2) Call to class ancestor function i.e. id = ancestor_name
-                    // We leave checking whether function in case 2 belonged to class ancestor or not to type checker
-                    //
-                    // According to current handling of `self`, function definition are fixed and do not change regardless
-                    // of which object is passed as `self` i.e. virtual polymorphism is not supported
-                    // Therefore, we change class id for case 2 to reflect behavior of our compiler
-
-                    let class_name = if *id == "self".into() {
-                        let ast::StmtKind::ClassDef { name, .. } =
-                            &definition_ast_list[class_id].1.as_ref().unwrap().node
-                        else {
-                            unreachable!()
-                        };
-                        name
-                    } else {
-                        id
-                    };
-
-                    let parent_method = definition_ast_list.iter().find_map(|def| {
-                        let (
-                            class_def,
-                            Some(ast::Located {
-                                node: ast::StmtKind::ClassDef { name, body, .. },
-                                ..
-                            }),
-                        ) = &def
-                        else {
-                            return None;
-                        };
-                        let TopLevelDef::Class { object_id: class_id, .. } = &*class_def.read()
-                        else {
-                            unreachable!()
-                        };
-
-                        if name == class_name {
-                            body.iter().find_map(|m| {
-                                let ast::StmtKind::FunctionDef { name, body, .. } = &m.node else {
-                                    return None;
-                                };
-                                if *name == *attr {
-                                    return Some((body.clone(), class_id.0));
-                                }
-                                None
-                            })
-                        } else {
-                            None
-                        }
-                    });
-
-                    // If method body is none then method does not exist
-                    if let Some((method_body, class_id)) = parent_method {
-                        result.extend(Self::get_all_assigned_field(
-                            class_id,
-                            definition_ast_list,
-                            method_body.as_slice(),
-                        )?);
-                    } else {
-                        return Err(HashSet::from([format!(
-                            "{}.{} not found in class {class_name} at {}",
-                            *id, *attr, value.location
-                        )]));
-                    }
+                    result.extend(Self::get_all_assigned_field(body.as_slice())?);
                }
                ast::StmtKind::Pass { .. }
                | ast::StmtKind::Assert { .. }
-                | ast::StmtKind::AnnAssign { .. } => {}
+                | ast::StmtKind::Expr { .. } => {}

                _ => {
                    unimplemented!()
@ -1134,3 +1016,23 @@ pub fn arraylike_get_ndims(unifier: &mut Unifier, ty: Type) -> u64 {
        _ => 0,
    }
 }
+
+/// Extract an ndarray's `ndims` [type][`Type`] in `u64`. Panic if not possible.
+/// The `ndims` must only contain 1 value.
+#[must_use]
+pub fn extract_ndims(unifier: &Unifier, ndims_ty: Type) -> u64 {
+    let ndims_ty_enum = unifier.get_ty_immutable(ndims_ty);
+    let TypeEnum::TLiteral { values, .. } = &*ndims_ty_enum else {
+        panic!("ndims_ty should be a TLiteral");
+    };
+
+    assert_eq!(values.len(), 1, "ndims_ty TLiteral should only contain 1 value");
+
+    let ndims = values[0].clone();
+    u64::try_from(ndims).unwrap()
+}
+
+/// Return an ndarray's `ndims` as a typechecker [`Type`] from its `u64` value.
+pub fn create_ndims(unifier: &mut Unifier, ndims: u64) -> Type {
+    unifier.get_fresh_literal(vec![SymbolValue::U64(ndims)], None)
+}
--- a/nac3core/src/toplevel/mod.rs
+++ b/nac3core/src/toplevel/mod.rs
@ -6,36 +6,36 @@ use std::{
    sync::Arc,
 };

-use inkwell::values::BasicValueEnum;
-use itertools::Itertools;
-use parking_lot::RwLock;
-
-use nac3parser::ast::{self, Expr, Location, Stmt, StrRef};
-
+use super::codegen::CodeGenContext;
+use super::typecheck::type_inferencer::PrimitiveStore;
+use super::typecheck::typedef::{
+    FunSignature, FuncArg, SharedUnifier, Type, TypeEnum, Unifier, VarMap,
+};
 use crate::{
-    codegen::{CodeGenContext, CodeGenerator},
+    codegen::CodeGenerator,
    symbol_resolver::{SymbolResolver, ValueEnum},
    typecheck::{
-        type_inferencer::{CodeLocation, PrimitiveStore},
-        typedef::{
-            CallId, FunSignature, FuncArg, SharedUnifier, Type, TypeEnum, TypeVarId, Unifier,
-            VarMap,
-        },
+        type_inferencer::CodeLocation,
+        typedef::{CallId, TypeVarId},
    },
 };
-use composer::*;
-use type_annotation::*;
+use inkwell::values::BasicValueEnum;
+use itertools::Itertools;
+use nac3parser::ast::{self, Location, Stmt, StrRef};
+use parking_lot::RwLock;
+
+#[derive(PartialEq, Eq, PartialOrd, Ord, Clone, Copy, Hash, Debug)]
+pub struct DefinitionId(pub usize);

 pub mod builtins;
 pub mod composer;
 pub mod helper;
 pub mod numpy;
+pub mod type_annotation;
+use composer::*;
+use type_annotation::*;
 #[cfg(test)]
 mod test;
-pub mod type_annotation;
-
-#[derive(PartialEq, Eq, PartialOrd, Ord, Clone, Copy, Hash, Debug)]
-pub struct DefinitionId(pub usize);

 type GenCallCallback = dyn for<'ctx, 'a> Fn(
        &mut CodeGenContext<'ctx, 'a>,
@ -148,25 +148,6 @@ pub enum TopLevelDef {
        /// Definition location.
        loc: Option<Location>,
    },
-    Variable {
-        /// Qualified name of the global variable, should be unique globally.
-        name: String,
-
-        /// Simple name, the same as in method/function definition.
-        simple_name: StrRef,
-
-        /// Type of the global variable.
-        ty: Type,
-
-        /// The declared type of the global variable, or [`None`] if no type annotation is provided.
-        ty_decl: Option<Expr>,
-
-        /// Symbol resolver of the module defined the class.
-        resolver: Option<Arc<dyn SymbolResolver + Send + Sync>>,
-
-        /// Definition location.
-        loc: Option<Location>,
-    },
 }

 pub struct TopLevelContext {
--- a/nac3core/src/toplevel/numpy.rs
+++ b/nac3core/src/toplevel/numpy.rs
@ -1,10 +1,11 @@
-use itertools::Itertools;
-
-use super::helper::PrimDef;
-use crate::typecheck::{
-    type_inferencer::PrimitiveStore,
-    typedef::{Type, TypeEnum, TypeVarId, Unifier, VarMap},
+use crate::{
+    toplevel::helper::PrimDef,
+    typecheck::{
+        type_inferencer::PrimitiveStore,
+        typedef::{Type, TypeEnum, TypeVarId, Unifier, VarMap},
+    },
 };
+use itertools::Itertools;

 /// Creates a `ndarray` [`Type`] with the given type arguments.
 ///
--- a/nac3core/src/toplevel/test.rs
+++ b/nac3core/src/toplevel/test.rs
@ -1,23 +1,21 @@
-use std::{collections::HashMap, sync::Arc};
-
-use indoc::indoc;
-use parking_lot::Mutex;
-use test_case::test_case;
-
-use nac3parser::{
-    ast::{fold::Fold, FileName},
-    parser::parse_program,
-};
-
-use super::{helper::PrimDef, DefinitionId, *};
+use super::*;
+use crate::toplevel::helper::PrimDef;
+use crate::typecheck::typedef::into_var_map;
 use crate::{
    codegen::CodeGenContext,
    symbol_resolver::{SymbolResolver, ValueEnum},
+    toplevel::DefinitionId,
    typecheck::{
        type_inferencer::PrimitiveStore,
-        typedef::{into_var_map, Type, Unifier},
+        typedef::{Type, Unifier},
    },
 };
+use indoc::indoc;
+use nac3parser::ast::FileName;
+use nac3parser::{ast::fold::Fold, parser::parse_program};
+use parking_lot::Mutex;
+use std::{collections::HashMap, sync::Arc};
+use test_case::test_case;

 struct ResolverInternal {
    id_to_type: Mutex<HashMap<StrRef, Type>>,
@ -64,7 +62,6 @@ impl SymbolResolver for Resolver {
        &self,
        _: StrRef,
        _: &mut CodeGenContext<'ctx, '_>,
-        _: &mut dyn CodeGenerator,
    ) -> Option<ValueEnum<'ctx>> {
        unimplemented!()
    }
--- a/nac3core/src/toplevel/type_annotation.rs
+++ b/nac3core/src/toplevel/type_annotation.rs
@ -1,12 +1,9 @@
-use strum::IntoEnumIterator;
-
+use super::*;
+use crate::symbol_resolver::SymbolValue;
+use crate::toplevel::helper::{PrimDef, PrimDefDetails};
+use crate::typecheck::typedef::VarMap;
 use nac3parser::ast::Constant;
-
-use super::{
-    helper::{PrimDef, PrimDefDetails},
-    *,
-};
-use crate::{symbol_resolver::SymbolValue, typecheck::typedef::VarMap};
+use strum::IntoEnumIterator;

 #[derive(Clone, Debug)]
 pub enum TypeAnnotation {
--- a/nac3core/src/typecheck/function_check.rs
+++ b/nac3core/src/typecheck/function_check.rs
@ -1,19 +1,13 @@
-use std::{
-    collections::{HashMap, HashSet},
-    iter::once,
-};
+use crate::toplevel::helper::PrimDef;

+use super::type_inferencer::Inferencer;
+use super::typedef::{Type, TypeEnum};
 use nac3parser::ast::{
    self, Constant, Expr, ExprKind,
    Operator::{LShift, RShift},
    Stmt, StmtKind, StrRef,
 };
-
-use super::{
-    type_inferencer::{DeclarationSource, IdentifierInfo, Inferencer},
-    typedef::{Type, TypeEnum},
-};
-use crate::toplevel::helper::PrimDef;
+use std::{collections::HashSet, iter::once};

 impl<'a> Inferencer<'a> {
    fn should_have_value(&mut self, expr: &Expr<Option<Type>>) -> Result<(), HashSet<String>> {
@ -27,29 +21,15 @@ impl<'a> Inferencer<'a> {
    fn check_pattern(
        &mut self,
        pattern: &Expr<Option<Type>>,
-        defined_identifiers: &mut HashMap<StrRef, IdentifierInfo>,
+        defined_identifiers: &mut HashSet<StrRef>,
    ) -> Result<(), HashSet<String>> {
        match &pattern.node {
            ExprKind::Name { id, .. } if id == &"none".into() => {
                Err(HashSet::from([format!("cannot assign to a `none` (at {})", pattern.location)]))
            }
            ExprKind::Name { id, .. } => {
-                // If `id` refers to a declared symbol, reject this assignment if it is used in the
-                // context of an (implicit) global variable
-                if let Some(id_info) = defined_identifiers.get(id) {
-                    if matches!(
-                        id_info.source,
-                        DeclarationSource::Global { is_explicit: Some(false) }
-                    ) {
-                        return Err(HashSet::from([format!(
-                            "cannot access local variable '{id}' before it is declared (at {})",
-                            pattern.location
-                        )]));
-                    }
-                }
-
-                if !defined_identifiers.contains_key(id) {
-                    defined_identifiers.insert(*id, IdentifierInfo::default());
+                if !defined_identifiers.contains(id) {
+                    defined_identifiers.insert(*id);
                }
                self.should_have_value(pattern)?;
                Ok(())
@ -89,7 +69,7 @@ impl<'a> Inferencer<'a> {
    fn check_expr(
        &mut self,
        expr: &Expr<Option<Type>>,
-        defined_identifiers: &mut HashMap<StrRef, IdentifierInfo>,
+        defined_identifiers: &mut HashSet<StrRef>,
    ) -> Result<(), HashSet<String>> {
        // there are some cases where the custom field is None
        if let Some(ty) = &expr.custom {
@ -110,7 +90,7 @@ impl<'a> Inferencer<'a> {
                    return Ok(());
                }
                self.should_have_value(expr)?;
-                if !defined_identifiers.contains_key(id) {
+                if !defined_identifiers.contains(id) {
                    match self.function_data.resolver.get_symbol_type(
                        self.unifier,
                        &self.top_level.definitions.read(),
@ -118,22 +98,7 @@ impl<'a> Inferencer<'a> {
                        *id,
                    ) {
                        Ok(_) => {
-                            let is_global = self.is_id_global(*id);
-
-                            defined_identifiers.insert(
-                                *id,
-                                IdentifierInfo {
-                                    source: match is_global {
-                                        Some(true) => {
-                                            DeclarationSource::Global { is_explicit: Some(false) }
-                                        }
-                                        Some(false) => {
-                                            DeclarationSource::Global { is_explicit: None }
-                                        }
-                                        None => DeclarationSource::Local,
-                                    },
-                                },
-                            );
+                            self.defined_identifiers.insert(*id);
                        }
                        Err(e) => {
                            return Err(HashSet::from([format!(
@ -206,7 +171,9 @@ impl<'a> Inferencer<'a> {
                let mut defined_identifiers = defined_identifiers.clone();
                for arg in &args.args {
                    // TODO: should we check the types here?
-                    defined_identifiers.entry(arg.node.arg).or_default();
+                    if !defined_identifiers.contains(&arg.node.arg) {
+                        defined_identifiers.insert(arg.node.arg);
+                    }
                }
                self.check_expr(body, &mut defined_identifiers)?;
            }
@ -269,7 +236,7 @@ impl<'a> Inferencer<'a> {
    fn check_stmt(
        &mut self,
        stmt: &Stmt<Option<Type>>,
-        defined_identifiers: &mut HashMap<StrRef, IdentifierInfo>,
+        defined_identifiers: &mut HashSet<StrRef>,
    ) -> Result<bool, HashSet<String>> {
        match &stmt.node {
            StmtKind::For { target, iter, body, orelse, .. } => {
@ -295,11 +262,9 @@ impl<'a> Inferencer<'a> {
                let body_returned = self.check_block(body, &mut body_identifiers)?;
                let orelse_returned = self.check_block(orelse, &mut orelse_identifiers)?;

-                for ident in body_identifiers.keys() {
-                    if !defined_identifiers.contains_key(ident)
-                        && orelse_identifiers.contains_key(ident)
-                    {
-                        defined_identifiers.insert(*ident, IdentifierInfo::default());
+                for ident in &body_identifiers {
+                    if !defined_identifiers.contains(ident) && orelse_identifiers.contains(ident) {
+                        defined_identifiers.insert(*ident);
                    }
                }
                Ok(body_returned && orelse_returned)
@ -330,7 +295,7 @@ impl<'a> Inferencer<'a> {
                    let mut defined_identifiers = defined_identifiers.clone();
                    let ast::ExcepthandlerKind::ExceptHandler { name, body, .. } = &handler.node;
                    if let Some(name) = name {
-                        defined_identifiers.insert(*name, IdentifierInfo::default());
+                        defined_identifiers.insert(*name);
                    }
                    self.check_block(body, &mut defined_identifiers)?;
                }
@ -394,44 +359,6 @@ impl<'a> Inferencer<'a> {
                }
                Ok(true)
            }
-            StmtKind::Global { names, .. } => {
-                for id in names {
-                    if let Some(id_info) = defined_identifiers.get(id) {
-                        if id_info.source == DeclarationSource::Local {
-                            return Err(HashSet::from([format!(
-                                "name '{id}' is referenced prior to global declaration at {}",
-                                stmt.location,
-                            )]));
-                        }
-
-                        continue;
-                    }
-
-                    match self.function_data.resolver.get_symbol_type(
-                        self.unifier,
-                        &self.top_level.definitions.read(),
-                        self.primitives,
-                        *id,
-                    ) {
-                        Ok(_) => {
-                            defined_identifiers.insert(
-                                *id,
-                                IdentifierInfo {
-                                    source: DeclarationSource::Global { is_explicit: Some(true) },
-                                },
-                            );
-                        }
-                        Err(e) => {
-                            return Err(HashSet::from([format!(
-                                "type error at identifier `{}` ({}) at {}",
-                                id, e, stmt.location
-                            )]))
-                        }
-                    }
-                }
-
-                Ok(false)
-            }
            // break, raise, etc.
            _ => Ok(false),
        }
@ -440,7 +367,7 @@ impl<'a> Inferencer<'a> {
    pub fn check_block(
        &mut self,
        block: &[Stmt<Option<Type>>],
-        defined_identifiers: &mut HashMap<StrRef, IdentifierInfo>,
+        defined_identifiers: &mut HashSet<StrRef>,
    ) -> Result<bool, HashSet<String>> {
        let mut ret = false;
        for stmt in block {
--- a/nac3core/src/typecheck/magic_methods.rs
+++ b/nac3core/src/typecheck/magic_methods.rs
@ -1,21 +1,17 @@
-use std::{cmp::max, collections::HashMap, rc::Rc};
-
-use itertools::{iproduct, Itertools};
-use strum::IntoEnumIterator;
-
-use nac3parser::ast::{Cmpop, Operator, StrRef, Unaryop};
-
-use super::{
+use crate::symbol_resolver::SymbolValue;
+use crate::toplevel::helper::{extract_ndims, PrimDef};
+use crate::toplevel::numpy::{make_ndarray_ty, unpack_ndarray_var_tys};
+use crate::typecheck::{
    type_inferencer::*,
    typedef::{FunSignature, FuncArg, Type, TypeEnum, Unifier, VarMap},
 };
-use crate::{
-    symbol_resolver::SymbolValue,
-    toplevel::{
-        helper::PrimDef,
-        numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
-    },
-};
+use itertools::{iproduct, Itertools};
+use nac3parser::ast::StrRef;
+use nac3parser::ast::{Cmpop, Operator, Unaryop};
+use std::cmp::max;
+use std::collections::HashMap;
+use std::rc::Rc;
+use strum::IntoEnumIterator;

 /// The variant of a binary operator.
 #[derive(Debug, Clone, Copy, PartialEq, Eq)]
@ -524,53 +520,41 @@ pub fn typeof_binop(
        }

        Operator::MatMult => {
-            // NOTE: NumPy matmul's LHS and RHS must both be ndarrays. Scalars are not allowed.
-            match (&*unifier.get_ty(lhs), &*unifier.get_ty(rhs)) {
-                (
-                    TypeEnum::TObj { obj_id: lhs_obj_id, .. },
-                    TypeEnum::TObj { obj_id: rhs_obj_id, .. },
-                ) if *lhs_obj_id == primitives.ndarray.obj_id(unifier).unwrap()
-                    && *rhs_obj_id == primitives.ndarray.obj_id(unifier).unwrap() =>
-                {
-                    // LHS and RHS have valid types
-                }
-                _ => {
-                    let lhs_str = unifier.stringify(lhs);
-                    let rhs_str = unifier.stringify(rhs);
-                    return Err(format!("ndarray.__matmul__ only accepts ndarray operands, but left operand has type {lhs_str}, and right operand has type {rhs_str}"));
-                }
+            let (lhs_dtype, lhs_ndims) = unpack_ndarray_var_tys(unifier, lhs);
+            let lhs_ndims = extract_ndims(unifier, lhs_ndims);
+
+            let (rhs_dtype, rhs_ndims) = unpack_ndarray_var_tys(unifier, rhs);
+            let rhs_ndims = extract_ndims(unifier, rhs_ndims);
+
+            if !(unifier.unioned(lhs_dtype, primitives.float)
+                && unifier.unioned(rhs_dtype, primitives.float))
+            {
+                return Err(format!(
+                    "ndarray.__matmul__ only supports float64 operations, but LHS has type {} and RHS has type {}",
+                    unifier.stringify(lhs),
+                    unifier.stringify(rhs)
+                ));
            }

-            let (_, lhs_ndims) = unpack_ndarray_var_tys(unifier, lhs);
-            let lhs_ndims = match &*unifier.get_ty_immutable(lhs_ndims) {
-                TypeEnum::TLiteral { values, .. } => {
-                    assert_eq!(values.len(), 1);
-                    u64::try_from(values[0].clone()).unwrap()
+            let result_ndims = match (lhs_ndims, rhs_ndims) {
+                (0, _) | (_, 0) => {
+                    return Err(
+                        "ndarray.__matmul__ does not allow unsized ndarray input".to_string()
+                    )
                }
-                _ => unreachable!(),
-            };
-            let (_, rhs_ndims) = unpack_ndarray_var_tys(unifier, rhs);
-            let rhs_ndims = match &*unifier.get_ty_immutable(rhs_ndims) {
-                TypeEnum::TLiteral { values, .. } => {
-                    assert_eq!(values.len(), 1);
-                    u64::try_from(values[0].clone()).unwrap()
-                }
-                _ => unreachable!(),
+                (1, 1) => 0,
+                (1, _) => rhs_ndims - 1,
+                (_, 1) => lhs_ndims - 1,
+                (m, n) => max(m, n),
            };

-            match (lhs_ndims, rhs_ndims) {
-                (2, 2) => typeof_ndarray_broadcast(unifier, primitives, lhs, rhs)?,
-                (lhs, rhs) if lhs == 0 || rhs == 0 => {
-                    return Err(format!(
-                    "Input operand {} does not have enough dimensions (has {lhs}, requires {rhs})",
-                    u8::from(rhs == 0)
-                ))
-                }
-                (lhs, rhs) => {
-                    return Err(format!(
-                        "ndarray.__matmul__ on {lhs}D and {rhs}D operands not supported"
-                    ))
-                }
+            if result_ndims == 0 {
+                // If the result is unsized, NumPy returns a scalar.
+                primitives.float
+            } else {
+                let result_ndims_ty =
+                    unifier.get_fresh_literal(vec![SymbolValue::U64(result_ndims)], None);
+                make_ndarray_ty(unifier, primitives, Some(primitives.float), Some(result_ndims_ty))
            }
        }

@ -773,7 +757,7 @@ pub fn set_primitives_magic_methods(store: &PrimitiveStore, unifier: &mut Unifie
    impl_div(unifier, store, ndarray_t, &[ndarray_t, ndarray_dtype_t], None);
    impl_floordiv(unifier, store, ndarray_t, &[ndarray_unsized_t, ndarray_unsized_dtype_t], None);
    impl_mod(unifier, store, ndarray_t, &[ndarray_unsized_t, ndarray_unsized_dtype_t], None);
-    impl_matmul(unifier, store, ndarray_t, &[ndarray_t], Some(ndarray_t));
+    impl_matmul(unifier, store, ndarray_t, &[ndarray_unsized_t], None);
    impl_sign(unifier, store, ndarray_t, Some(ndarray_t));
    impl_invert(unifier, store, ndarray_t, Some(ndarray_t));
    impl_eq(unifier, store, ndarray_t, &[ndarray_unsized_t, ndarray_unsized_dtype_t], None);
--- a/nac3core/src/typecheck/type_error.rs
+++ b/nac3core/src/typecheck/type_error.rs
@ -1,13 +1,14 @@
-use std::{collections::HashMap, fmt::Display};
+use std::collections::HashMap;
+use std::fmt::Display;

-use itertools::Itertools;
-
-use nac3parser::ast::{Cmpop, Location, StrRef};
+use crate::typecheck::{magic_methods::HasOpInfo, typedef::TypeEnum};

 use super::{
-    magic_methods::{Binop, HasOpInfo},
-    typedef::{RecordKey, Type, TypeEnum, Unifier},
+    magic_methods::Binop,
+    typedef::{RecordKey, Type, Unifier},
 };
+use itertools::Itertools;
+use nac3parser::ast::{Cmpop, Location, StrRef};

 #[derive(Debug, Clone)]
 pub enum TypeErrorKind {
--- a/nac3core/src/typecheck/type_inferencer/mod.rs
+++ b/nac3core/src/typecheck/type_inferencer/mod.rs
@ -1,25 +1,14 @@
-use std::{
-    cell::RefCell,
-    cmp::max,
-    collections::{HashMap, HashSet},
-    convert::{From, TryInto},
-    iter::once,
-    sync::Arc,
-};
-
-use itertools::{izip, Itertools};
-
-use nac3parser::ast::{
-    self,
-    fold::{self, Fold},
-    Arguments, Comprehension, ExprContext, ExprKind, Ident, Located, Location, StrRef,
-};
+use std::cmp::max;
+use std::collections::{HashMap, HashSet};
+use std::convert::{From, TryInto};
+use std::iter::{self, once};
+use std::{cell::RefCell, sync::Arc};

 use super::{
    magic_methods::*,
    type_error::{TypeError, TypeErrorKind},
    typedef::{
-        into_var_map, iter_type_vars, Call, CallId, FunSignature, FuncArg, Mapping, OperatorInfo,
+        into_var_map, iter_type_vars, Call, CallId, FunSignature, FuncArg, OperatorInfo,
        RecordField, RecordKey, Type, TypeEnum, TypeVar, Unifier, VarMap,
    },
 };
@ -28,9 +17,15 @@ use crate::{
    toplevel::{
        helper::{arraylike_flatten_element_type, arraylike_get_ndims, PrimDef},
        numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
-        type_annotation::TypeAnnotation,
        TopLevelContext, TopLevelDef,
    },
+    typecheck::typedef::Mapping,
+};
+use itertools::{izip, Itertools};
+use nac3parser::ast::{
+    self,
+    fold::{self, Fold},
+    Arguments, Comprehension, ExprContext, ExprKind, Located, Location, StrRef,
 };

 #[cfg(test)]
@ -88,40 +83,6 @@ impl PrimitiveStore {
    }
 }

-/// The location where an identifier declaration refers to.
-#[derive(Clone, Copy, Debug, Eq, PartialEq)]
-pub enum DeclarationSource {
-    /// Local scope.
-    Local,
-
-    /// Global scope.
-    Global {
-        /// Whether the identifier is declared by the use of `global` statement. This field is
-        /// [`None`] if the identifier does not refer to a variable.
-        is_explicit: Option<bool>,
-    },
-}
-
-/// Information regarding a defined identifier.
-#[derive(Clone, Copy, Debug)]
-pub struct IdentifierInfo {
-    /// Whether this identifier refers to a global variable.
-    pub source: DeclarationSource,
-}
-
-impl Default for IdentifierInfo {
-    fn default() -> Self {
-        IdentifierInfo { source: DeclarationSource::Local }
-    }
-}
-
-impl IdentifierInfo {
-    #[must_use]
-    pub fn new() -> IdentifierInfo {
-        IdentifierInfo::default()
-    }
-}
-
 pub struct FunctionData {
    pub resolver: Arc<dyn SymbolResolver + Send + Sync>,
    pub return_type: Option<Type>,
@ -130,7 +91,7 @@ pub struct FunctionData {

 pub struct Inferencer<'a> {
    pub top_level: &'a TopLevelContext,
-    pub defined_identifiers: HashMap<StrRef, IdentifierInfo>,
+    pub defined_identifiers: HashSet<StrRef>,
    pub function_data: &'a mut FunctionData,
    pub unifier: &'a mut Unifier,
    pub primitives: &'a PrimitiveStore,
@ -141,7 +102,6 @@ pub struct Inferencer<'a> {
 }

 type InferenceError = HashSet<String>;
-type OverrideResult = Result<Option<ast::Expr<Option<Type>>>, InferenceError>;

 struct NaiveFolder();
 impl Fold<()> for NaiveFolder {
@ -262,7 +222,9 @@ impl<'a> Fold<()> for Inferencer<'a> {
                                handler.location,
                            ));
                            if let Some(name) = name {
-                                self.defined_identifiers.entry(name).or_default();
+                                if !self.defined_identifiers.contains(&name) {
+                                    self.defined_identifiers.insert(name);
+                                }
                                if let Some(old_typ) = self.variable_mapping.insert(name, typ) {
                                    let loc = handler.location;
                                    self.unifier.unify(old_typ, typ).map_err(|e| {
@ -414,7 +376,6 @@ impl<'a> Fold<()> for Inferencer<'a> {
            | ast::StmtKind::Continue { .. }
            | ast::StmtKind::Expr { .. }
            | ast::StmtKind::For { .. }
-            | ast::StmtKind::Global { .. }
            | ast::StmtKind::Pass { .. }
            | ast::StmtKind::Try { .. } => {}
            ast::StmtKind::If { test, .. } | ast::StmtKind::While { test, .. } => {
@ -586,7 +547,7 @@ impl<'a> Fold<()> for Inferencer<'a> {
                        unreachable!("must be tobj")
                    }
                } else {
-                    if !self.defined_identifiers.contains_key(id) {
+                    if !self.defined_identifiers.contains(id) {
                        match self.function_data.resolver.get_symbol_type(
                            self.unifier,
                            &self.top_level.definitions.read(),
@ -594,22 +555,7 @@ impl<'a> Fold<()> for Inferencer<'a> {
                            *id,
                        ) {
                            Ok(_) => {
-                                let is_global = self.is_id_global(*id);
-
-                                self.defined_identifiers.insert(
-                                    *id,
-                                    IdentifierInfo {
-                                        source: match is_global {
-                                            Some(true) => DeclarationSource::Global {
-                                                is_explicit: Some(false),
-                                            },
-                                            Some(false) => {
-                                                DeclarationSource::Global { is_explicit: None }
-                                            }
-                                            None => DeclarationSource::Local,
-                                        },
-                                    },
-                                );
+                                self.defined_identifiers.insert(*id);
                            }
                            Err(e) => {
                                return report_error(
@ -674,8 +620,8 @@ impl<'a> Inferencer<'a> {
    fn infer_pattern<T>(&mut self, pattern: &ast::Expr<T>) -> Result<(), InferenceError> {
        match &pattern.node {
            ExprKind::Name { id, .. } => {
-                if !self.defined_identifiers.contains_key(id) {
-                    self.defined_identifiers.insert(*id, IdentifierInfo::default());
+                if !self.defined_identifiers.contains(id) {
+                    self.defined_identifiers.insert(*id);
                }
                Ok(())
            }
@ -784,8 +730,8 @@ impl<'a> Inferencer<'a> {
        let mut defined_identifiers = self.defined_identifiers.clone();
        for arg in &args.args {
            let name = &arg.node.arg;
-            if !defined_identifiers.contains_key(name) {
-                defined_identifiers.insert(*name, IdentifierInfo::default());
+            if !defined_identifiers.contains(name) {
+                defined_identifiers.insert(*name);
            }
        }
        let fn_args: Vec<_> = args
@ -1235,6 +1181,45 @@ impl<'a> Inferencer<'a> {
            }));
        }

+        if ["np_shape".into(), "np_strides".into()].contains(id) && args.len() == 1 {
+            let ndarray = self.fold_expr(args.remove(0))?;
+
+            let ndims = arraylike_get_ndims(self.unifier, ndarray.custom.unwrap());
+
+            // Make a tuple of size `ndims` full of int32 (TODO: Make it usize)
+            let ret_ty = TypeEnum::TTuple {
+                ty: iter::repeat(self.primitives.int32).take(ndims as usize).collect_vec(),
+                is_vararg_ctx: false,
+            };
+            let ret_ty = self.unifier.add_ty(ret_ty);
+
+            let func_ty = TypeEnum::TFunc(FunSignature {
+                args: vec![FuncArg {
+                    name: "a".into(),
+                    default_value: None,
+                    ty: ndarray.custom.unwrap(),
+                    is_vararg: false,
+                }],
+                ret: ret_ty,
+                vars: VarMap::new(),
+            });
+            let func_ty = self.unifier.add_ty(func_ty);
+
+            return Ok(Some(Located {
+                location,
+                custom: Some(ret_ty),
+                node: ExprKind::Call {
+                    func: Box::new(Located {
+                        custom: Some(func_ty),
+                        location: func.location,
+                        node: ExprKind::Name { id: *id, ctx: *ctx },
+                    }),
+                    args: vec![ndarray],
+                    keywords: vec![],
+                },
+            }));
+        }
+
        if id == &"np_dot".into() {
            let arg0 = self.fold_expr(args.remove(0))?;
            let arg1 = self.fold_expr(args.remove(0))?;
@ -1602,29 +1587,36 @@ impl<'a> Inferencer<'a> {
        }
        // 2-argument ndarray n-dimensional creation functions
        if id == &"np_full".into() && args.len() == 2 {
-            // Parse arguments
-            let shape_expr = args.remove(0);
-            let (ndims, shape) =
-                self.fold_numpy_function_call_shape_argument(*id, 0, shape_expr)?; // Special handling for `shape`
+            let ExprKind::List { elts, .. } = &args[0].node else {
+                return report_error(
+                    format!(
+                        "Expected List literal for first argument of {id}, got {}",
+                        args[0].node.name()
+                    )
+                    .as_str(),
+                    args[0].location,
+                );
+            };

-            let fill_value = self.fold_expr(args.remove(0))?;
+            let ndims = elts.len() as u64;

-            // Build the return type
-            let dtype = fill_value.custom.unwrap();
+            let arg0 = self.fold_expr(args.remove(0))?;
+            let arg1 = self.fold_expr(args.remove(0))?;
+
+            let ty = arg1.custom.unwrap();
            let ndims = self.unifier.get_fresh_literal(vec![SymbolValue::U64(ndims)], None);
-            let ret = make_ndarray_ty(self.unifier, self.primitives, Some(dtype), Some(ndims));
-
+            let ret = make_ndarray_ty(self.unifier, self.primitives, Some(ty), Some(ndims));
            let custom = self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
                args: vec![
                    FuncArg {
                        name: "shape".into(),
-                        ty: shape.custom.unwrap(),
+                        ty: arg0.custom.unwrap(),
                        default_value: None,
                        is_vararg: false,
                    },
                    FuncArg {
                        name: "fill_value".into(),
-                        ty: fill_value.custom.unwrap(),
+                        ty: arg1.custom.unwrap(),
                        default_value: None,
                        is_vararg: false,
                    },
@ -1642,7 +1634,7 @@ impl<'a> Inferencer<'a> {
                        location: func.location,
                        node: ExprKind::Name { id: *id, ctx: *ctx },
                    }),
-                    args: vec![shape, fill_value],
+                    args: vec![arg0, arg1],
                    keywords: vec![],
                },
            }));
@ -1719,86 +1711,6 @@ impl<'a> Inferencer<'a> {
        Ok(None)
    }

-    /// Checks whether a class method is calling parent function
-    /// Returns [`None`] if its not a call to parent method, otherwise
-    /// returns a new `func` with class name replaced by `self` and method resolved to its `DefinitionID`
-    ///
-    /// e.g.  A.f1(self, ...) returns Some(self.{DefintionID(f1)})
-    fn check_overriding(&mut self, func: &ast::Expr<()>, args: &[ast::Expr<()>]) -> OverrideResult {
-        // `self` must be first argument for call to parent method
-        if let Some(Located { node: ExprKind::Name { id, .. }, .. }) = &args.first() {
-            if *id != "self".into() {
-                return Ok(None);
-            }
-        } else {
-            return Ok(None);
-        }
-
-        let Located {
-            node: ExprKind::Attribute { value, attr: method_name, ctx }, location, ..
-        } = func
-        else {
-            return Ok(None);
-        };
-        let ExprKind::Name { id: class_name, ctx: class_ctx } = &value.node else {
-            return Ok(None);
-        };
-        let zelf = &self.fold_expr(args[0].clone())?;
-
-        // Check whether the method belongs to class ancestors
-        let def_id = self.unifier.get_ty(zelf.custom.unwrap());
-        let TypeEnum::TObj { obj_id, .. } = def_id.as_ref() else { unreachable!() };
-        let defs = self.top_level.definitions.read();
-        let res = {
-            if let TopLevelDef::Class { ancestors, .. } = &*defs[obj_id.0].read() {
-                let res = ancestors.iter().find_map(|f| {
-                    let TypeAnnotation::CustomClass { id, .. } = f else { unreachable!() };
-                    let TopLevelDef::Class { name, methods, .. } = &*defs[id.0].read() else {
-                        unreachable!()
-                    };
-                    // Class names are stored as `__module__.class`
-                    let name = name.to_string();
-                    let (_, name) = name.rsplit_once('.').unwrap();
-                    if name == class_name.to_string() {
-                        return methods.iter().find_map(|f| {
-                            if f.0 == *method_name {
-                                return Some(*f);
-                            }
-                            None
-                        });
-                    }
-                    None
-                });
-                res
-            } else {
-                None
-            }
-        };
-
-        match res {
-            Some(r) => {
-                let mut new_func = func.clone();
-                let mut new_value = value.clone();
-                new_value.node = ExprKind::Name { id: "self".into(), ctx: *class_ctx };
-                new_func.node =
-                    ExprKind::Attribute { value: new_value.clone(), attr: *method_name, ctx: *ctx };
-
-                let mut new_func = self.fold_expr(new_func)?;
-
-                let ExprKind::Attribute { value, .. } = new_func.node else { unreachable!() };
-                new_func.node =
-                    ExprKind::Attribute { value, attr: r.2 .0.to_string().into(), ctx: *ctx };
-                new_func.custom = Some(r.1);
-
-                Ok(Some(new_func))
-            }
-            None => report_error(
-                format!("Ancestor method [{class_name}.{method_name}] should be defined with same decorator as its overridden version").as_str(),
-                *location,
-            ),
-        }
-    }
-
    fn fold_call(
        &mut self,
        location: Location,
@ -1812,20 +1724,8 @@ impl<'a> Inferencer<'a> {
            return Ok(spec_call_func);
        }

-        // Check for call to parent method
-        let override_res = self.check_overriding(&func, &args)?;
-        let is_override = override_res.is_some();
-        let func = if is_override { override_res.unwrap() } else { self.fold_expr(func)? };
-        let func = Box::new(func);
-
-        let mut args =
-            args.into_iter().map(|v| self.fold_expr(v)).collect::<Result<Vec<_>, _>>()?;
-
-        // TODO: Handle passing of self to functions to allow runtime lookup of functions to be called
-        // Currently removing `self` and using compile time function definitions
-        if is_override {
-            args.remove(0);
-        }
+        let func = Box::new(self.fold_expr(func)?);
+        let args = args.into_iter().map(|v| self.fold_expr(v)).collect::<Result<Vec<_>, _>>()?;
        let keywords = keywords
            .into_iter()
            .map(|v| fold::fold_keyword(self, v))
@ -2685,22 +2585,4 @@ impl<'a> Inferencer<'a> {
        self.constrain(body.custom.unwrap(), orelse.custom.unwrap(), &body.location)?;
        Ok(body.custom.unwrap())
    }
-
-    /// Determines whether the given `id` refers to a global symbol.
-    ///
-    /// Returns `Some(true)` if `id` refers to a global variable, `Some(false)` if `id` refers to a
-    /// class/function, and `None` if `id` refers to a local symbol.
-    pub(super) fn is_id_global(&self, id: Ident) -> Option<bool> {
-        self.top_level
-            .definitions
-            .read()
-            .iter()
-            .map(|def| match *def.read() {
-                TopLevelDef::Class { name, .. } => (name, false),
-                TopLevelDef::Function { simple_name, .. } => (simple_name, false),
-                TopLevelDef::Variable { simple_name, .. } => (simple_name, true),
-            })
-            .find(|(global, _)| global == &id)
-            .map(|(_, has_explicit_prop)| has_explicit_prop)
-    }
 }
--- a/nac3core/src/typecheck/type_inferencer/test.rs
+++ b/nac3core/src/typecheck/type_inferencer/test.rs
@ -1,19 +1,17 @@
-use std::iter::zip;
-
-use indexmap::IndexMap;
-use indoc::indoc;
-use parking_lot::RwLock;
-use test_case::test_case;
-
-use nac3parser::{ast::FileName, parser::parse_program};
-
+use super::super::{magic_methods::with_fields, typedef::*};
 use super::*;
 use crate::{
-    codegen::{CodeGenContext, CodeGenerator},
+    codegen::CodeGenContext,
    symbol_resolver::ValueEnum,
    toplevel::{helper::PrimDef, DefinitionId, TopLevelDef},
-    typecheck::{magic_methods::with_fields, typedef::*},
 };
+use indexmap::IndexMap;
+use indoc::indoc;
+use nac3parser::ast::FileName;
+use nac3parser::parser::parse_program;
+use parking_lot::RwLock;
+use std::iter::zip;
+use test_case::test_case;

 struct Resolver {
    id_to_type: HashMap<StrRef, Type>,
@ -43,7 +41,6 @@ impl SymbolResolver for Resolver {
        &self,
        _: StrRef,
        _: &mut CodeGenContext<'ctx, '_>,
-        _: &mut dyn CodeGenerator,
    ) -> Option<ValueEnum<'ctx>> {
        unimplemented!()
    }
@ -520,7 +517,7 @@ impl TestEnvironment {
            primitives: &mut self.primitives,
            virtual_checks: &mut self.virtual_checks,
            calls: &mut self.calls,
-            defined_identifiers: HashMap::default(),
+            defined_identifiers: HashSet::default(),
            in_handler: false,
        }
    }
@ -596,9 +593,8 @@ fn test_basic(source: &str, mapping: &HashMap<&str, &str>, virtuals: &[(&str, &s
    println!("source:\n{source}");
    let mut env = TestEnvironment::new();
    let id_to_name = std::mem::take(&mut env.id_to_name);
-    let mut defined_identifiers: HashMap<_, _> =
-        env.identifier_mapping.keys().copied().map(|id| (id, IdentifierInfo::default())).collect();
-    defined_identifiers.insert("virtual".into(), IdentifierInfo::default());
+    let mut defined_identifiers: HashSet<_> = env.identifier_mapping.keys().copied().collect();
+    defined_identifiers.insert("virtual".into());
    let mut inferencer = env.get_inferencer();
    inferencer.defined_identifiers.clone_from(&defined_identifiers);
    let statements = parse_program(source, FileName::default()).unwrap();
@ -743,9 +739,8 @@ fn test_primitive_magic_methods(source: &str, mapping: &HashMap<&str, &str>) {
    println!("source:\n{source}");
    let mut env = TestEnvironment::basic_test_env();
    let id_to_name = std::mem::take(&mut env.id_to_name);
-    let mut defined_identifiers: HashMap<_, _> =
-        env.identifier_mapping.keys().copied().map(|id| (id, IdentifierInfo::default())).collect();
-    defined_identifiers.insert("virtual".into(), IdentifierInfo::default());
+    let mut defined_identifiers: HashSet<_> = env.identifier_mapping.keys().copied().collect();
+    defined_identifiers.insert("virtual".into());
    let mut inferencer = env.get_inferencer();
    inferencer.defined_identifiers.clone_from(&defined_identifiers);
    let statements = parse_program(source, FileName::default()).unwrap();
--- a/nac3core/src/typecheck/typedef/mod.rs
+++ b/nac3core/src/typecheck/typedef/mod.rs
@ -1,28 +1,21 @@
-use std::{
-    borrow::Cow,
-    cell::RefCell,
-    collections::{HashMap, HashSet},
-    fmt::{self, Display},
-    iter::{repeat, zip},
-    rc::Rc,
-    sync::{Arc, Mutex},
-};
-
+use super::magic_methods::{Binop, HasOpInfo};
+use super::type_error::{TypeError, TypeErrorKind};
+use super::unification_table::{UnificationKey, UnificationTable};
+use crate::symbol_resolver::SymbolValue;
+use crate::toplevel::helper::PrimDef;
+use crate::toplevel::{DefinitionId, TopLevelContext, TopLevelDef};
+use crate::typecheck::magic_methods::OpInfo;
+use crate::typecheck::type_inferencer::PrimitiveStore;
 use indexmap::IndexMap;
 use itertools::{repeat_n, Itertools};
-
 use nac3parser::ast::{Cmpop, Location, StrRef, Unaryop};
-
-use super::{
-    magic_methods::{Binop, HasOpInfo, OpInfo},
-    type_error::{TypeError, TypeErrorKind},
-    type_inferencer::PrimitiveStore,
-    unification_table::{UnificationKey, UnificationTable},
-};
-use crate::{
-    symbol_resolver::SymbolValue,
-    toplevel::{helper::PrimDef, DefinitionId, TopLevelContext, TopLevelDef},
-};
+use std::cell::RefCell;
+use std::collections::HashMap;
+use std::fmt::{self, Display};
+use std::iter::{repeat, zip};
+use std::rc::Rc;
+use std::sync::{Arc, Mutex};
+use std::{borrow::Cow, collections::HashSet};

 #[cfg(test)]
 mod test;
@ -677,8 +670,8 @@ impl Unifier {
        let num_args = posargs.len() + kwargs.len();

        // Now we check the arguments against the parameters,
-        // and depending on what `call_info` is, we might change how `unify_call()` behaves
-        // to improve user error messages when type checking fails.
+        // and depending on what `call_info` is, we might change how the behavior `unify_call()`
+        // in hopes to improve user error messages when type checking fails.
        match operator_info {
            Some(OperatorInfo::IsBinaryOp { self_type, operator }) => {
                // The call is written in the form of (say) `a + b`.
--- a/nac3core/src/typecheck/typedef/test.rs
+++ b/nac3core/src/typecheck/typedef/test.rs
@ -1,12 +1,10 @@
-use std::collections::HashMap;
-
+use super::super::magic_methods::with_fields;
+use super::*;
 use indoc::indoc;
 use itertools::Itertools;
+use std::collections::HashMap;
 use test_case::test_case;

-use super::*;
-use crate::typecheck::magic_methods::with_fields;
-
 impl Unifier {
    /// Check whether two types are equal.
    fn eq(&mut self, a: Type, b: Type) -> bool {
--- a/nac3ld/src/lib.rs
+++ b/nac3ld/src/lib.rs
@ -21,12 +21,13 @@
    clippy::wildcard_imports
 )]

-use std::{collections::HashMap, mem, ptr, slice, str};
-
-use byteorder::{ByteOrder, LittleEndian};
-
 use dwarf::*;
 use elf::*;
+use std::collections::HashMap;
+use std::{mem, ptr, slice, str};
+
+extern crate byteorder;
+use byteorder::{ByteOrder, LittleEndian};

 mod dwarf;
 mod elf;
--- a/nac3parser/Cargo.toml
+++ b/nac3parser/Cargo.toml
@ -8,15 +8,15 @@ license = "MIT"
 edition = "2021"

 [build-dependencies]
-lalrpop = "0.22"
+lalrpop = "0.20"

 [dependencies]
 nac3ast = { path = "../nac3ast" }
-lalrpop-util = "0.22"
+lalrpop-util = "0.20"
 log = "0.4"
 unic-emoji-char = "0.9"
 unic-ucd-ident  = "0.9"
-unicode_names2 = "1.3"
+unicode_names2 = "1.2"
 phf = { version = "0.11", features = ["macros"] }
 ahash = "0.8"

--- a/nac3parser/src/config_comment_helper.rs
+++ b/nac3parser/src/config_comment_helper.rs
@ -1,10 +1,8 @@
-use crate::{
-    ast::{Ident, Location},
-    error::*,
-    token::Tok,
-};
+use crate::ast::Ident;
+use crate::ast::Location;
+use crate::error::*;
+use crate::token::Tok;
 use lalrpop_util::ParseError;
-
 use nac3ast::*;

 pub fn make_config_comment(
--- a/nac3parser/src/error.rs
+++ b/nac3parser/src/error.rs
@ -1,11 +1,12 @@
 //! Define internal parse error types
 //! The goal is to provide a matching and a safe error API, maksing errors from LALR
-use std::error::Error;
-use std::fmt;
-
 use lalrpop_util::ParseError as LalrpopError;

-use crate::{ast::Location, token::Tok};
+use crate::ast::Location;
+use crate::token::Tok;
+
+use std::error::Error;
+use std::fmt;

 /// Represents an error during lexical scanning.
 #[derive(Debug, PartialEq)]
--- a/nac3parser/src/fstring.rs
+++ b/nac3parser/src/fstring.rs
@ -1,11 +1,12 @@
-use std::{iter, mem, str};
+use std::iter;
+use std::mem;
+use std::str;
+
+use crate::ast::{Constant, ConversionFlag, Expr, ExprKind, Location};
+use crate::error::{FStringError, FStringErrorType, ParseError};
+use crate::parser::parse_expression;

 use self::FStringErrorType::*;
-use crate::{
-    ast::{Constant, ConversionFlag, Expr, ExprKind, Location},
-    error::{FStringError, FStringErrorType, ParseError},
-    parser::parse_expression,
-};

 struct FStringParser<'a> {
    chars: iter::Peekable<str::Chars<'a>>,
--- a/nac3parser/src/function.rs
+++ b/nac3parser/src/function.rs
@ -1,11 +1,8 @@
+use ahash::RandomState;
 use std::collections::HashSet;

-use ahash::RandomState;
-
-use crate::{
-    ast,
-    error::{LexicalError, LexicalErrorType},
-};
+use crate::ast;
+use crate::error::{LexicalError, LexicalErrorType};

 pub struct ArgumentList {
    pub args: Vec<ast::Expr>,
--- a/nac3parser/src/lexer.rs
+++ b/nac3parser/src/lexer.rs
@ -1,16 +1,16 @@
 //! This module takes care of lexing python source text.
 //!
 //! This means source code is translated into separate tokens.
-use std::{char, cmp::Ordering, num::IntErrorKind, str::FromStr};
-
-use unic_emoji_char::is_emoji_presentation;
-use unic_ucd_ident::{is_xid_continue, is_xid_start};

 pub use super::token::Tok;
-use crate::{
-    ast::{FileName, Location},
-    error::{LexicalError, LexicalErrorType},
-};
+use crate::ast::{FileName, Location};
+use crate::error::{LexicalError, LexicalErrorType};
+use std::char;
+use std::cmp::Ordering;
+use std::num::IntErrorKind;
+use std::str::FromStr;
+use unic_emoji_char::is_emoji_presentation;
+use unic_ucd_ident::{is_xid_continue, is_xid_start};

 #[derive(Clone, Copy, PartialEq, Debug, Default)]
 struct IndentationLevel {
--- a/nac3parser/src/parser.rs
+++ b/nac3parser/src/parser.rs
@ -5,16 +5,14 @@
 //! parse a whole program, a single statement, or a single
 //! expression.

+use nac3ast::Location;
 use std::iter;

-use nac3ast::Location;
-
+use crate::ast::{self, FileName};
+use crate::error::ParseError;
+use crate::lexer;
 pub use crate::mode::Mode;
-use crate::{
-    ast::{self, FileName},
-    error::ParseError,
-    lexer, python,
-};
+use crate::python;

 /*
 * Parse python code.
--- a/nac3parser/src/token.rs
+++ b/nac3parser/src/token.rs
@ -1,8 +1,7 @@
 //! Different token definitions.
 //! Loosely based on token.h from CPython source:
-use std::fmt::{self, Write};
-
 use crate::ast;
+use std::fmt::{self, Write};

 /// Python source code can be tokenized in a sequence of these tokens.
 #[derive(Clone, Debug, PartialEq)]
--- a/nac3standalone/Cargo.toml
+++ b/nac3standalone/Cargo.toml
@ -9,8 +9,14 @@ no-escape-analysis = ["nac3core/no-escape-analysis"]

 [dependencies]
 parking_lot = "0.12"
+nac3parser = { path = "../nac3parser" }
 nac3core = { path = "../nac3core" }

 [dependencies.clap]
 version = "4.5"
 features = ["derive"]
+
+[dependencies.inkwell]
+version = "0.4"
+default-features = false
+features = ["llvm14-0", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
lyken	c845924c20	allow ListObject to have TVar item_type	2024-08-24 12:37:25 +08:00
lyken	2941e8e865	fixup! fixup! core/ndstrides: implement np_array() fix binop +	2024-08-23 16:35:43 +08:00
lyken	4e3e490b92	fixup! core/object: add ListObject and TupleObject fix List field items name	2024-08-23 16:27:49 +08:00
lyken	aad4fafcba	fixup! core: refactor to use ListObject / List fix gen_expr list index slice bug	2024-08-23 16:24:18 +08:00
lyken	9e005e9b07	core/model: fix Ptr::copy_from int types	2024-08-23 16:23:16 +08:00
lyken	7e45c104be	core: remove List proxy	2024-08-23 15:34:26 +08:00
lyken	d2650e6979	core: refactor to use ListObject / List	2024-08-23 15:33:00 +08:00
lyken	2d799d13e2	core/model: add Int not	2024-08-23 15:28:34 +08:00
lyken	2fa3ada445	fixup! core/ndstrides: implement np_array() fix ListObject::get_opaque_list_ptr comment	2024-08-23 12:10:51 +08:00
lyken	787fe23202	fixup! core/ndstrides: implement ndarray indexing fix index comment	2024-08-23 11:50:45 +08:00
lyken	5a893e1c15	core: remove Range proxy	2024-08-23 10:57:31 +08:00
lyken	2b29f7b0f5	core: refactor to use RangeObject / Range	2024-08-23 10:47:30 +08:00
lyken	122f55e615	core/object: add RangeObject & RangeObject::len	2024-08-23 10:22:01 +08:00
lyken	c0cace843d	core/object: remove *Object::is_instance This makes implementations awkward.	2024-08-23 10:21:39 +08:00
lyken	5c68ef00ac	core/irrt: refactor out slice::indices and range::len	2024-08-23 10:02:45 +08:00
lyken	3782791323	core: make IRRT slice and range work for any int types	2024-08-23 09:52:08 +08:00
lyken	ac6c7c5985	fixup! artiq: reimplement get_obj_value to use ndarray with strides update symbol_resolver for general array	2024-08-22 20:57:56 +08:00
lyken	8b0305ab6b	fixup! core/model: introduce models general array	2024-08-22 20:56:25 +08:00
lyken	be4b04dbb3	core: remove old ndarray code and NDArray proxy Nothing depends on the old ndarray implementation now.	2024-08-22 16:34:27 +08:00
lyken	e652919b8e	artiq: reimplement get_obj_value to use ndarray with strides	2024-08-22 16:34:27 +08:00
lyken	ef391b81aa	artiq: reimplement polymorphic_print for ndarray	2024-08-22 16:34:27 +08:00
lyken	ad5506bff1	artiq: reimplement reformat_rpc_arg for ndarrays	2024-08-22 16:34:27 +08:00
lyken	31931b7b26	core/ndstrides: implement np_size()	2024-08-22 16:34:27 +08:00
lyken	be6d704020	standalone: add test_ndarray_broadcast_to	2024-08-22 16:23:01 +08:00
lyken	117110dd91	standalone: add test_ndarray_subscript_assignment	2024-08-22 16:23:01 +08:00
lyken	c582ffe53d	core/ndstrides: implement ndarray subscript assignment	2024-08-22 16:23:01 +08:00
lyken	51b1921e05	core/ndstrides: implement cmpop	2024-08-22 16:23:01 +08:00
lyken	50457f19e6	core/ndstrides: implement unary op	2024-08-22 16:23:01 +08:00
lyken	54f7e1edfd	core/ndstrides: implement nalgebra functions	2024-08-22 16:23:01 +08:00
lyken	1562a938a1	core/ndstrides: add NDArrayObject::to_any	2024-08-22 16:23:01 +08:00
lyken	00800ba6ee	core/ndstrides: add ContiguousNDArray Currently this is used to interop with nalgebra.	2024-08-22 16:23:01 +08:00
lyken	b9e00eb8a5	core/ndstrides: partially update builtin_fns to use ndarray with strides nalgebra functions are not updated	2024-08-22 16:23:01 +08:00
lyken	566ce7df50	core/ndstrides: implement np_dot() for scalars and 1D	2024-08-22 16:23:01 +08:00
lyken	70c26561e1	standalone: extend test_ndarray_matmul	2024-08-22 16:23:01 +08:00
lyken	4fef633090	core/ndstrides: implement general ndarray matmul	2024-08-22 16:23:01 +08:00
lyken	ae351f7678	core/ndstrides: implement binop	2024-08-22 16:23:01 +08:00
lyken	3efae534f7	core/ndstrides: add NDArrayOut, broadcast_map and map	2024-08-22 16:23:01 +08:00
lyken	adca310424	core/ndstrides: add more ScalarOrNDArray and NDArrayObject utils	2024-08-22 16:23:01 +08:00
lyken	e8e4801c92	core/ndstrides: implement np_transpose() (no axes argument)	2024-08-22 16:23:01 +08:00
lyken	9bdc520bbc	core/ndstrides: implement broadcasting & np_broadcast_to()	2024-08-22 16:23:01 +08:00
lyken	9bd08f8de8	core/ndstrides: implement np_reshape()	2024-08-22 16:23:01 +08:00
lyken	5f94f4a4cd	core: categorize np_{transpose,reshape} as 'view functions'	2024-08-22 16:23:01 +08:00
lyken	a2a1e74be0	core/ndstrides: implement np_shape() and np_strides() These functions are not important, but they are handy for debugging + implementing them takes little effort. NOTE: `np.strides()` is not an actual NumPy function. You can only(?) access them thru `ndarray.strides`.	2024-08-22 16:23:01 +08:00
lyken	99eac99db2	core/ndstrides: implement ndarray.fill() and .copy()	2024-08-22 16:23:01 +08:00
lyken	70e1349d32	core/ndstrides: implement np_identity() and np_eye()	2024-08-22 16:23:01 +08:00
lyken	ada6e95d75	core/ndstrides: implement np_array() It also checks for inconsistent dimensions if the input is a list. e.g., rejecting `[[1.0, 2.0], [3.0]]`. Previously it was a todo of `np_array()`.	2024-08-22 16:23:01 +08:00
lyken	4dcbaed8ee	core/irrt: add List Needed for implementing np_array()	2024-08-22 16:23:01 +08:00
lyken	0bb2b02daa	core/ndstrides: add NDArrayObject::atleast_nd	2024-08-22 16:23:01 +08:00
lyken	df6916dbe8	core/ndstrides: add NDArrayObject::make_copy	2024-08-22 16:23:01 +08:00
lyken	0a874da5fc	core/ndstrides: implement ndarray indexing The functionality for `...` and `np.newaxis` is there in IRRT, but there is no implementation of them for @kernel Python expressions because of #486.	2024-08-22 16:23:01 +08:00
lyken	c74b1eb9d8	core/irrt: rename NDIndex to NDIndexInt The name `NDIndex` is used in later commits.	2024-08-22 16:23:01 +08:00
lyken	bda003989e	core/irrt: add Slice and Range Needed for implementing general ndarray indexing	2024-08-22 16:23:01 +08:00
lyken	5411ac5c88	core/ndstrides: implement & refactor call_len()	2024-08-22 16:23:01 +08:00
lyken	1c317f9205	core/ndstrides: implement ndarray np_{zeros,ones,full,empty}	2024-08-22 16:23:01 +08:00
lyken	701e45364c	core/object: add is_instance for ndarray, tuple and list	2024-08-22 16:23:01 +08:00
lyken	fd1a9f4f77	core/model: add util::gen_for_model	2024-08-22 16:23:01 +08:00
lyken	f9b8071df9	core/object: add ListObject and TupleObject Needed for implementing other ndarray utils.	2024-08-22 16:23:00 +08:00
lyken	48fb3ff5ad	core/ndstrides: add ndarray iterator (NDIter)	2024-08-22 16:23:00 +08:00
lyken	4777909543	core/ndstrides: define ndarray with strides	2024-08-22 16:23:00 +08:00
lyken	2ae9196540	core/toplevel/helper: add {extract,create}_ndims	2024-08-22 16:23:00 +08:00
lyken	851ae28460	core/object: introduce object Small abstraction to simplify implementations.	2024-08-22 16:23:00 +08:00
lyken	7c604237b3	core/model: introduce models	2024-08-22 16:23:00 +08:00
lyken	1c7ce22fd5	core/irrt/exceptions: add debug utils with exceptions	2024-08-22 10:06:45 +08:00
lyken	9d3d552e93	core/irrt/exceptions: allow irrt to raise exceptions	2024-08-22 10:06:45 +08:00
lyken	d6deb5af26	core/irrt: split irrt.cpp into headers	2024-08-22 10:06:45 +08:00
lyken	e3f3c498fe	core/irrt: build.rs capture IR defined constants	2024-08-22 10:06:45 +08:00
lyken	20781d11fd	core/irrt: build.rs capture IR defined types	2024-08-22 10:06:45 +08:00
lyken	ecd72e8cad	core/irrt: reformat	2024-08-22 10:06:45 +08:00
lyken	b2183fba24	core: add .clang-format	2024-08-22 10:06:45 +08:00
lyken	3c4d04e7c9	core/irrt: comment build.rs & move irrt to its own dir To prepare for future IRRT implementations, and to also make cargo only have to watch a single directory.	2024-08-22 10:06:45 +08:00