core/ndstrides: refactor numpy indexing

Data content should be copied and strides should be updated after
negative indices are resolved.

.clang-format

@@ -1,32 +1,3 @@
-BasedOnStyle: LLVM
+BasedOnStyle: Google
-
-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
 IndentWidth: 4
-MaxEmptyLinesToKeep: 1
+ReflowComments: false
-PointerAlignment: Left
-ReflowComments: true
-SortIncludes: false
-SortUsingDeclarations: true
-SpaceAfterTemplateKeyword: false
-SpacesBeforeTrailingComments: 2
-TabWidth: 4
-UseTab: Never

.gitignore

@@ -1,4 +1,3 @@
 __pycache__
 /target
-/nac3standalone/demo/linalg/target
 nix/windows/msys2

.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]

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",
 ]
 
 [[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",
 ]
 
 [[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"
@@ -126,12 +117,9 @@ checksum = "1fd0f2584146f6f2ef48085050886acf353beff7305ebd1ae69500e27c67f64b"
 
 [[package]]
 name = "cc"
-version = "1.1.31"
+version = "1.1.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c2e7962b54006dcfcc61cb72735f4d89bb97061dd6a7ed882ec6b8ee53714c6f"
+checksum = "2aba8f4e9906c7ce3c73463f62a7f0c65183ada1a2d47e397cc8810827f9694f"
-dependencies = [
- "shlex",
-]
 
 [[package]]
 name = "cfg-if"
@@ -141,9 +129,9 @@ checksum = "baf1de4339761588bc0619e3cbc0120ee582ebb74b53b4efbf79117bd2da40fd"
 
 [[package]]
 name = "clap"
-version = "4.5.20"
+version = "4.5.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b97f376d85a664d5837dbae44bf546e6477a679ff6610010f17276f686d867e8"
+checksum = "35723e6a11662c2afb578bcf0b88bf6ea8e21282a953428f240574fcc3a2b5b3"
 dependencies = [
  "clap_builder",
  "clap_derive",
@@ -151,9 +139,9 @@ dependencies = [
 
 [[package]]
 name = "clap_builder"
-version = "4.5.20"
+version = "4.5.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "19bc80abd44e4bed93ca373a0704ccbd1b710dc5749406201bb018272808dc54"
+checksum = "49eb96cbfa7cfa35017b7cd548c75b14c3118c98b423041d70562665e07fb0fa"
 dependencies = [
  "anstream",
  "anstyle",
@@ -163,14 +151,14 @@ dependencies = [
 
 [[package]]
 name = "clap_derive"
-version = "4.5.18"
+version = "4.5.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4ac6a0c7b1a9e9a5186361f67dfa1b88213572f427fb9ab038efb2bd8c582dab"
+checksum = "5d029b67f89d30bbb547c89fd5161293c0aec155fc691d7924b64550662db93e"
 dependencies = [
  "heck 0.5.0",
  "proc-macro2",
  "quote",
- "syn 2.0.85",
+ "syn 2.0.72",
 ]
 
 [[package]]
@@ -181,9 +169,9 @@ 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"
@@ -194,16 +182,7 @@ dependencies = [
  "encode_unicode",
  "lazy_static",
  "libc",
- "windows-sys 0.52.0",
+ "windows-sys",
-]
-
-[[package]]
-name = "cpufeatures"
-version = "0.2.14"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "608697df725056feaccfa42cffdaeeec3fccc4ffc38358ecd19b243e716a78e0"
-dependencies = [
- "libc",
 ]
 
 [[package]]
@@ -263,23 +242,30 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "22ec99545bb0ed0ea7bb9b8e1e9122ea386ff8a48c0922e43f36d45ab09e0e80"
 
 [[package]]
-name = "crypto-common"
+name = "crunchy"
-version = "0.1.6"
+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",
+ "cfg-if",
- "typenum",
+ "dirs-sys-next",
 ]
 
 [[package]]
-name = "digest"
+name = "dirs-sys-next"
-version = "0.10.7"
+version = "0.1.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9ed9a281f7bc9b7576e61468ba615a66a5c8cfdff42420a70aa82701a3b1e292"
+checksum = "4ebda144c4fe02d1f7ea1a7d9641b6fc6b580adcfa024ae48797ecdeb6825b4d"
 dependencies = [
- "block-buffer",
+ "libc",
- "crypto-common",
+ "redox_users",
+ "winapi",
 ]
 
 [[package]]
@@ -316,14 +302,14 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "534c5cf6194dfab3db3242765c03bbe257cf92f22b38f6bc0c58d59108a820ba"
 dependencies = [
  "libc",
- "windows-sys 0.52.0",
+ "windows-sys",
 ]
 
 [[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 +326,6 @@ 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 +361,6 @@ 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 +373,6 @@ 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 +385,12 @@ dependencies = [
 
 [[package]]
 name = "indexmap"
-version = "2.6.0"
+version = "2.2.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "707907fe3c25f5424cce2cb7e1cbcafee6bdbe735ca90ef77c29e84591e5b9da"
+checksum = "168fb715dda47215e360912c096649d23d58bf392ac62f73919e831745e40f26"
 dependencies = [
  "equivalent",
- "hashbrown 0.15.0",
+ "hashbrown 0.14.5",
 ]
 
 [[package]]
@@ -440,9 +401,9 @@ 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 +415,13 @@ 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 2.0.72",
 ]
 
 [[package]]
@@ -483,6 +444,15 @@ 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 +468,35 @@ version = "1.0.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "49f1f14873335454500d59611f1cf4a4b0f786f9ac11f4312a78e4cf2566695b"
 
-[[package]]
-name = "keccak"
-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 +507,9 @@ checksum = "bbd2bcb4c963f2ddae06a2efc7e9f3591312473c50c6685e1f298068316e66fe"
 
 [[package]]
 name = "libc"
-version = "0.2.161"
+version = "0.2.155"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8e9489c2807c139ffd9c1794f4af0ebe86a828db53ecdc7fea2111d0fed085d1"
+checksum = "97b3888a4aecf77e811145cadf6eef5901f4782c53886191b2f693f24761847c"
 
 [[package]]
 name = "libloading"
@@ -561,6 +521,16 @@ 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 +591,11 @@ dependencies = [
 name = "nac3artiq"
 version = "0.1.0"
 dependencies = [
- "itertools",
+ "inkwell",
+ "itertools 0.13.0",
  "nac3core",
  "nac3ld",
+ "nac3parser",
  "parking_lot",
  "pyo3",
  "tempfile",
@@ -634,6 +606,7 @@ name = "nac3ast"
 version = "0.1.0"
 dependencies = [
  "fxhash",
+ "lazy_static",
  "parking_lot",
  "string-interner",
 ]
@@ -643,11 +616,11 @@ name = "nac3core"
 version = "0.1.0"
 dependencies = [
  "crossbeam",
- "indexmap 2.6.0",
+ "indexmap 2.2.6",
  "indoc",
  "inkwell",
  "insta",
- "itertools",
+ "itertools 0.13.0",
  "nac3parser",
  "parking_lot",
  "rayon",
@@ -685,7 +658,9 @@ name = "nac3standalone"
 version = "0.1.0"
 dependencies = [
  "clap",
+ "inkwell",
  "nac3core",
+ "nac3parser",
  "parking_lot",
 ]
 
@@ -697,9 +672,9 @@ 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 +706,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b4c5cc86750666a3ed20bdaf5ca2a0344f9c67674cae0515bec2da16fbaa47db"
 dependencies = [
  "fixedbitset",
- "indexmap 2.6.0",
+ "indexmap 2.2.6",
 ]
 
 [[package]]
@@ -774,7 +749,7 @@ dependencies = [
  "phf_shared 0.11.2",
  "proc-macro2",
  "quote",
- "syn 2.0.85",
+ "syn 2.0.72",
 ]
 
 [[package]]
@@ -803,18 +778,15 @@ 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"
-version = "0.2.20"
+version = "0.2.17"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "77957b295656769bb8ad2b6a6b09d897d94f05c41b069aede1fcdaa675eaea04"
+checksum = "5b40af805b3121feab8a3c29f04d8ad262fa8e0561883e7653e024ae4479e6de"
-dependencies = [
- "zerocopy",
-]
 
 [[package]]
 name = "precomputed-hash"
@@ -824,9 +796,9 @@ 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 +850,7 @@ dependencies = [
  "proc-macro2",
  "pyo3-macros-backend",
  "quote",
- "syn 2.0.85",
+ "syn 2.0.72",
 ]
 
 [[package]]
@@ -891,14 +863,14 @@ dependencies = [
  "proc-macro2",
  "pyo3-build-config",
  "quote",
- "syn 2.0.85",
+ "syn 2.0.72",
 ]
 
 [[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 +927,29 @@ 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"
+name = "redox_users"
-version = "1.11.1"
+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 = "1.10.5"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "b91213439dad192326a0d7c6ee3955910425f441d7038e0d6933b0aec5c4517f"
 dependencies = [
  "aho-corasick",
  "memchr",
@@ -976,9 +959,9 @@ 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 +970,9 @@ 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"
@@ -1000,22 +983,22 @@ 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",
  "libc",
  "linux-raw-sys",
- "windows-sys 0.52.0",
+ "windows-sys",
 ]
 
 [[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"
@@ -1046,32 +1029,31 @@ checksum = "61697e0a1c7e512e84a621326239844a24d8207b4669b41bc18b32ea5cbf988b"
 
 [[package]]
 name = "serde"
-version = "1.0.214"
+version = "1.0.204"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f55c3193aca71c12ad7890f1785d2b73e1b9f63a0bbc353c08ef26fe03fc56b5"
+checksum = "bc76f558e0cbb2a839d37354c575f1dc3fdc6546b5be373ba43d95f231bf7c12"
 dependencies = [
  "serde_derive",
 ]
 
 [[package]]
 name = "serde_derive"
-version = "1.0.214"
+version = "1.0.204"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "de523f781f095e28fa605cdce0f8307e451cc0fd14e2eb4cd2e98a355b147766"
+checksum = "e0cd7e117be63d3c3678776753929474f3b04a43a080c744d6b0ae2a8c28e222"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.85",
+ "syn 2.0.72",
 ]
 
 [[package]]
 name = "serde_json"
-version = "1.0.132"
+version = "1.0.120"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d726bfaff4b320266d395898905d0eba0345aae23b54aee3a737e260fd46db03"
+checksum = "4e0d21c9a8cae1235ad58a00c11cb40d4b1e5c784f1ef2c537876ed6ffd8b7c5"
 dependencies = [
  "itoa",
- "memchr",
  "ryu",
  "serde",
 ]
@@ -1088,22 +1070,6 @@ 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"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0fda2ff0d084019ba4d7c6f371c95d8fd75ce3524c3cb8fb653a3023f6323e64"
-
 [[package]]
 name = "similar"
 version = "2.6.0"
@@ -1168,7 +1134,7 @@ dependencies = [
  "proc-macro2",
  "quote",
  "rustversion",
- "syn 2.0.85",
+ "syn 2.0.72",
 ]
 
 [[package]]
@@ -1184,9 +1150,9 @@ dependencies = [
 
 [[package]]
 name = "syn"
-version = "2.0.85"
+version = "2.0.72"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5023162dfcd14ef8f32034d8bcd4cc5ddc61ef7a247c024a33e24e1f24d21b56"
+checksum = "dc4b9b9bf2add8093d3f2c0204471e951b2285580335de42f9d2534f3ae7a8af"
 dependencies = [
  "proc-macro2",
  "quote",
@@ -1195,31 +1161,31 @@ dependencies = [
 
 [[package]]
 name = "target-lexicon"
-version = "0.12.16"
+version = "0.12.15"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "61c41af27dd6d1e27b1b16b489db798443478cef1f06a660c96db617ba5de3b1"
+checksum = "4873307b7c257eddcb50c9bedf158eb669578359fb28428bef438fec8e6ba7c2"
 
 [[package]]
 name = "tempfile"
-version = "3.13.0"
+version = "3.10.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f0f2c9fc62d0beef6951ccffd757e241266a2c833136efbe35af6cd2567dca5b"
+checksum = "85b77fafb263dd9d05cbeac119526425676db3784113aa9295c88498cbf8bff1"
 dependencies = [
  "cfg-if",
  "fastrand",
- "once_cell",
  "rustix",
- "windows-sys 0.59.0",
+ "windows-sys",
 ]
 
 [[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",
+ "dirs-next",
- "windows-sys 0.52.0",
+ "rustversion",
+ "winapi",
 ]
 
 [[package]]
@@ -1237,29 +1203,32 @@ 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 2.0.72",
 ]
 
 [[package]]
-name = "typenum"
+name = "tiny-keccak"
-version = "1.17.0"
+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 +1284,27 @@ 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 +1312,9 @@ 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",
@@ -1388,14 +1357,36 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "9c8d87e72b64a3b4db28d11ce29237c246188f4f51057d65a7eab63b7987e423"
 
 [[package]]
-name = "winapi-util"
+name = "winapi"
-version = "0.1.9"
+version = "0.3.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "cf221c93e13a30d793f7645a0e7762c55d169dbb0a49671918a2319d289b10bb"
+checksum = "5c839a674fcd7a98952e593242ea400abe93992746761e38641405d28b00f419"
 dependencies = [
- "windows-sys 0.59.0",
+ "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 = "0.1.8"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "4d4cc384e1e73b93bafa6fb4f1df8c41695c8a91cf9c4c64358067d15a7b6c6b"
+dependencies = [
+ "windows-sys",
+]
+
+[[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"
@@ -1405,15 +1396,6 @@ dependencies = [
  "windows-targets",
 ]
 
-[[package]]
-name = "windows-sys"
-version = "0.59.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1e38bc4d79ed67fd075bcc251a1c39b32a1776bbe92e5bef1f0bf1f8c531853b"
-dependencies = [
- "windows-targets",
-]
-
 [[package]]
 name = "windows-targets"
 version = "0.52.6"
@@ -1493,7 +1475,6 @@ version = "0.7.35"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "1b9b4fd18abc82b8136838da5d50bae7bdea537c574d8dc1a34ed098d6c166f0"
 dependencies = [
- "byteorder",
  "zerocopy-derive",
 ]
 
@@ -1505,5 +1486,5 @@ checksum = "fa4f8080344d4671fb4e831a13ad1e68092748387dfc4f55e356242fae12ce3e"
 dependencies = [
  "proc-macro2",
  "quote",
- "syn 2.0.85",
+ "syn 2.0.72",
 ]

flake.lock

@@ -2,11 +2,11 @@
   "nodes": {
     "nixpkgs": {
       "locked": {
-        "lastModified": 1727348695,
+        "lastModified": 1721924956,
-        "narHash": "sha256-J+PeFKSDV+pHL7ukkfpVzCOO7mBSrrpJ3svwBFABbhI=",
+        "narHash": "sha256-Sb1jlyRO+N8jBXEX9Pg9Z1Qb8Bw9QyOgLDNMEpmjZ2M=",
         "owner": "NixOS",
         "repo": "nixpkgs",
-        "rev": "1925c603f17fc89f4c8f6bf6f631a802ad85d784",
+        "rev": "5ad6a14c6bf098e98800b091668718c336effc95",
         "type": "github"
       },
       "original": {

flake.nix

@@ -6,7 +6,6 @@
   outputs = { self, nixpkgs }:
     let
       pkgs = import nixpkgs { system = "x86_64-linux"; };
-      pkgs32 = import nixpkgs { system = "i686-linux"; };
     in rec {
       packages.x86_64-linux = rec {
         llvm-nac3 = pkgs.callPackage ./nix/llvm {};
@@ -14,24 +13,9 @@
           ''
           mkdir -p $out/bin
           ln -s ${pkgs.llvmPackages_14.clang-unwrapped}/bin/clang $out/bin/clang-irrt
+          ln -s ${pkgs.llvmPackages_14.clang}/bin/clang $out/bin/clang-irrt-test
           ln -s ${pkgs.llvmPackages_14.llvm.out}/bin/llvm-as $out/bin/llvm-as-irrt
           '';
-        demo-linalg-stub = pkgs.rustPlatform.buildRustPackage {
-          name = "demo-linalg-stub";
-          src = ./nac3standalone/demo/linalg;
-          cargoLock = {
-            lockFile = ./nac3standalone/demo/linalg/Cargo.lock;
-          };
-          doCheck = false;
-        };
-        demo-linalg-stub32 = pkgs32.rustPlatform.buildRustPackage {
-          name = "demo-linalg-stub32";
-          src = ./nac3standalone/demo/linalg;
-          cargoLock = {
-            lockFile = ./nac3standalone/demo/linalg/Cargo.lock;
-          };
-          doCheck = false;
-        };
         nac3artiq = pkgs.python3Packages.toPythonModule (
           pkgs.rustPlatform.buildRustPackage rec {
             name = "nac3artiq";
@@ -40,6 +24,7 @@
             cargoLock = {
               lockFile = ./Cargo.lock;
             };
+            cargoTestFlags = [ "--features" "test" ];
             passthru.cargoLock = cargoLock;
             nativeBuildInputs = [ pkgs.python3 (pkgs.wrapClangMulti pkgs.llvmPackages_14.clang) llvm-tools-irrt pkgs.llvmPackages_14.llvm.out llvm-nac3 ];
             buildInputs = [ pkgs.python3 llvm-nac3 ];
@@ -49,9 +34,7 @@
               echo "Checking nac3standalone demos..."
               pushd nac3standalone/demo
               patchShebangs .
-              export DEMO_LINALG_STUB=${demo-linalg-stub}/lib/liblinalg.a
+              ./check_demos.sh
-              export DEMO_LINALG_STUB32=${demo-linalg-stub32}/lib/liblinalg.a
-              ./check_demos.sh -i686
               popd
               echo "Running Cargo tests..."
               cargoCheckHook
@@ -181,11 +164,6 @@
           pre-commit
           rustfmt
         ];
-        shellHook =
-          ''
-          export DEMO_LINALG_STUB=${packages.x86_64-linux.demo-linalg-stub}/lib/liblinalg.a
-          export DEMO_LINALG_STUB32=${packages.x86_64-linux.demo-linalg-stub32}/lib/liblinalg.a
-          '';
       };
       devShells.x86_64-linux.msys2 = pkgs.mkShell {
         name = "nac3-dev-shell-msys2";

nac3artiq/Cargo.toml

@@ -12,10 +12,15 @@ 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"]

nac3artiq/demo/min_artiq.py

@@ -112,15 +112,10 @@ def extern(function):
     register_function(function)
     return function
 
-
+def rpc(function):
-def rpc(arg=None, flags={}):
+    """Decorates a function declaration defined by the core device runtime."""
-    """Decorates a function or method to be executed on the host interpreter."""
+    register_function(function)
-    if arg is None:
+    return function
-        def inner_decorator(function):
-            return rpc(function, flags)
-        return inner_decorator
-    register_function(arg)
-    return arg
 
 def kernel(function_or_method):
     """Decorates a function or method to be executed on the core device."""

nac3artiq/demo/str_abi.py

@@ -1,26 +0,0 @@
-from min_artiq import *
-from numpy import ndarray, zeros as np_zeros
-
-
-@nac3
-class StrFail:
-    core: KernelInvariant[Core]
-
-    def __init__(self):
-        self.core = Core()
-
-    @kernel
-    def hello(self, arg: str):
-        pass
-
-    @kernel
-    def consume_ndarray(self, arg: ndarray[str, 1]):
-        pass
-
-    def run(self):
-        self.hello("world")
-        self.consume_ndarray(np_zeros([10], dtype=str))
-
-
-if __name__ == "__main__":
-    StrFail().run()

nac3artiq/src/lib.rs

@@ -16,65 +16,64 @@
     clippy::wildcard_imports
 )]
 
-use std::{
+use std::collections::{HashMap, HashSet};
-    collections::{HashMap, HashSet},
+use std::fs;
-    fs,
+use std::io::Write;
-    io::Write,
+use std::process::Command;
-    process::Command,
+use std::rc::Rc;
-    rc::Rc,
+use std::sync::Arc;
-    sync::Arc,
-};
 
-use itertools::Itertools;
+use inkwell::{
-use parking_lot::{Mutex, RwLock};
+    context::Context,
-use pyo3::{
+    memory_buffer::MemoryBuffer,
-    create_exception, exceptions,
+    module::{Linkage, Module},
-    prelude::*,
+    passes::PassBuilderOptions,
-    types::{PyBytes, PyDict, PySet},
+    support::is_multithreaded,
+    targets::*,
+    OptimizationLevel,
 };
-use tempfile::{self, TempDir};
+use itertools::Itertools;
+use nac3core::codegen::{gen_func_impl, CodeGenLLVMOptions, CodeGenTargetMachineOptions};
+use nac3core::toplevel::builtins::get_exn_constructor;
+use nac3core::typecheck::typedef::{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::{
+    codegen::irrt::load_irrt,
-        concrete_type::ConcreteTypeStore, gen_func_impl, irrt::load_irrt, CodeGenLLVMOptions,
+    codegen::{concrete_type::ConcreteTypeStore, CodeGenTask, WithCall, WorkerRegistry},
-        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,
-    },
     symbol_resolver::SymbolResolver,
     toplevel::{
-        builtins::get_exn_constructor,
+        composer::{ComposerConfig, TopLevelComposer},
-        composer::{BuiltinFuncCreator, BuiltinFuncSpec, ComposerConfig, TopLevelComposer},
         DefinitionId, GenCall, TopLevelDef,
     },
-    typecheck::{
+    typecheck::typedef::{FunSignature, FuncArg},
-        type_inferencer::PrimitiveStore,
+    typecheck::{type_inferencer::PrimitiveStore, typedef::Type},
-        typedef::{into_var_map, FunSignature, FuncArg, Type, TypeEnum, Unifier, VarMap},
-    },
 };
+
 use nac3ld::Linker;
 
-use codegen::{
+use tempfile::{self, TempDir};
-    attributes_writeback, gen_core_log, gen_rtio_log, rpc_codegen_callback, ArtiqCodeGenerator,
+
+use crate::codegen::attributes_writeback;
+use crate::{
+    codegen::{rpc_codegen_callback, ArtiqCodeGenerator},
+    symbol_resolver::{DeferredEvaluationStore, InnerResolver, PythonHelper, Resolver},
 };
-use symbol_resolver::{DeferredEvaluationStore, InnerResolver, PythonHelper, Resolver};
-use timeline::TimeFns;
 
 mod codegen;
 mod symbol_resolver;
 mod timeline;
 
+use timeline::TimeFns;
+
 #[derive(PartialEq, Clone, Copy)]
 enum Isa {
     Host,
@@ -128,7 +127,7 @@ struct Nac3 {
     isa: Isa,
     time_fns: &'static (dyn TimeFns + Sync),
     primitive: PrimitiveStore,
-    builtins: Vec<BuiltinFuncSpec>,
+    builtins: Vec<(StrRef, FunSignature, Arc<GenCall>)>,
     pyid_to_def: Arc<RwLock<HashMap<u64, DefinitionId>>>,
     primitive_ids: PrimitivePythonId,
     working_directory: TempDir,
@@ -195,8 +194,10 @@ 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) {
+                                if let ExprKind::Name { id, .. } = decorator.node {
-                                    id == "kernel" || id == "portable" || id == "rpc"
+                                    id.to_string() == "kernel"
+                                        || id.to_string() == "portable"
+                                        || id.to_string() == "rpc"
                                 } else {
                                     false
                                 }
@@ -209,8 +210,9 @@ impl Nac3 {
                 }
                 StmtKind::FunctionDef { ref decorator_list, .. } => {
                     decorator_list.iter().any(|decorator| {
-                        if let Some(id) = decorator_id_string(decorator) {
+                        if let ExprKind::Name { id, .. } = decorator.node {
-                            id == "extern" || id == "kernel" || id == "portable" || id == "rpc"
+                            let id = id.to_string();
+                            id == "extern" || id == "portable" || id == "kernel" || id == "rpc"
                         } else {
                             false
                         }
@@ -263,7 +265,7 @@ impl Nac3 {
                     arg_names.len(),
                 ));
             }
-            for (i, FuncArg { ty, default_value, name, .. }) in args.iter().enumerate() {
+            for (i, FuncArg { ty, default_value, name }) in args.iter().enumerate() {
                 let in_name = match arg_names.get(i) {
                     Some(n) => n,
                     None if default_value.is_none() => {
@@ -299,64 +301,6 @@ impl Nac3 {
         None
     }
 
-    /// Returns a [`Vec`] of builtins that needs to be initialized during method compilation time.
-    fn get_lateinit_builtins() -> Vec<Box<BuiltinFuncCreator>> {
-        vec![
-            Box::new(|primitives, unifier| {
-                let arg_ty = unifier.get_fresh_var(Some("T".into()), None);
-
-                (
-                    "core_log".into(),
-                    FunSignature {
-                        args: vec![FuncArg {
-                            name: "arg".into(),
-                            ty: arg_ty.ty,
-                            default_value: None,
-                            is_vararg: false,
-                        }],
-                        ret: primitives.none,
-                        vars: into_var_map([arg_ty]),
-                    },
-                    Arc::new(GenCall::new(Box::new(move |ctx, obj, fun, args, generator| {
-                        gen_core_log(ctx, &obj, fun, &args, generator)?;
-
-                        Ok(None)
-                    }))),
-                )
-            }),
-            Box::new(|primitives, unifier| {
-                let arg_ty = unifier.get_fresh_var(Some("T".into()), None);
-
-                (
-                    "rtio_log".into(),
-                    FunSignature {
-                        args: vec![
-                            FuncArg {
-                                name: "channel".into(),
-                                ty: primitives.str,
-                                default_value: None,
-                                is_vararg: false,
-                            },
-                            FuncArg {
-                                name: "arg".into(),
-                                ty: arg_ty.ty,
-                                default_value: None,
-                                is_vararg: false,
-                            },
-                        ],
-                        ret: primitives.none,
-                        vars: into_var_map([arg_ty]),
-                    },
-                    Arc::new(GenCall::new(Box::new(move |ctx, obj, fun, args, generator| {
-                        gen_rtio_log(ctx, &obj, fun, &args, generator)?;
-
-                        Ok(None)
-                    }))),
-                )
-            }),
-        ]
-    }
-
     fn compile_method<T>(
         &self,
         obj: &PyAny,
@@ -369,7 +313,6 @@ impl Nac3 {
         let size_t = self.isa.get_size_type();
         let (mut composer, mut builtins_def, mut builtins_ty) = TopLevelComposer::new(
             self.builtins.clone(),
-            Self::get_lateinit_builtins(),
             ComposerConfig { kernel_ann: Some("Kernel"), kernel_invariant_ann: "KernelInvariant" },
             size_t,
         );
@@ -446,6 +389,7 @@ 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 +420,9 @@ impl Nac3 {
 
             match &stmt.node {
                 StmtKind::FunctionDef { decorator_list, .. } => {
-                    if decorator_list
+                    if decorator_list.iter().any(|decorator| matches!(decorator.node, ExprKind::Name { id, .. } if id == "rpc".into())) {
-                        .iter()
+                        store_fun.call1(py, (def_id.0.into_py(py), module.getattr(py, name.to_string().as_str()).unwrap())).unwrap();
-                        .any(|decorator| decorator_id_string(decorator) == Some("rpc".to_string()))
+                        rpc_ids.push((None, def_id));
-                    {
-                        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));
                     }
                 }
                 StmtKind::ClassDef { name, body, .. } => {
@@ -502,26 +430,19 @@ 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| {
+                            if decorator_list.iter().any(|decorator| matches!(decorator.node, ExprKind::Name { id, .. } if id == "rpc".into())) {
-                                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 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 +481,7 @@ 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(),
@@ -576,10 +498,6 @@ impl Nac3 {
             .register_top_level(synthesized.pop().unwrap(), Some(resolver.clone()), "", false)
             .unwrap();
 
-        // Process IRRT
-        let context = Context::create();
-        let irrt = load_irrt(&context, resolver.as_ref());
-
         let fun_signature =
             FunSignature { args: vec![], ret: self.primitive.none, vars: VarMap::new() };
         let mut store = ConcreteTypeStore::new();
@@ -617,12 +535,13 @@ 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 +552,7 @@ 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 +567,6 @@ impl Nac3 {
                             }
                         }
                     }
-                    TopLevelDef::Variable { .. } => {
-                        return Err(CompileError::new_err(String::from(
-                            "Unsupported @rpc annotation on global variable",
-                        )))
-                    }
                 }
             }
         }
@@ -712,7 +626,7 @@ 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 +645,7 @@ 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());
@@ -754,7 +668,7 @@ impl Nac3 {
             membuffer.lock().push(buffer);
         });
 
-        // Link all modules into `main`.
+        let context = inkwell::context::Context::create();
         let buffers = membuffers.lock();
         let main = context
             .create_module_from_ir(MemoryBuffer::create_from_memory_range(&buffers[0], "main"))
@@ -783,7 +697,8 @@ impl Nac3 {
             )
             .unwrap();
 
-        main.link_in_module(irrt).map_err(|err| CompileError::new_err(err.to_string()))?;
+        main.link_in_module(load_irrt(&context))
+            .map_err(|err| CompileError::new_err(err.to_string()))?;
 
         let mut function_iter = main.get_first_function();
         while let Some(func) = function_iter {
@@ -869,41 +784,6 @@ 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(),
@@ -973,7 +853,7 @@ impl Nac3 {
             Isa::RiscV32IMA => &timeline::NOW_PINNING_TIME_FNS,
             Isa::CortexA9 | Isa::Host => &timeline::EXTERN_TIME_FNS,
         };
-        let (primitive, _) = TopLevelComposer::make_primitives(isa.get_size_type());
+        let primitive: PrimitiveStore = TopLevelComposer::make_primitives(isa.get_size_type()).0;
         let builtins = vec![
             (
                 "now_mu".into(),
@@ -989,7 +869,6 @@ impl Nac3 {
                         name: "t".into(),
                         ty: primitive.int64,
                         default_value: None,
-                        is_vararg: false,
                     }],
                     ret: primitive.none,
                     vars: VarMap::new(),
@@ -1009,7 +888,6 @@ impl Nac3 {
                         name: "dt".into(),
                         ty: primitive.int64,
                         default_value: None,
-                        is_vararg: false,
                     }],
                     ret: primitive.none,
                     vars: VarMap::new(),

nac3artiq/src/symbol_resolver.rs

@@ -1,30 +1,14 @@
-use std::{
+use inkwell::{
-    collections::{HashMap, HashSet},
+    types::{BasicType, BasicTypeEnum},
-    sync::{
+    values::BasicValueEnum,
-        atomic::{AtomicBool, Ordering::Relaxed},
+    AddressSpace,
-        Arc,
-    },
 };
-
 use itertools::Itertools;
-use parking_lot::RwLock;
-use pyo3::{
-    types::{PyDict, PyTuple},
-    PyAny, PyObject, PyResult, Python,
-};
-
 use nac3core::{
     codegen::{
         classes::{NDArrayType, ProxyType},
         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 +20,21 @@ use nac3core::{
         typedef::{into_var_map, iter_type_vars, Type, TypeEnum, TypeVar, Unifier, VarMap},
     },
 };
+use nac3parser::ast::{self, StrRef};
+use parking_lot::{Mutex, RwLock};
+use pyo3::{
+    types::{PyDict, PyTuple},
+    PyAny, PyObject, PyResult, Python,
+};
+use std::{
+    collections::{HashMap, HashSet},
+    sync::{
+        atomic::{AtomicBool, Ordering::Relaxed},
+        Arc,
+    },
+};
 
-use super::PrimitivePythonId;
+use crate::PrimitivePythonId;
 
 pub enum PrimitiveValue {
     I32(i32),
@@ -82,6 +79,7 @@ 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,
@@ -135,8 +133,6 @@ impl StaticValue for PythonValue {
                         format!("{}_const", self.id).as_str(),
                     );
                     global.set_constant(true);
-                    // Set linkage of global to private to avoid name collisions
-                    global.set_linkage(Linkage::Private);
                     global.set_initializer(&ctx.ctx.const_struct(
                         &[ctx.ctx.i32_type().const_int(u64::from(id), false).into()],
                         false,
@@ -167,7 +163,7 @@ impl StaticValue for PythonValue {
                 PrimitiveValue::Bool(val) => {
                     ctx.ctx.i8_type().const_int(u64::from(*val), false).into()
                 }
-                PrimitiveValue::Str(val) => ctx.gen_string(generator, val).into(),
+                PrimitiveValue::Str(val) => ctx.ctx.const_string(val.as_bytes(), true).into(),
             });
         }
         if let Some(global) = ctx.module.get_global(&self.id.to_string()) {
@@ -355,7 +351,7 @@ impl InnerResolver {
             Ok(Ok((ndarray, false)))
         } else if ty_id == self.primitive_ids.tuple {
             // do not handle type var param and concrete check here
-            Ok(Ok((unifier.add_ty(TypeEnum::TTuple { ty: vec![], is_vararg_ctx: false }), false)))
+            Ok(Ok((unifier.add_ty(TypeEnum::TTuple { ty: vec![] }), false)))
         } else if ty_id == self.primitive_ids.option {
             Ok(Ok((primitives.option, false)))
         } else if ty_id == self.primitive_ids.none {
@@ -559,10 +555,7 @@ impl InnerResolver {
                             Err(err) => return Ok(Err(err)),
                             _ => return Ok(Err("tuple type needs at least 1 type parameters".to_string()))
                         };
-                    Ok(Ok((
+                    Ok(Ok((unifier.add_ty(TypeEnum::TTuple { ty: args }), true)))
-                        unifier.add_ty(TypeEnum::TTuple { ty: args, is_vararg_ctx: false }),
-                        true,
-                    )))
                 }
                 TypeEnum::TObj { params, obj_id, .. } => {
                     let subst = {
@@ -804,9 +797,7 @@ impl InnerResolver {
                     .map(|elem| self.get_obj_type(py, elem, unifier, defs, primitives))
                     .collect();
                 let types = types?;
-                Ok(types.map(|types| {
+                Ok(types.map(|types| unifier.add_ty(TypeEnum::TTuple { ty: types })))
-                    unifier.add_ty(TypeEnum::TTuple { ty: types, is_vararg_ctx: false })
-                }))
             }
             // special handling for option type since its class member layout in python side
             // is special and cannot be mapped directly to a nac3 type as below
@@ -981,7 +972,7 @@ impl InnerResolver {
         } else if ty_id == self.primitive_ids.string || ty_id == self.primitive_ids.np_str_ {
             let val: String = obj.extract().unwrap();
             self.id_to_primitive.write().insert(id, PrimitiveValue::Str(val.clone()));
-            Ok(Some(ctx.gen_string(generator, val).into()))
+            Ok(Some(ctx.ctx.const_string(val.as_bytes(), true).into()))
         } else if ty_id == self.primitive_ids.float || ty_id == self.primitive_ids.float64 {
             let val: f64 = obj.extract().unwrap();
             self.id_to_primitive.write().insert(id, PrimitiveValue::F64(val));
@@ -1212,9 +1203,7 @@ impl InnerResolver {
             Ok(Some(ndarray.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 {
+            let TypeEnum::TTuple { ty } = expected_ty_enum.as_ref() else { unreachable!() };
-                unreachable!()
-            };
 
             let tup_tys = ty.iter();
             let elements: &PyTuple = obj.downcast()?;
@@ -1470,7 +1459,6 @@ 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();

nac3artiq/src/timeline.rs

@@ -1,12 +1,9 @@
-use itertools::Either;
+use inkwell::{
-
+    values::{BasicValueEnum, CallSiteValue},
-use nac3core::{
+    AddressSpace, AtomicOrdering,
-    codegen::CodeGenContext,
-    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();
 

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"

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>> =
+lazy_static! {
-    LazyLock::new(|| Mutex::new(StringInterner::with_hasher(FxBuildHasher::default())));
+    static ref INTERNER: Mutex<Interner> =
+        Mutex::new(StringInterner::with_hasher(FxBuildHasher::default()));
+}
 
 thread_local! {
     static LOCAL_INTERNER: RefCell<HashMap<String, StrRef>> = RefCell::default();

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")]

nac3core/Cargo.toml

@@ -1,26 +1,26 @@
+[features]
+test = []
+
 [package]
 name = "nac3core"
 version = "0.1.0"
 authors = ["M-Labs"]
 edition = "2021"
 
-[features]
-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 = "0.26.2"
-strum_macros = "0.26"
+strum_macros = "0.26.4"
 
 [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"

nac3core/build.rs

@@ -1,32 +1,46 @@
+use regex::Regex;
 use std::{
     env,
     fs::File,
     io::Write,
-    path::Path,
+    path::{Path, PathBuf},
     process::{Command, Stdio},
 };
 
-use regex::Regex;
+const CMD_IRRT_CLANG: &str = "clang-irrt";
+const CMD_IRRT_CLANG_TEST: &str = "clang-irrt-test";
+const CMD_IRRT_LLVM_AS: &str = "llvm-as-irrt";
 
-fn main() {
+fn get_out_dir() -> PathBuf {
-    let out_dir = env::var("OUT_DIR").unwrap();
+    PathBuf::from(env::var("OUT_DIR").unwrap())
-    let out_dir = Path::new(&out_dir);
+}
-    let irrt_dir = Path::new("irrt");
 
-    let irrt_cpp_path = irrt_dir.join("irrt.cpp");
+fn get_irrt_dir() -> &'static Path {
+    Path::new("irrt")
+}
+
+/// Compile `irrt.cpp` for use in `src/codegen`
+fn compile_irrt_cpp() {
+    let out_dir = get_out_dir();
+    let irrt_dir = get_irrt_dir();
 
     /*
      * HACK: Sadly, clang doesn't let us emit generic LLVM bitcode.
      * Compiling for WASM32 and filtering the output with regex is the closest we can get.
      */
-    let mut flags: Vec<&str> = vec![
+    let irrt_cpp_path = irrt_dir.join("irrt.cpp");
+    let flags: &[&str] = &[
         "--target=wasm32",
         "-x",
         "c++",
-        "-std=c++20",
         "-fno-discard-value-names",
         "-fno-exceptions",
         "-fno-rtti",
+        match env::var("PROFILE").as_deref() {
+            Ok("debug") => "-O0",
+            Ok("release") => "-O3",
+            flavor => panic!("Unknown or missing build flavor {flavor:?}"),
+        },
         "-emit-llvm",
         "-S",
         "-Wall",
@@ -38,22 +52,11 @@ fn main() {
         irrt_cpp_path.to_str().unwrap(),
     ];
 
-    match env::var("PROFILE").as_deref() {
-        Ok("debug") => {
-            flags.push("-O0");
-            flags.push("-DIRRT_DEBUG_ASSERT");
-        }
-        Ok("release") => {
-            flags.push("-O3");
-        }
-        flavor => panic!("Unknown or missing build flavor {flavor:?}"),
-    }
-
     // Tell Cargo to rerun if any file under `irrt_dir` (recursive) changes
     println!("cargo:rerun-if-changed={}", irrt_dir.to_str().unwrap());
 
     // Compile IRRT and capture the LLVM IR output
-    let output = Command::new("clang-irrt")
+    let output = Command::new(CMD_IRRT_CLANG)
         .args(flags)
         .output()
         .map(|o| {
@@ -99,7 +102,9 @@ fn main() {
         file.write_all(filtered_output.as_bytes()).unwrap();
     }
 
-    let mut llvm_as = Command::new("llvm-as-irrt")
+    // Assemble the emitted and filtered IR to .bc
+    // That .bc will be integrated into nac3core's codegen
+    let mut llvm_as = Command::new(CMD_IRRT_LLVM_AS)
         .stdin(Stdio::piped())
         .arg("-o")
         .arg(out_dir.join("irrt.bc"))
@@ -108,3 +113,48 @@ fn main() {
     llvm_as.stdin.as_mut().unwrap().write_all(filtered_output.as_bytes()).unwrap();
     assert!(llvm_as.wait().unwrap().success());
 }
+
+/// Compile `irrt_test.cpp` for testing
+fn compile_irrt_test_cpp() {
+    let out_dir = get_out_dir();
+    let irrt_dir = get_irrt_dir();
+
+    let exe_path = out_dir.join("irrt_test.out"); // Output path of the compiled test executable
+    let irrt_test_cpp_path = irrt_dir.join("irrt_test.cpp");
+    let flags: &[&str] = &[
+        irrt_test_cpp_path.to_str().unwrap(),
+        "-x",
+        "c++",
+        "-I",
+        irrt_dir.to_str().unwrap(),
+        "-g",
+        "-fno-discard-value-names",
+        "-O0",
+        "-Wall",
+        "-Wextra",
+        "-Werror=return-type",
+        "-lm", // for `tgamma()`, `lgamma()`
+        "-o",
+        exe_path.to_str().unwrap(),
+    ];
+
+    Command::new(CMD_IRRT_CLANG_TEST)
+        .args(flags)
+        .output()
+        .map(|o| {
+            assert!(o.status.success(), "{}", std::str::from_utf8(&o.stderr).unwrap());
+            o
+        })
+        .unwrap();
+    println!("cargo:rerun-if-changed={}", irrt_dir.to_str().unwrap());
+}
+
+fn main() {
+    compile_irrt_cpp();
+
+    // https://github.com/rust-lang/cargo/issues/2549
+    // `cargo test -F test` to also build `irrt_test.cpp
+    if cfg!(feature = "test") {
+        compile_irrt_test_cpp();
+    }
+}

nac3core/irrt/irrt.cpp

@@ -1,6 +1,10 @@
-#include "irrt/exception.hpp"
+#define IRRT_DEFINE_TYPEDEF_INTS
-#include "irrt/int_types.hpp"
+#include <irrt_everything.hpp>
-#include "irrt/list.hpp"
+
-#include "irrt/math.hpp"
+/*
-#include "irrt/ndarray.hpp"
+ * All IRRT implementations.
-#include "irrt/slice.hpp"
+ *
+ * We don't have pre-compiled objects, so we are writing all implementations in
+ * headers and concatenate them with `#include` into one massive source file that
+ * contains all the IRRT stuff.
+ */

nac3core/irrt/irrt/artiq_defs.hpp

@@ -0,0 +1,39 @@
+#pragma once
+
+#include <irrt/int_defs.hpp>
+
+/*
+This file defines all ARTIQ-specific structures
+*/
+
+/**
+ * @brief ARTIQ's `cslice` object
+ *
+ * See https://docs.rs/cslice/0.3.0/src/cslice/lib.rs.html#33-37
+ */
+template <typename SizeT>
+struct CSlice {
+    const char *base;
+    SizeT len;
+};
+
+/**
+ * @brief Int type of ARTIQ's `Exception` IDs.
+ */
+typedef uint32_t ExceptionId;
+
+/**
+ * @brief ARTIQ's `Exception` object
+ *
+ * See https://github.com/m-labs/artiq/blob/b0d2705c385f64b6e6711c1726cd9178f40b598e/artiq/firmware/libeh/eh_artiq.rs#L1C1-L17C1
+ */
+template <typename SizeT>
+struct Exception {
+    ExceptionId id;
+    CSlice<SizeT> file;
+    uint32_t line;
+    uint32_t column;
+    CSlice<SizeT> function;
+    CSlice<SizeT> message;
+    uint32_t param;
+};

nac3core/irrt/irrt/core.hpp

@@ -0,0 +1,347 @@
+#pragma once
+
+#include <irrt/int_defs.hpp>
+#include <irrt/slice.hpp>
+#include <irrt/utils.hpp>
+
+// NDArray indices are always `uint32_t`.
+using NDIndexInt = uint32_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;
+}
+
+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, NDIndexInt* 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 NDIndexInt* 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 NDIndexInt* in_idx,
+                                            NDIndexInt* 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" {
+#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 + size + size + 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);
+}
+
+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, NDIndexInt* 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, NDIndexInt* 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 NDIndexInt* 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 NDIndexInt* 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 NDIndexInt* in_idx,
+                                       NDIndexInt* 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 NDIndexInt* in_idx,
+                                         NDIndexInt* out_idx) {
+    __nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx,
+                                           out_idx);
+}
+}  // extern "C"

nac3core/irrt/irrt/cslice.hpp

@@ -1,9 +0,0 @@
-#pragma once
-
-#include "irrt/int_types.hpp"
-
-template<typename SizeT>
-struct CSlice {
-    uint8_t* base;
-    SizeT len;
-};

nac3core/irrt/irrt/debug.hpp

@@ -1,25 +0,0 @@
-#pragma once
-
-// Set in nac3core/build.rs
-#ifdef IRRT_DEBUG_ASSERT
-#define IRRT_DEBUG_ASSERT_BOOL true
-#else
-#define IRRT_DEBUG_ASSERT_BOOL false
-#endif
-
-#define raise_debug_assert(SizeT, 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(SizeT, expr)                                                  \
-    if constexpr (IRRT_DEBUG_ASSERT_BOOL) {                                        \
-        if (!(expr)) {                                                             \
-            raise_debug_assert(SizeT, "Got false.", NO_PARAM, NO_PARAM, NO_PARAM); \
-        }                                                                          \
-    }

nac3core/irrt/irrt/error_context.hpp

@@ -0,0 +1,92 @@
+#pragma once
+
+#include <irrt/artiq_defs.hpp>
+#include <irrt/int_defs.hpp>
+#include <irrt/utils.hpp>
+
+namespace {
+/**
+ * @brief A (limited) set of known Exception IDs usable in IRRT
+ */
+struct ErrorContextExceptions {
+    ExceptionId index_error;
+    ExceptionId value_error;
+    ExceptionId assertion_error;
+    ExceptionId runtime_error;
+    ExceptionId type_error;
+};
+
+/**
+ * @brief The IRRT error context object
+ *
+ * This object contains all the details needed to propagate Python-like Exceptions in
+ * IRRT - within IRRT itself or propagate out of extern calls from nac3core.
+ */
+struct ErrorContext {
+    const ErrorContextExceptions *exceptions;
+
+    // Exception thrown by IRRT
+    ExceptionId exception_id;
+    // Points to empty c-string if there is no thrown Exception
+    const char *msg;
+    uint64_t param1;
+    uint64_t param2;
+    uint64_t param3;
+
+    void initialize(const ErrorContextExceptions *exceptions) {
+        this->exceptions = exceptions;
+        clear_error();
+    }
+
+    void clear_error() {
+        // NOTE: Point the msg to an empty str.
+        // Don't set it to nullptr - to implement `has_exception`
+        this->msg = "";
+    }
+
+    void set_exception(ExceptionId exception_id, const char *msg,
+                       uint64_t param1 = 0, uint64_t param2 = 0,
+                       uint64_t param3 = 0) {
+        this->exception_id = exception_id;
+        this->msg = msg;
+        this->param1 = param1;
+        this->param2 = param2;
+        this->param3 = param3;
+    }
+
+    bool has_exception() { return !cstr_utils::is_empty(msg); }
+
+    template <typename SizeT>
+    void get_exception_str(CSlice<SizeT> *dst_str) {
+        dst_str->base = msg;
+        dst_str->len = (SizeT)cstr_utils::length(msg);
+    }
+};
+}  // namespace
+
+extern "C" {
+void __nac3_error_context_initialize(ErrorContext *errctx,
+                                     ErrorContextExceptions *exceptions) {
+    errctx->initialize(exceptions);
+}
+
+bool __nac3_error_context_has_exception(ErrorContext *errctx) {
+    return errctx->has_exception();
+}
+
+void __nac3_error_context_get_exception_str(ErrorContext *errctx,
+                                            CSlice<int32_t> *dst_str) {
+    errctx->get_exception_str<int32_t>(dst_str);
+}
+
+void __nac3_error_context_get_exception_str64(ErrorContext *errctx,
+                                              CSlice<int64_t> *dst_str) {
+    errctx->get_exception_str<int64_t>(dst_str);
+}
+
+// Used for testing
+void __nac3_error_dummy_raise(ErrorContext *errctx) {
+    errctx->set_exception(errctx->exceptions->runtime_error,
+                          "Error thrown from __nac3_error_dummy_raise");
+}
+}

nac3core/irrt/irrt/exception.hpp

@@ -1,82 +0,0 @@
-#pragma once
-
-#include "irrt/cslice.hpp"
-#include "irrt/int_types.hpp"
-
-/**
- * @brief The int type of ARTIQ exception IDs.
- */
-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;
-}
-
-/**
- * @brief Extern function to `__nac3_raise`
- *
- * 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);
-
-namespace {
-/**
- * @brief NAC3's Exception struct
- */
-template<typename SizeT>
-struct Exception {
-    ExceptionId id;
-    CSlice<SizeT> filename;
-    int32_t line;
-    int32_t column;
-    CSlice<SizeT> function;
-    CSlice<SizeT> msg;
-    int64_t params[3];
-};
-
-constexpr 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) {
-    Exception<SizeT> e = {
-        .id = id,
-        .filename = {.base = reinterpret_cast<const uint8_t*>(filename), .len = __builtin_strlen(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)},
-    };
-    e.params[0] = param0;
-    e.params[1] = param1;
-    e.params[2] = param2;
-    __nac3_raise(reinterpret_cast<void*>(&e));
-    __builtin_unreachable();
-}
-
-/**
- * @brief Raise an exception with location details (location in the IRRT source files).
- * @param SizeT The runtime `size_t` type.
- * @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
- * `NO_PARAM` to indicate they are unused.
- */
-#define raise_exception(SizeT, id, msg, param0, param1, param2) \
-    _raise_exception_helper<SizeT>(id, __FILE__, __LINE__, __FUNCTION__, msg, param0, param1, param2)
-}  // namespace

nac3core/irrt/irrt/int_defs.hpp

@@ -0,0 +1,12 @@
+#pragma once
+
+// This is made toggleable since `irrt_test.cpp` itself would include
+// headers that define these typedefs
+#ifdef IRRT_DEFINE_TYPEDEF_INTS
+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);
+#endif

nac3core/irrt/irrt/int_types.hpp

@@ -1,22 +0,0 @@
-#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;

nac3core/irrt/irrt/list.hpp

@@ -1,75 +0,0 @@
-#pragma once
-
-#include "irrt/int_types.hpp"
-#include "irrt/math_util.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"

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);
-}
-}

nac3core/irrt/irrt/math_util.hpp

@@ -1,13 +0,0 @@
-#pragma once
-
-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) {
-    return a > b ? b : a;
-}
-}  // namespace

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);
-}
-}

nac3core/irrt/irrt/ndarray/basic.hpp

@@ -0,0 +1,315 @@
+#pragma once
+
+#include <irrt/error_context.hpp>
+#include <irrt/int_defs.hpp>
+#include <irrt/ndarray/def.hpp>
+
+namespace {
+namespace ndarray {
+namespace basic {
+namespace util {
+/**
+ * @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(ErrorContext* errctx, SizeT ndims,
+                              const SizeT* shape) {
+    for (SizeT axis = 0; axis < ndims; axis++) {
+        if (shape[axis] < 0) {
+            errctx->set_exception(
+                errctx->exceptions->value_error,
+                "negative dimensions are not allowed; axis {0} "
+                "has dimension {1}",
+                axis, shape[axis]);
+            return;
+        }
+    }
+}
+
+/**
+ * @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 (int32_t i = 0; i < ndims; i++) {
+        int32_t axis = ndims - i - 1;
+        int32_t dim = shape[axis];
+
+        indices[axis] = nth % dim;
+        nth /= dim;
+    }
+}
+}  // namespace util
+
+/**
+ * @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 util::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 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++) {
+        int axis = ndarray->ndims - i - 1;
+        ndarray->strides[axis] = stride_product * ndarray->itemsize;
+        stride_product *= ndarray->shape[axis];
+    }
+}
+
+/**
+ * @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 Return the pointer to the nth (0-based) element in a flattened view of `ndarray`.
+ */
+template <typename SizeT>
+uint8_t* get_nth_pelement(const NDArray<SizeT>* ndarray, SizeT nth) {
+    SizeT* indices = (SizeT*)__builtin_alloca(sizeof(SizeT) * ndarray->ndims);
+    util::set_indices_by_nth(ndarray->ndims, ndarray->shape, indices, nth);
+    return get_pelement_by_indices(ndarray, indices);
+}
+
+/**
+ * @brief Like `get_nth_pelement` but asserts that `nth` is in bounds.
+ */
+template <typename SizeT>
+uint8_t* checked_get_nth_pelement(ErrorContext* errctx,
+                                  const NDArray<SizeT>* ndarray, SizeT nth) {
+    SizeT arr_size = ndarray->size();
+    if (!(0 <= nth && nth < arr_size)) {
+        errctx->set_exception(
+            errctx->exceptions->index_error,
+            "index {0} is out of bounds, valid range is {1} <= index < {2}",
+            nth, 0, arr_size);
+        return 0;
+    }
+    return get_nth_pelement(ndarray, nth);
+}
+
+/**
+ * @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 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>
+void len(ErrorContext* errctx, const NDArray<SizeT>* ndarray,
+         SliceIndex* dst_length) {
+    // numpy prohibits `__len__` on unsized objects
+    if (ndarray->ndims == 0) {
+        errctx->set_exception(errctx->exceptions->type_error,
+                              "len() of unsized object");
+        return;
+    }
+
+    *dst_length = (SliceIndex)ndarray->shape[0];
+}
+
+/**
+ * @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) {
+    __builtin_assume(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);
+    }
+}
+
+/**
+ * @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 = 0; i < ndarray->ndims - 1; i++) {
+        if (ndarray->strides[i] !=
+            ndarray->shape[i + 1] + ndarray->strides[i + 1]) {
+            return false;
+        }
+    }
+
+    return true;
+}
+}  // namespace basic
+}  // namespace ndarray
+}  // namespace
+
+extern "C" {
+using namespace ndarray::basic;
+
+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);
+}
+
+void __nac3_ndarray_len(ErrorContext* errctx, NDArray<int32_t>* ndarray,
+                        SliceIndex* dst_len) {
+    return len(errctx, ndarray, dst_len);
+}
+
+void __nac3_ndarray_len64(ErrorContext* errctx, NDArray<int64_t>* ndarray,
+                          SliceIndex* dst_len) {
+    return len(errctx, ndarray, dst_len);
+}
+
+void __nac3_ndarray_util_assert_shape_no_negative(ErrorContext* errctx,
+                                                  int32_t ndims,
+                                                  int32_t* shape) {
+    util::assert_shape_no_negative(errctx, ndims, shape);
+}
+
+void __nac3_ndarray_util_assert_shape_no_negative64(ErrorContext* errctx,
+                                                    int64_t ndims,
+                                                    int64_t* shape) {
+    util::assert_shape_no_negative(errctx, ndims, shape);
+}
+
+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);
+}
+
+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);
+}
+
+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);
+}
+
+uint8_t* __nac3_ndarray_get_nth_pelement(NDArray<int32_t>* ndarray,
+                                         int32_t index) {
+    return get_nth_pelement(ndarray, index);
+}
+
+uint8_t* __nac3_ndarray_get_nth_pelement64(NDArray<int64_t>* ndarray,
+                                           int64_t index) {
+    return get_nth_pelement(ndarray, index);
+}
+}

nac3core/irrt/irrt/ndarray/broadcast.hpp

@@ -0,0 +1,221 @@
+#pragma once
+
+#include <irrt/error_context.hpp>
+#include <irrt/int_defs.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 {
+namespace util {
+/**
+ * @brief Return true if `src_shape` can broadcast to `dst_shape`.
+ */
+template <typename SizeT>
+bool can_broadcast_shape_to(SizeT target_ndims, const SizeT* target_shape,
+                            SizeT src_ndims, const SizeT* src_shape) {
+    /*
+     *  // See https://numpy.org/doc/stable/user/basics.broadcasting.html
+
+     *  This function handles this example:
+     *  ```
+     *  Image  (3d array): 256 x 256 x 3
+     *  Scale  (1d array):             3
+     *  Result (3d array): 256 x 256 x 3
+     *  ```
+
+     *  Other interesting examples to consider:
+     *  - `can_broadcast_shape_to([3], [1, 1, 1, 1, 3]) == true`
+     *  - `can_broadcast_shape_to([3], [3, 1]) == false`
+     *  - `can_broadcast_shape_to([256, 256, 3], [256, 1, 3]) == true`
+
+     *  In cases when the shapes contain zero(es):
+     *  - `can_broadcast_shape_to([0], [1]) == true`
+     *  - `can_broadcast_shape_to([0], [2]) == false`
+     *  - `can_broadcast_shape_to([0, 4, 0, 0], [1]) == true`
+     *  - `can_broadcast_shape_to([0, 4, 0, 0], [1, 1, 1, 1]) == true`
+     *  - `can_broadcast_shape_to([0, 4, 0, 0], [1, 4, 1, 1]) == true`
+     *  - `can_broadcast_shape_to([4, 3], [0, 3]) == false`
+     *  - `can_broadcast_shape_to([4, 3], [0, 0]) == false`
+     */
+
+    // This is essentially doing the following in Python:
+    // `for target_dim, src_dim in itertools.zip_longest(target_shape[::-1], src_shape[::-1], fillvalue=1)`
+    for (SizeT i = 0; i < max(target_ndims, src_ndims); i++) {
+        SizeT target_dim_i = target_ndims - i - 1;
+        SizeT src_dim_i = src_ndims - i - 1;
+
+        bool target_dim_exists = target_dim_i >= 0;
+        bool src_dim_exists = src_dim_i >= 0;
+
+        SizeT target_dim = target_dim_exists ? target_shape[target_dim_i] : 1;
+        SizeT src_dim = src_dim_exists ? src_shape[src_dim_i] : 1;
+
+        bool ok = src_dim == 1 || target_dim == src_dim;
+        if (!ok) return false;
+    }
+
+    return true;
+}
+
+/**
+ * @brief Performs `np.broadcast_shapes`
+ */
+template <typename SizeT>
+void broadcast_shapes(ErrorContext* errctx, SizeT num_shapes,
+                      const ShapeEntry<SizeT>* shapes, SizeT dst_ndims,
+                      SizeT* 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 it should already know in order to allocate `dst_shape` in the first place.
+    // `dst_shape` must be pre-allocated.
+    // `dst_shape` does not have to be initialized
+
+    // TODO: Implementation is not obvious
+
+    // This is essentially a `mconcat` where the neutral element is `[1, 1, 1, 1, ...]`, and the operation is commutative.
+
+    // Set `dst_shape` to all `1`s.
+    for (SizeT dst_axis = 0; dst_axis < dst_ndims; dst_axis++) {
+        dst_shape[dst_axis] = 0;
+    }
+
+    for (SizeT i = 0; i < num_shapes; i++) {
+        ShapeEntry<SizeT> entry = shapes[i];
+        SizeT entry_axis = entry.ndims - i;
+        SizeT dst_axis = dst_ndims - i;
+
+        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) {
+            // Do nothing
+        } else if (entry_dim == dst_dim) {
+            // Do nothing
+        } else {
+            errctx->set_exception(errctx->exceptions->value_error,
+                                  "shape mismatch: objects cannot be broadcast "
+                                  "to a single shape.");
+            return;
+        }
+    }
+}
+}  // namespace util
+
+/**
+ * @brief Perform `np.broadcast_to(<ndarray>, <target_shape>)` and appropriate assertions.
+ *
+ * Cautious note on https://github.com/numpy/numpy/issues/21744..
+ *
+ * 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(ErrorContext* errctx, const NDArray<SizeT>* src_ndarray,
+                  NDArray<SizeT>* dst_ndarray) {
+    /*
+     * Cautions:
+     *   ```
+     *   xs = np.zeros((4,))
+     *   ys = np.zero((4, 1))
+     *   ys[:] = xs # ok
+     *
+     *   xs = np.zeros((1, 4))
+     *   ys = np.zero((4,))
+     *   ys[:] = xs # allowed
+     *   # However `np.broadcast_to(xs, (4,))` would fails, as per numpy's broadcasting rule.
+     *   # and apparently numpy will "deprecate" this? SEE https://github.com/numpy/numpy/issues/21744
+     *   # This implementation will NOT support this assignment.
+     *   ```
+    */
+
+    if (!ndarray::broadcast::util::can_broadcast_shape_to(
+            dst_ndarray->ndims, dst_ndarray->shape, src_ndarray->ndims,
+            src_ndarray->shape)) {
+        errctx->set_exception(errctx->exceptions->value_error,
+                              "operands could not be broadcast together");
+        return;
+    }
+
+    dst_ndarray->data = src_ndarray->data;
+    dst_ndarray->itemsize = src_ndarray->itemsize;
+
+    // TODO: Implementation is not obvious
+    SizeT stride_product = 1;
+    for (SizeT i = 0; i < max(src_ndarray->ndims, dst_ndarray->ndims); i++) {
+        SizeT src_ndarray_dim_i = src_ndarray->ndims - i - 1;
+        SizeT dst_dim_i = dst_ndarray->ndims - i - 1;
+
+        bool src_ndarray_dim_exists = src_ndarray_dim_i >= 0;
+        bool dst_dim_exists = dst_dim_i >= 0;
+
+        bool c1 = src_ndarray_dim_exists &&
+                  src_ndarray->shape[src_ndarray_dim_i] == 1;
+        bool c2 = dst_dim_exists && dst_ndarray->shape[dst_dim_i] != 1;
+        if (!src_ndarray_dim_exists || (c1 && c2)) {
+            dst_ndarray->strides[dst_dim_i] = 0;  // Freeze it in-place
+        } else {
+            dst_ndarray->strides[dst_dim_i] =
+                stride_product * src_ndarray->itemsize;
+            stride_product *= src_ndarray->shape[src_ndarray_dim_i];
+        }
+    }
+}
+}  // namespace broadcast
+}  // namespace ndarray
+}  // namespace
+
+extern "C" {
+using namespace ndarray::broadcast;
+
+void __nac3_ndarray_broadcast_to(ErrorContext* errctx,
+                                 NDArray<int32_t>* src_ndarray,
+                                 NDArray<int32_t>* dst_ndarray) {
+    broadcast_to(errctx, src_ndarray, dst_ndarray);
+}
+
+void __nac3_ndarray_broadcast_to64(ErrorContext* errctx,
+                                   NDArray<int64_t>* src_ndarray,
+                                   NDArray<int64_t>* dst_ndarray) {
+    broadcast_to(errctx, src_ndarray, dst_ndarray);
+}
+
+void __nac3_ndarray_broadcast_shapes(ErrorContext* errctx, int32_t num_shapes,
+                                     const ShapeEntry<int32_t>* shapes,
+                                     int32_t dst_ndims, int32_t* dst_shape) {
+    ndarray::broadcast::util::broadcast_shapes(errctx, num_shapes, shapes,
+                                               dst_ndims, dst_shape);
+}
+
+void __nac3_ndarray_broadcast_shapes64(ErrorContext* errctx, int64_t num_shapes,
+                                       const ShapeEntry<int64_t>* shapes,
+                                       int64_t dst_ndims, int64_t* dst_shape) {
+    ndarray::broadcast::util::broadcast_shapes(errctx, num_shapes, shapes,
+                                               dst_ndims, dst_shape);
+}
+}

nac3core/irrt/irrt/ndarray/def.hpp

@@ -0,0 +1,44 @@
+#pragma once
+
+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

nac3core/irrt/irrt/ndarray/indexing.hpp

@@ -0,0 +1,200 @@
+#pragma once
+
+#include <irrt/error_context.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
+ *
+ * See https://numpy.org/doc/stable/user/basics.indexing.html#single-element-indexing
+ *
+ * `data` points to a `SliceIndex`.
+ */
+const NDIndexType ND_INDEX_TYPE_SINGLE_ELEMENT = 0;
+/**
+ * @brief A slice index
+ *
+ * See https://numpy.org/doc/stable/user/basics.indexing.html#slicing-and-striding
+ *
+ * `data` points to a `UserRange`.
+ */
+const NDIndexType ND_INDEX_TYPE_SLICE = 1;
+
+/**
+ * @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 {
+namespace util {
+
+/**
+ * @brief Return the expected rank of the resulting ndarray
+ * created by indexing an ndarray of rank `ndims` using `indexes`.
+ */
+template <typename SizeT>
+void deduce_ndims_after_indexing(ErrorContext* errctx, SizeT* final_ndims,
+                                 SizeT ndims, SizeT num_indexes,
+                                 const NDIndex* indexes) {
+    if (num_indexes > ndims) {
+        errctx->set_exception(errctx->exceptions->index_error,
+                              "too many indices for array: array is "
+                              "{0}-dimensional, but {1} were indexed",
+                              ndims, num_indexes);
+        return;
+    }
+
+    *final_ndims = ndims;
+    for (SizeT i = 0; i < num_indexes; i++) {
+        if (indexes[i].type == ND_INDEX_TYPE_SINGLE_ELEMENT) {
+            // An index demotes the rank by 1
+            (*final_ndims)--;
+        }
+    }
+}
+}  // namespace util
+
+/**
+ * @brief Perform ndarray "basic indexing" (https://numpy.org/doc/stable/user/basics.indexing.html#basic-indexing)
+ *
+ * This is function very similar to performing `dst_ndarray = src_ndarray[indexes]` in Python (where the variables
+ * can all be found in the parameter of this function).
+ *
+ * In other words, this function takes in an ndarray (`src_ndarray`), index it with `indexes`, and return the
+ * indexed array (by writing the result to `dst_ndarray`).
+ *
+ * This function also does proper assertions on `indexes`.
+ *
+ * # 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 `indexes`.
+ *   - `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 indexes Indexes 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(ErrorContext* errctx, SizeT num_indexes, const NDIndex* indexes,
+           const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
+    // Reference code: https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L652
+
+    dst_ndarray->data = src_ndarray->data;
+    dst_ndarray->itemsize = src_ndarray->itemsize;
+
+    SizeT src_axis = 0;
+    SizeT dst_axis = 0;
+
+    for (SliceIndex i = 0; i < num_indexes; i++) {
+        const NDIndex* index = &indexes[i];
+        if (index->type == ND_INDEX_TYPE_SINGLE_ELEMENT) {
+            SliceIndex input = *((SliceIndex*)index->data);
+            SliceIndex k = slice::resolve_index_in_length(
+                src_ndarray->shape[src_axis], input);
+
+            if (k == slice::OUT_OF_BOUNDS) {
+                errctx->set_exception(errctx->exceptions->index_error,
+                                      "index {0} is out of bounds for axis {1} "
+                                      "with size {2}",
+                                      input, src_axis,
+                                      src_ndarray->shape[src_axis]);
+                return;
+            }
+
+            dst_ndarray->data += k * src_ndarray->strides[src_axis];
+
+            src_axis++;
+        } else if (index->type == ND_INDEX_TYPE_SLICE) {
+            UserSlice* input = (UserSlice*)index->data;
+
+            Slice slice;
+            input->indices_checked(errctx, src_ndarray->shape[src_axis],
+                                   &slice);
+            if (errctx->has_exception()) {
+                return;
+            }
+
+            dst_ndarray->data +=
+                (SizeT)slice.start * src_ndarray->strides[src_axis];
+            dst_ndarray->strides[dst_axis] =
+                ((SizeT)slice.step) * src_ndarray->strides[src_axis];
+            dst_ndarray->shape[dst_axis] = (SizeT)slice.len();
+
+            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];
+    }
+}
+}  // namespace indexing
+}  // namespace ndarray
+}  // namespace
+
+extern "C" {
+using namespace ndarray::indexing;
+
+void __nac3_ndarray_indexing_deduce_ndims_after_indexing(
+    ErrorContext* errctx, int32_t* result, int32_t ndims, int32_t num_indexes,
+    const NDIndex* indexes) {
+    ndarray::indexing::util::deduce_ndims_after_indexing(errctx, result, ndims,
+                                                         num_indexes, indexes);
+}
+
+void __nac3_ndarray_indexing_deduce_ndims_after_indexing64(
+    ErrorContext* errctx, int64_t* result, int64_t ndims, int64_t num_indexes,
+    const NDIndex* indexes) {
+    ndarray::indexing::util::deduce_ndims_after_indexing(errctx, result, ndims,
+                                                         num_indexes, indexes);
+}
+
+void __nac3_ndarray_index(ErrorContext* errctx, int32_t num_indexes,
+                          NDIndex* indexes, NDArray<int32_t>* src_ndarray,
+                          NDArray<int32_t>* dst_ndarray) {
+    index(errctx, num_indexes, indexes, src_ndarray, dst_ndarray);
+}
+
+void __nac3_ndarray_index64(ErrorContext* errctx, int64_t num_indexes,
+                            NDIndex* indexes, NDArray<int64_t>* src_ndarray,
+                            NDArray<int64_t>* dst_ndarray) {
+    index(errctx, num_indexes, indexes, src_ndarray, dst_ndarray);
+}
+}

nac3core/irrt/irrt/ndarray/reshape.hpp

@@ -0,0 +1,117 @@
+#pragma once
+
+#include <irrt/error_context.hpp>
+#include <irrt/int_defs.hpp>
+#include <irrt/ndarray/def.hpp>
+
+namespace {
+namespace ndarray {
+namespace reshape {
+namespace util {
+
+/**
+ * @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(ErrorContext* errctx, 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.
+                    errctx->set_exception(
+                        errctx->exceptions->value_error,
+                        "can only specify one unknown dimension");
+                    return;
+                } 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...
+
+                errctx->set_exception(
+                    errctx->exceptions->value_error,
+                    "Found negative dimension {0} on axis {1}", dim, axis_i);
+                return;
+            }
+        } 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) {
+        errctx->set_exception(
+            errctx->exceptions->value_error,
+            "cannot reshape array of size {0} into given shape", size);
+        return;
+    }
+}
+}  // namespace util
+}  // namespace reshape
+}  // namespace ndarray
+}  // namespace
+
+extern "C" {
+
+void __nac3_ndarray_resolve_and_check_new_shape(ErrorContext* errctx,
+                                                int32_t size, int32_t new_ndims,
+                                                int32_t* new_shape) {
+    ndarray::reshape::util::resolve_and_check_new_shape(errctx, size, new_ndims,
+                                                        new_shape);
+}
+
+void __nac3_ndarray_resolve_and_check_new_shape64(ErrorContext* errctx,
+                                                  int64_t size,
+                                                  int64_t new_ndims,
+                                                  int64_t* new_shape) {
+    ndarray::reshape::util::resolve_and_check_new_shape(errctx, size, new_ndims,
+                                                        new_shape);
+}
+}

nac3core/irrt/irrt/slice.hpp

@@ -1,28 +1,166 @@
 #pragma once
 
-#include "irrt/int_types.hpp"
+#include <irrt/error_context.hpp>
+#include <irrt/int_defs.hpp>
+#include <irrt/slice.hpp>
+#include <irrt/utils.hpp>
 
-extern "C" {
+// The type of an index or a value describing the length of a
-SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
+// range/slice is always `int32_t`.
-    if (i < 0) {
+using SliceIndex = int32_t;
-        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) {
+namespace {
-    SliceIndex diff = end - start;
+
-    if (diff > 0 && step > 0) {
+/**
-        return ((diff - 1) / step) + 1;
+ * @brief A Python-like slice with resolved indices.
-    } else if (diff < 0 && step < 0) {
+ *
-        return ((diff + 1) / step) + 1;
+ * "Resolved indices" means that `start` and `stop` must be positive and are
+ * bound to a known length.
+ */
+struct Slice {
+    SliceIndex start;
+    SliceIndex stop;
+    SliceIndex step;
+
+    /**
+     * @brief Calculate and return the length / the number of the slice.
+     * 
+     * If this were a Python range, this function would be `len(range(start, stop, step))`.
+     */
+    SliceIndex len() {
+        SliceIndex diff = stop - 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;
+        }
+    }
+};
+
+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).
+ *
+ */
+SliceIndex resolve_index_in_length_clamped(SliceIndex length,
+                                           SliceIndex index) {
+    if (index < 0) {
+        return max<SliceIndex>(length + index, 0);
     } else {
-        return 0;
+        return min<SliceIndex>(length, index);
     }
 }
-}
+
+const SliceIndex OUT_OF_BOUNDS = -1;
+
+/**
+ * @brief Like `resolve_index_in_length_clamped`, but returns `OUT_OF_BOUNDS`
+ * if `index` is out of bounds.
+ */
+SliceIndex resolve_index_in_length(SliceIndex length, SliceIndex index) {
+    SliceIndex resolved = index < 0 ? length + index : index;
+    if (0 <= resolved && resolved < length) {
+        return resolved;
+    } else {
+        return OUT_OF_BOUNDS;
+    }
+}
+}  // namespace slice
+
+/**
+ * @brief A Python-like slice with **unresolved** indices.
+ */
+struct UserSlice {
+    bool start_defined;
+    SliceIndex start;
+
+    bool stop_defined;
+    SliceIndex stop;
+
+    bool step_defined;
+    SliceIndex step;
+
+    UserSlice() { this->reset(); }
+
+    void reset() {
+        this->start_defined = false;
+        this->stop_defined = false;
+        this->step_defined = false;
+    }
+
+    void set_start(SliceIndex start) {
+        this->start_defined = true;
+        this->start = start;
+    }
+
+    void set_stop(SliceIndex stop) {
+        this->stop_defined = true;
+        this->stop = stop;
+    }
+
+    void set_step(SliceIndex step) {
+        this->step_defined = true;
+        this->step = step;
+    }
+
+    /**
+     * @brief Resolve this slice.
+     *
+     * In Python, this would be `slice(start, stop, step).indices(length)`.
+     *
+     * @return A `Slice` with the resolved indices.
+     */
+    Slice indices(SliceIndex length) {
+        Slice result;
+
+        result.step = step_defined ? step : 1;
+        bool step_is_negative = result.step < 0;
+
+        if (start_defined) {
+            result.start =
+                slice::resolve_index_in_length_clamped(length, start);
+        } else {
+            result.start = step_is_negative ? length - 1 : 0;
+        }
+
+        if (stop_defined) {
+            result.stop = slice::resolve_index_in_length_clamped(length, stop);
+        } else {
+            result.stop = step_is_negative ? -1 : length;
+        }
+
+        return result;
+    }
+
+    /**
+     * @brief Like `.indices()` but with assertions.
+     */
+    void indices_checked(ErrorContext* errctx, SliceIndex length,
+                         Slice* result) {
+        if (length < 0) {
+            errctx->set_exception(errctx->exceptions->value_error,
+                                  "length should not be negative, got {0}",
+                                  length);
+            return;
+        }
+
+        if (this->step_defined && this->step == 0) {
+            errctx->set_exception(errctx->exceptions->value_error,
+                                  "slice step cannot be zero");
+            return;
+        }
+
+        *result = this->indices(length);
+    }
+};
+}  // namespace

nac3core/irrt/irrt/utils.hpp

@@ -0,0 +1,104 @@
+#pragma once
+
+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) {
+    return a > b ? b : a;
+}
+
+/**
+ * @brief Compare contents of two arrays with the same length.
+ */
+template <typename T>
+bool arrays_match(int len, T* as, T* bs) {
+    for (int i = 0; i < len; i++) {
+        if (as[i] != bs[i]) return false;
+    }
+    return true;
+}
+
+namespace cstr_utils {
+/**
+ * @brief Return true if `str` is empty.
+ */
+bool is_empty(const char* str) { return str[0] == '\0'; }
+
+/**
+ * @brief Implementation of `strcmp()`
+ */
+int8_t compare(const char* a, const char* b) {
+    uint32_t i = 0;
+    while (true) {
+        if (a[i] < b[i]) {
+            return -1;
+        } else if (a[i] > b[i]) {
+            return 1;
+        } else {
+            if (a[i] == '\0') {
+                return 0;
+            } else {
+                i++;
+            }
+        }
+    }
+}
+
+/**
+ * @brief Return true two strings have the same content.
+ */
+int8_t equal(const char* a, const char* b) { return compare(a, b) == 0; }
+
+/**
+ * @brief Implementation of `strlen()`.
+ */
+uint32_t length(const char* str) {
+    uint32_t length = 0;
+    while (*str != '\0') {
+        length++;
+        str++;
+    }
+    return length;
+}
+
+/**
+ * @brief Copy a null-terminated string to a buffer with limited size and guaranteed null-termination.
+ *
+ * `dst_max_size` must be greater than 0, otherwise this function has undefined behavior.
+ *
+ * This function attempts to copy everything from `src` from `dst`, and *always* null-terminates `dst`.
+ *
+ * If the size of `dst` is too small, the final byte (`dst[dst_max_size - 1]`) of `dst` will be set to
+ * the null terminator.
+ *
+ * @param src String to copy from.
+ * @param dst Buffer to copy string to.
+ * @param dst_max_size
+ *   Number of bytes of this buffer, including the space needed for the null terminator.
+ *   Must be greater than 0.
+ * @return If `dst` is too small to contain everything in `src`.
+ */
+bool copy(const char* src, char* dst, uint32_t dst_max_size) {
+    for (uint32_t i = 0; i < dst_max_size; i++) {
+        bool is_last = i + 1 == dst_max_size;
+        if (is_last && src[i] != '\0') {
+            dst[i] = '\0';
+            return false;
+        }
+
+        if (src[i] == '\0') {
+            dst[i] = '\0';
+            return true;
+        }
+
+        dst[i] = src[i];
+    }
+
+    __builtin_unreachable();
+}
+}  // namespace cstr_utils
+}  // namespace

nac3core/irrt/irrt_everything.hpp

@@ -0,0 +1,13 @@
+#pragma once
+
+#include <irrt/artiq_defs.hpp>
+#include <irrt/core.hpp>
+#include <irrt/error_context.hpp>
+#include <irrt/int_defs.hpp>
+#include <irrt/ndarray/basic.hpp>
+#include <irrt/ndarray/broadcast.hpp>
+#include <irrt/ndarray/def.hpp>
+#include <irrt/ndarray/indexing.hpp>
+#include <irrt/ndarray/reshape.hpp>
+#include <irrt/slice.hpp>
+#include <irrt/utils.hpp>

nac3core/irrt/irrt_test.cpp

@@ -0,0 +1,20 @@
+// This file will be compiled like a real C++ program,
+// and we do have the luxury to use the standard libraries.
+// That is if the nix flakes do not have issues... especially on msys2...
+#include <cstdint>
+#include <cstdio>
+#include <cstdlib>
+#include <test/test_core.hpp>
+#include <test/test_ndarray_basic.hpp>
+#include <test/test_ndarray_broadcast.hpp>
+#include <test/test_ndarray_indexing.hpp>
+#include <test/test_slice.hpp>
+
+int main() {
+    test::core::run();
+    test::slice::run();
+    test::ndarray_basic::run();
+    test::ndarray_indexing::run();
+    test::ndarray_broadcast::run();
+    return 0;
+}

nac3core/irrt/test/includes.hpp

@@ -0,0 +1,11 @@
+#pragma once
+
+#include <cstdint>
+#include <cstdio>
+#include <cstdlib>
+#include <irrt_everything.hpp>
+#include <test/util.hpp>
+
+/*
+    Include this header for every test_*.cpp
+*/

nac3core/irrt/test/test_core.hpp

@@ -0,0 +1,16 @@
+#pragma once
+
+#include <test/includes.hpp>
+
+namespace test {
+namespace core {
+void test_int_exp() {
+    BEGIN_TEST();
+
+    assert_values_match(125, __nac3_int_exp_impl<int32_t>(5, 3));
+    assert_values_match(3125, __nac3_int_exp_impl<int32_t>(5, 5));
+}
+
+void run() { test_int_exp(); }
+}  // namespace core
+}  // namespace test

nac3core/irrt/test/test_ndarray_basic.hpp

@@ -0,0 +1,30 @@
+#pragma once
+
+#include <test/includes.hpp>
+
+namespace test {
+namespace ndarray_basic {
+void test_calc_size_from_shape_normal() {
+    // Test shapes with normal values
+    BEGIN_TEST();
+
+    int32_t shape[4] = {2, 3, 5, 7};
+    assert_values_match(
+        210, ndarray::basic::util::calc_size_from_shape<int32_t>(4, shape));
+}
+
+void test_calc_size_from_shape_has_zero() {
+    // Test shapes with 0 in them
+    BEGIN_TEST();
+
+    int32_t shape[4] = {2, 0, 5, 7};
+    assert_values_match(
+        0, ndarray::basic::util::calc_size_from_shape<int32_t>(4, shape));
+}
+
+void run() {
+    test_calc_size_from_shape_normal();
+    test_calc_size_from_shape_has_zero();
+}
+}  // namespace ndarray_basic
+}  // namespace test

nac3core/irrt/test/test_ndarray_broadcast.hpp

@@ -0,0 +1,129 @@
+#pragma once
+
+#include <test/includes.hpp>
+
+namespace test {
+namespace ndarray_broadcast {
+void test_can_broadcast_shape() {
+    BEGIN_TEST();
+
+    assert_values_match(true,
+                        ndarray::broadcast::util::can_broadcast_shape_to(
+                            1, (int32_t[]){3}, 5, (int32_t[]){1, 1, 1, 1, 3}));
+    assert_values_match(false, ndarray::broadcast::util::can_broadcast_shape_to(
+                                   1, (int32_t[]){3}, 2, (int32_t[]){3, 1}));
+    assert_values_match(true, ndarray::broadcast::util::can_broadcast_shape_to(
+                                  1, (int32_t[]){3}, 1, (int32_t[]){3}));
+    assert_values_match(false, ndarray::broadcast::util::can_broadcast_shape_to(
+                                   1, (int32_t[]){1}, 1, (int32_t[]){3}));
+    assert_values_match(true, ndarray::broadcast::util::can_broadcast_shape_to(
+                                  1, (int32_t[]){1}, 1, (int32_t[]){1}));
+    assert_values_match(
+        true, ndarray::broadcast::util::can_broadcast_shape_to(
+                  3, (int32_t[]){256, 256, 3}, 3, (int32_t[]){256, 1, 3}));
+    assert_values_match(true,
+                        ndarray::broadcast::util::can_broadcast_shape_to(
+                            3, (int32_t[]){256, 256, 3}, 1, (int32_t[]){3}));
+    assert_values_match(false,
+                        ndarray::broadcast::util::can_broadcast_shape_to(
+                            3, (int32_t[]){256, 256, 3}, 1, (int32_t[]){2}));
+    assert_values_match(true,
+                        ndarray::broadcast::util::can_broadcast_shape_to(
+                            3, (int32_t[]){256, 256, 3}, 1, (int32_t[]){1}));
+
+    // In cases when the shapes contain zero(es)
+    assert_values_match(true, ndarray::broadcast::util::can_broadcast_shape_to(
+                                  1, (int32_t[]){0}, 1, (int32_t[]){1}));
+    assert_values_match(false, ndarray::broadcast::util::can_broadcast_shape_to(
+                                   1, (int32_t[]){0}, 1, (int32_t[]){2}));
+    assert_values_match(true,
+                        ndarray::broadcast::util::can_broadcast_shape_to(
+                            4, (int32_t[]){0, 4, 0, 0}, 1, (int32_t[]){1}));
+    assert_values_match(
+        true, ndarray::broadcast::util::can_broadcast_shape_to(
+                  4, (int32_t[]){0, 4, 0, 0}, 4, (int32_t[]){1, 1, 1, 1}));
+    assert_values_match(
+        true, ndarray::broadcast::util::can_broadcast_shape_to(
+                  4, (int32_t[]){0, 4, 0, 0}, 4, (int32_t[]){1, 4, 1, 1}));
+    assert_values_match(false, ndarray::broadcast::util::can_broadcast_shape_to(
+                                   2, (int32_t[]){4, 3}, 2, (int32_t[]){0, 3}));
+    assert_values_match(false, ndarray::broadcast::util::can_broadcast_shape_to(
+                                   2, (int32_t[]){4, 3}, 2, (int32_t[]){0, 0}));
+}
+
+void test_ndarray_broadcast() {
+    /*
+    # array = np.array([[19.9, 29.9, 39.9, 49.9]], dtype=np.float64)
+    # >>> [[19.9 29.9 39.9 49.9]]
+    #
+    # array = np.broadcast_to(array, (2, 3, 4))
+    # >>> [[[19.9 29.9 39.9 49.9]
+    # >>>   [19.9 29.9 39.9 49.9]
+    # >>>   [19.9 29.9 39.9 49.9]]
+    # >>>  [[19.9 29.9 39.9 49.9]
+    # >>>   [19.9 29.9 39.9 49.9]
+    # >>>   [19.9 29.9 39.9 49.9]]]
+    #
+    # assery array.strides == (0, 0, 8)
+
+    */
+    BEGIN_TEST();
+
+    double in_data[4] = {19.9, 29.9, 39.9, 49.9};
+    const int32_t in_ndims = 2;
+    int32_t in_shape[in_ndims] = {1, 4};
+    int32_t in_strides[in_ndims] = {};
+    NDArray<int32_t> ndarray = {.data = (uint8_t*)in_data,
+                                .itemsize = sizeof(double),
+                                .ndims = in_ndims,
+                                .shape = in_shape,
+                                .strides = in_strides};
+    ndarray::basic::set_strides_by_shape(&ndarray);
+
+    const int32_t dst_ndims = 3;
+    int32_t dst_shape[dst_ndims] = {2, 3, 4};
+    int32_t dst_strides[dst_ndims] = {};
+    NDArray<int32_t> dst_ndarray = {
+        .ndims = dst_ndims, .shape = dst_shape, .strides = dst_strides};
+
+    ErrorContext errctx = create_testing_errctx();
+    ndarray::broadcast::broadcast_to(&errctx, &ndarray, &dst_ndarray);
+    assert_errctx_no_exception(&errctx);
+
+    assert_arrays_match(dst_ndims, ((int32_t[]){0, 0, 8}), dst_ndarray.strides);
+
+    assert_values_match(19.9,
+                        *((double*)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, ((int32_t[]){0, 0, 0}))));
+    assert_values_match(29.9,
+                        *((double*)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, ((int32_t[]){0, 0, 1}))));
+    assert_values_match(39.9,
+                        *((double*)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, ((int32_t[]){0, 0, 2}))));
+    assert_values_match(49.9,
+                        *((double*)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, ((int32_t[]){0, 0, 3}))));
+    assert_values_match(19.9,
+                        *((double*)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, ((int32_t[]){0, 1, 0}))));
+    assert_values_match(29.9,
+                        *((double*)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, ((int32_t[]){0, 1, 1}))));
+    assert_values_match(39.9,
+                        *((double*)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, ((int32_t[]){0, 1, 2}))));
+    assert_values_match(49.9,
+                        *((double*)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, ((int32_t[]){0, 1, 3}))));
+    assert_values_match(49.9,
+                        *((double*)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, ((int32_t[]){1, 2, 3}))));
+}
+
+void run() {
+    test_can_broadcast_shape();
+    test_ndarray_broadcast();
+}
+}  // namespace ndarray_broadcast
+}  // namespace test

nac3core/irrt/test/test_ndarray_indexing.hpp

@@ -0,0 +1,220 @@
+#pragma once
+
+#include <test/includes.hpp>
+
+namespace test {
+namespace ndarray_indexing {
+void test_normal_1() {
+    /*
+        Reference Python code:
+        ```python
+        ndarray = np.arange(12, dtype=np.float64).reshape((3, 4));
+        # array([[ 0.,  1.,  2.,  3.],
+        #        [ 4.,  5.,  6.,  7.],
+        #        [ 8.,  9., 10., 11.]])
+
+        dst_ndarray = ndarray[-2:, 1::2]
+        # array([[ 5.,  7.],
+        #        [ 9., 11.]])
+
+        assert dst_ndarray.shape == (2, 2)
+        assert dst_ndarray.strides == (32, 16)
+        assert dst_ndarray[0, 0] == 5.0
+        assert dst_ndarray[0, 1] == 7.0
+        assert dst_ndarray[1, 0] == 9.0
+        assert dst_ndarray[1, 1] == 11.0
+        ```
+    */
+    BEGIN_TEST();
+
+    // Prepare src_ndarray
+    double src_data[12] = {0.0, 1.0, 2.0, 3.0, 4.0,  5.0,
+                           6.0, 7.0, 8.0, 9.0, 10.0, 11.0};
+    int32_t src_itemsize = sizeof(double);
+    const int32_t src_ndims = 2;
+    int32_t src_shape[src_ndims] = {3, 4};
+    int32_t src_strides[src_ndims] = {};
+    NDArray<int32_t> src_ndarray = {.data = (uint8_t *)src_data,
+                                    .itemsize = src_itemsize,
+                                    .ndims = src_ndims,
+                                    .shape = src_shape,
+                                    .strides = src_strides};
+    ndarray::basic::set_strides_by_shape(&src_ndarray);
+
+    // Prepare dst_ndarray
+    const int32_t dst_ndims = 2;
+    int32_t dst_shape[dst_ndims] = {999, 999};    // Empty values
+    int32_t dst_strides[dst_ndims] = {999, 999};  // Empty values
+    NDArray<int32_t> dst_ndarray = {.data = nullptr,
+                                    .ndims = dst_ndims,
+                                    .shape = dst_shape,
+                                    .strides = dst_strides};
+
+    // Create the subscripts in `ndarray[-2::, 1::2]`
+    UserSlice subscript_1;
+    subscript_1.set_start(-2);
+
+    UserSlice subscript_2;
+    subscript_2.set_start(1);
+    subscript_2.set_step(2);
+
+    const int32_t num_indexes = 2;
+    NDIndex indexes[num_indexes] = {
+        {.type = ND_INDEX_TYPE_SLICE, .data = (uint8_t *)&subscript_1},
+        {.type = ND_INDEX_TYPE_SLICE, .data = (uint8_t *)&subscript_2}};
+
+    ErrorContext errctx = create_testing_errctx();
+    ndarray::indexing::index(&errctx, num_indexes, indexes, &src_ndarray,
+                             &dst_ndarray);
+    assert_errctx_no_exception(&errctx);
+
+    int32_t expected_shape[dst_ndims] = {2, 2};
+    int32_t expected_strides[dst_ndims] = {32, 16};
+
+    assert_arrays_match(dst_ndims, expected_shape, dst_ndarray.shape);
+    assert_arrays_match(dst_ndims, expected_strides, dst_ndarray.strides);
+
+    // dst_ndarray[0, 0]
+    assert_values_match(5.0,
+                        *((double *)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, (int32_t[dst_ndims]){0, 0})));
+    // dst_ndarray[0, 1]
+    assert_values_match(7.0,
+                        *((double *)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, (int32_t[dst_ndims]){0, 1})));
+    // dst_ndarray[1, 0]
+    assert_values_match(9.0,
+                        *((double *)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, (int32_t[dst_ndims]){1, 0})));
+    // dst_ndarray[1, 1]
+    assert_values_match(11.0,
+                        *((double *)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, (int32_t[dst_ndims]){1, 1})));
+}
+
+void test_normal_2() {
+    /*
+        ```python
+        ndarray = np.arange(12, dtype=np.float64).reshape((3, 4))
+        # array([[ 0.,  1.,  2.,  3.],
+        #        [ 4.,  5.,  6.,  7.],
+        #        [ 8.,  9., 10., 11.]])
+
+        dst_ndarray = ndarray[2, ::-2]
+        # array([11.,  9.])
+
+        assert dst_ndarray.shape == (2,)
+        assert dst_ndarray.strides == (-16,)
+        assert dst_ndarray[0] == 11.0
+        assert dst_ndarray[1] == 9.0
+        ```
+    */
+    BEGIN_TEST();
+
+    // Prepare src_ndarray
+    double src_data[12] = {0.0, 1.0, 2.0, 3.0, 4.0,  5.0,
+                           6.0, 7.0, 8.0, 9.0, 10.0, 11.0};
+    int32_t src_itemsize = sizeof(double);
+    const int32_t src_ndims = 2;
+    int32_t src_shape[src_ndims] = {3, 4};
+    int32_t src_strides[src_ndims] = {};
+    NDArray<int32_t> src_ndarray = {.data = (uint8_t *)src_data,
+                                    .itemsize = src_itemsize,
+                                    .ndims = src_ndims,
+                                    .shape = src_shape,
+                                    .strides = src_strides};
+    ndarray::basic::set_strides_by_shape(&src_ndarray);
+
+    // Prepare dst_ndarray
+    const int32_t dst_ndims = 1;
+    int32_t dst_shape[dst_ndims] = {999};    // Empty values
+    int32_t dst_strides[dst_ndims] = {999};  // Empty values
+    NDArray<int32_t> dst_ndarray = {.data = nullptr,
+                                    .ndims = dst_ndims,
+                                    .shape = dst_shape,
+                                    .strides = dst_strides};
+
+    // Create the subscripts in `ndarray[2, ::-2]`
+    int32_t subscript_1 = 2;
+
+    UserSlice subscript_2;
+    subscript_2.set_step(-2);
+
+    const int32_t num_indexes = 2;
+    NDIndex indexes[num_indexes] = {
+        {.type = ND_INDEX_TYPE_SINGLE_ELEMENT, .data = (uint8_t *)&subscript_1},
+        {.type = ND_INDEX_TYPE_SLICE, .data = (uint8_t *)&subscript_2}};
+
+    ErrorContext errctx = create_testing_errctx();
+    ndarray::indexing::index(&errctx, num_indexes, indexes, &src_ndarray,
+                             &dst_ndarray);
+    assert_errctx_no_exception(&errctx);
+
+    int32_t expected_shape[dst_ndims] = {2};
+    int32_t expected_strides[dst_ndims] = {-16};
+    assert_arrays_match(dst_ndims, expected_shape, dst_ndarray.shape);
+    assert_arrays_match(dst_ndims, expected_strides, dst_ndarray.strides);
+
+    assert_values_match(11.0,
+                        *((double *)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, (int32_t[dst_ndims]){0})));
+    assert_values_match(9.0,
+                        *((double *)ndarray::basic::get_pelement_by_indices(
+                            &dst_ndarray, (int32_t[dst_ndims]){1})));
+}
+
+void test_index_subscript_out_of_bounds() {
+    /*
+        # Consider `my_array`
+
+        print(my_array.shape)
+        # (4, 5, 6)
+
+        my_array[2, 100] # error, index subscript at axis 1 is out of bounds
+    */
+    BEGIN_TEST();
+
+    // Prepare src_ndarray
+    const int32_t src_ndims = 2;
+    int32_t src_shape[src_ndims] = {3, 4};
+    int32_t src_strides[src_ndims] = {};
+    NDArray<int32_t> src_ndarray = {
+        .data = (uint8_t *)nullptr,  // placeholder, we wouldn't access it
+        .itemsize = sizeof(double),  // placeholder
+        .ndims = src_ndims,
+        .shape = src_shape,
+        .strides = src_strides};
+    ndarray::basic::set_strides_by_shape(&src_ndarray);
+
+    // Create the subscripts in `my_array[2, 100]`
+    int32_t subscript_1 = 2;
+    int32_t subscript_2 = 100;
+
+    const int32_t num_indexes = 2;
+    NDIndex indexes[num_indexes] = {
+        {.type = ND_INDEX_TYPE_SINGLE_ELEMENT, .data = (uint8_t *)&subscript_1},
+        {.type = ND_INDEX_TYPE_SINGLE_ELEMENT,
+         .data = (uint8_t *)&subscript_2}};
+
+    // Prepare dst_ndarray
+    const int32_t dst_ndims = 0;
+    int32_t dst_shape[dst_ndims] = {};
+    int32_t dst_strides[dst_ndims] = {};
+    NDArray<int32_t> dst_ndarray = {.data = nullptr,  // placehloder
+                                    .ndims = dst_ndims,
+                                    .shape = dst_shape,
+                                    .strides = dst_strides};
+
+    ErrorContext errctx = create_testing_errctx();
+    ndarray::indexing::index(&errctx, num_indexes, indexes, &src_ndarray,
+                             &dst_ndarray);
+    assert_errctx_has_exception(&errctx, errctx.exceptions->index_error);
+}
+
+void run() {
+    test_normal_1();
+    test_normal_2();
+    test_index_subscript_out_of_bounds();
+}
+}  // namespace ndarray_indexing
+}  // namespace test

nac3core/irrt/test/test_slice.hpp

@@ -0,0 +1,92 @@
+#pragma once
+
+#include <irrt_everything.hpp>
+#include <test/includes.hpp>
+
+namespace test {
+namespace slice {
+void test_slice_normal() {
+    // Normal situation
+    BEGIN_TEST();
+
+    UserSlice user_slice;
+    user_slice.set_stop(5);
+
+    Slice slice = user_slice.indices(100);
+
+    printf("%d, %d, %d\n", slice.start, slice.stop, slice.step);
+
+    assert_values_match(0, slice.start);
+    assert_values_match(5, slice.stop);
+    assert_values_match(1, slice.step);
+}
+
+void test_slice_start_too_large() {
+    // Start is too large and should be clamped to length
+    BEGIN_TEST();
+
+    UserSlice user_slice;
+    user_slice.set_start(400);
+
+    Slice slice = user_slice.indices(100);
+
+    assert_values_match(100, slice.start);
+    assert_values_match(100, slice.stop);
+    assert_values_match(1, slice.step);
+}
+
+void test_slice_negative_start_stop() {
+    // Negative start/stop should be resolved
+    BEGIN_TEST();
+
+    UserSlice user_slice;
+    user_slice.set_start(-10);
+    user_slice.set_stop(-5);
+
+    Slice slice = user_slice.indices(100);
+
+    assert_values_match(90, slice.start);
+    assert_values_match(95, slice.stop);
+    assert_values_match(1, slice.step);
+}
+
+void test_slice_only_negative_step() {
+    // Things like `[::-5]` should be handled correctly
+    BEGIN_TEST();
+
+    UserSlice user_slice;
+    user_slice.set_step(-5);
+
+    Slice slice = user_slice.indices(100);
+
+    assert_values_match(99, slice.start);
+    assert_values_match(-1, slice.stop);
+    assert_values_match(-5, slice.step);
+}
+
+void test_slice_step_zero() {
+    // Step = 0 is a value error
+    BEGIN_TEST();
+
+    ErrorContext errctx = create_testing_errctx();
+
+    UserSlice user_slice;
+    user_slice.set_start(2);
+    user_slice.set_stop(12);
+    user_slice.set_step(0);
+
+    Slice slice;
+    user_slice.indices_checked(&errctx, 100, &slice);
+
+    assert_errctx_has_exception(&errctx, errctx.exceptions->value_error);
+}
+
+void run() {
+    test_slice_normal();
+    test_slice_start_too_large();
+    test_slice_negative_start_stop();
+    test_slice_only_negative_step();
+    test_slice_step_zero();
+}
+}  // namespace slice
+}  // namespace test

nac3core/irrt/test/util.hpp

@@ -0,0 +1,188 @@
+#pragma once
+
+#include <cstdio>
+#include <cstdlib>
+
+template <class T>
+void print_value(const T& value);
+
+template <>
+void print_value(const bool& value) {
+    printf("%s", value ? "true" : "false");
+}
+
+template <>
+void print_value(const int8_t& value) {
+    printf("%d", value);
+}
+
+template <>
+void print_value(const int32_t& value) {
+    printf("%d", value);
+}
+
+template <>
+void print_value(const uint8_t& value) {
+    printf("%u", value);
+}
+
+template <>
+void print_value(const uint32_t& value) {
+    printf("%u", value);
+}
+
+template <>
+void print_value(const float& value) {
+    printf("%f", value);
+}
+
+template <>
+void print_value(const double& value) {
+    printf("%f", value);
+}
+
+void __begin_test(const char* function_name, const char* file, int line) {
+    printf("######### Running %s @ %s:%d\n", function_name, file, line);
+}
+
+#define BEGIN_TEST() __begin_test(__FUNCTION__, __FILE__, __LINE__)
+
+void test_fail() {
+    printf("[!] Test failed. Exiting with status code 1.\n");
+    exit(1);
+}
+
+template <typename T>
+void debug_print_array(int len, const T* as) {
+    printf("[");
+    for (int i = 0; i < len; i++) {
+        if (i != 0) printf(", ");
+        print_value(as[i]);
+    }
+    printf("]");
+}
+
+void print_assertion_passed(const char* file, int line) {
+    printf("[*] Assertion passed on %s:%d\n", file, line);
+}
+
+void print_assertion_failed(const char* file, int line) {
+    printf("[!] Assertion failed on %s:%d\n", file, line);
+}
+
+void __assert_true(const char* file, int line, bool cond) {
+    if (cond) {
+        print_assertion_passed(file, line);
+    } else {
+        print_assertion_failed(file, line);
+        test_fail();
+    }
+}
+
+#define assert_true(cond) __assert_true(__FILE__, __LINE__, cond)
+
+template <typename T>
+void __assert_arrays_match(const char* file, int line, int len,
+                           const T* expected, const T* got) {
+    if (arrays_match(len, expected, got)) {
+        print_assertion_passed(file, line);
+    } else {
+        print_assertion_failed(file, line);
+        printf("Expect = ");
+        debug_print_array(len, expected);
+        printf("\n");
+        printf("   Got = ");
+        debug_print_array(len, got);
+        printf("\n");
+        test_fail();
+    }
+}
+
+#define assert_arrays_match(len, expected, got) \
+    __assert_arrays_match(__FILE__, __LINE__, len, expected, got)
+
+template <typename T>
+void __assert_values_match(const char* file, int line, T expected, T got) {
+    if (expected == got) {
+        print_assertion_passed(file, line);
+    } else {
+        print_assertion_failed(file, line);
+        printf("Expect = ");
+        print_value(expected);
+        printf("\n");
+        printf("   Got = ");
+        print_value(got);
+        printf("\n");
+        test_fail();
+    }
+}
+
+#define assert_values_match(expected, got) \
+    __assert_values_match(__FILE__, __LINE__, expected, got)
+
+// A fake set of ExceptionIds for testing only
+const ErrorContextExceptions TEST_ERROR_CONTEXT_EXCEPTIONS = {
+    .index_error = 0,
+    .value_error = 1,
+    .assertion_error = 2,
+    .runtime_error = 3,
+    .type_error = 4,
+};
+
+ErrorContext create_testing_errctx() {
+    // Everything is global so it is fine to directly return a struct
+    // ErrorContext
+    ErrorContext errctx;
+    errctx.initialize(&TEST_ERROR_CONTEXT_EXCEPTIONS);
+    return errctx;
+}
+
+void print_errctx_content(ErrorContext* errctx) {
+    if (errctx->has_exception()) {
+        printf(
+            "(Exception ID %d): %s ... where param1 = %ld, param2 = %ld, "
+            "param3 = "
+            "%ld\n",
+            errctx->exception_id, errctx->msg, errctx->param1, errctx->param2,
+            errctx->param3);
+    } else {
+        printf("<no exception>\n");
+    }
+}
+
+void __assert_errctx_no_exception(const char* file, int line,
+                                  ErrorContext* errctx) {
+    if (errctx->has_exception()) {
+        print_assertion_failed(file, line);
+        printf("Expecting no exception but caught the following:\n\n");
+        print_errctx_content(errctx);
+        test_fail();
+    }
+}
+
+#define assert_errctx_no_exception(errctx) \
+    __assert_errctx_no_exception(__FILE__, __LINE__, errctx)
+
+void __assert_errctx_has_exception(const char* file, int line,
+                                   ErrorContext* errctx,
+                                   ExceptionId expected_exception_id) {
+    if (errctx->has_exception()) {
+        if (errctx->exception_id != expected_exception_id) {
+            print_assertion_failed(file, line);
+            printf(
+                "Expecting exception id %d but got exception id %d. Error "
+                "caught:\n\n",
+                expected_exception_id, errctx->exception_id);
+            print_errctx_content(errctx);
+            test_fail();
+        }
+    } else {
+        print_assertion_failed(file, line);
+        printf("Expecting an exception, but there is none.");
+        test_fail();
+    }
+}
+
+#define assert_errctx_has_exception(errctx, expected_exception_id) \
+    __assert_errctx_has_exception(__FILE__, __LINE__, errctx,      \
+                                  expected_exception_id)

nac3core/src/codegen/builtin_fns.rs

@@ -1,102 +1,26 @@
-use inkwell::{
+use inkwell::types::BasicTypeEnum;
-    types::BasicTypeEnum,
+use inkwell::values::BasicValueEnum;
-    values::{BasicValue, BasicValueEnum, IntValue, PointerValue},
+use inkwell::{FloatPredicate, IntPredicate, OptimizationLevel};
-    FloatPredicate, IntPredicate, OptimizationLevel,
-};
 use itertools::Itertools;
 
-use super::{
+use crate::codegen::classes::{NDArrayValue, ProxyValue, UntypedArrayLikeAccessor};
-    classes::{
+use crate::codegen::numpy::ndarray_elementwise_unaryop_impl;
-        ArrayLikeValue, NDArrayValue, ProxyValue, RangeValue, TypedArrayLikeAccessor,
+use crate::codegen::stmt::gen_for_callback_incrementing;
-        UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
+use crate::codegen::{extern_fns, irrt, llvm_intrinsics, numpy, CodeGenContext, CodeGenerator};
-    },
+use crate::toplevel::helper::PrimDef;
-    expr::destructure_range,
+use crate::toplevel::numpy::unpack_ndarray_var_tys;
-    extern_fns, irrt,
+use crate::typecheck::typedef::Type;
-    irrt::calculate_len_for_slice_range,
-    llvm_intrinsics,
-    macros::codegen_unreachable,
-    numpy,
-    numpy::ndarray_elementwise_unaryop_impl,
-    stmt::gen_for_callback_incrementing,
-    CodeGenContext, CodeGenerator,
-};
-use crate::{
-    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys},
-    typecheck::typedef::{Type, TypeEnum},
-};
 
 /// Shorthand for [`unreachable!()`] when a type of argument is not supported.
 ///
 /// The generated message will contain the function name and the name of the unsupported type.
 fn unsupported_type(ctx: &CodeGenContext<'_, '_>, fn_name: &str, tys: &[Type]) -> ! {
-    codegen_unreachable!(
+    unreachable!(
-        ctx,
         "{fn_name}() not supported for '{}'",
         tys.iter().map(|ty| format!("'{}'", ctx.unifier.stringify(*ty))).join(", "),
     )
 }
 
-/// Invokes the `len` builtin function.
-pub fn call_len<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    n: (Type, BasicValueEnum<'ctx>),
-) -> Result<IntValue<'ctx>, String> {
-    let llvm_i32 = ctx.ctx.i32_type();
-    let range_ty = ctx.primitives.range;
-    let (arg_ty, arg) = n;
-
-    Ok(if ctx.unifier.unioned(arg_ty, range_ty) {
-        let arg = RangeValue::from_ptr_val(arg.into_pointer_value(), Some("range"));
-        let (start, end, step) = destructure_range(ctx, arg);
-        calculate_len_for_slice_range(generator, ctx, start, end, step)
-    } else {
-        match &*ctx.unifier.get_ty_immutable(arg_ty) {
-            TypeEnum::TTuple { ty, .. } => llvm_i32.const_int(ty.len() as u64, false),
-            TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::List.id() => {
-                let zero = llvm_i32.const_zero();
-                let len = ctx
-                    .build_gep_and_load(
-                        arg.into_pointer_value(),
-                        &[zero, llvm_i32.const_int(1, false)],
-                        None,
-                    )
-                    .into_int_value();
-                ctx.builder.build_int_truncate_or_bit_cast(len, llvm_i32, "len").unwrap()
-            }
-            TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-                let llvm_usize = generator.get_size_type(ctx.ctx);
-
-                let arg = NDArrayValue::from_ptr_val(arg.into_pointer_value(), llvm_usize, None);
-
-                let ndims = arg.dim_sizes().size(ctx, generator);
-                ctx.make_assert(
-                    generator,
-                    ctx.builder
-                        .build_int_compare(IntPredicate::NE, ndims, llvm_usize.const_zero(), "")
-                        .unwrap(),
-                    "0:TypeError",
-                    "len() of unsized object",
-                    [None, None, None],
-                    ctx.current_loc,
-                );
-
-                let len = unsafe {
-                    arg.dim_sizes().get_typed_unchecked(
-                        ctx,
-                        generator,
-                        &llvm_usize.const_zero(),
-                        None,
-                    )
-                };
-
-                ctx.builder.build_int_truncate_or_bit_cast(len, llvm_i32, "len").unwrap()
-            }
-            _ => codegen_unreachable!(ctx),
-        }
-    })
-}
-
 /// Invokes the `int32` builtin function.
 pub fn call_int32<'ctx, G: CodeGenerator + ?Sized>(
     generator: &mut G,
@@ -107,6 +31,7 @@ pub fn call_int32<'ctx, G: CodeGenerator + ?Sized>(
     let llvm_usize = generator.get_size_type(ctx.ctx);
 
     let (n_ty, n) = n;
+
     Ok(match n {
         BasicValueEnum::IntValue(n) if matches!(n.get_type().get_bit_width(), 1 | 8) => {
             debug_assert!(ctx.unifier.unioned(n_ty, ctx.primitives.bool));
@@ -677,7 +602,7 @@ pub fn call_ceil<'ctx, G: CodeGenerator + ?Sized>(
                 ret_elem_ty,
                 None,
                 NDArrayValue::from_ptr_val(n, llvm_usize, None),
-                |generator, ctx, val| call_ceil(generator, ctx, (elem_ty, val), ret_elem_ty),
+                |generator, ctx, val| call_floor(generator, ctx, (elem_ty, val), ret_elem_ty),
             )?;
 
             ndarray.as_base_value().into()
@@ -794,7 +719,7 @@ pub fn call_numpy_minimum<'ctx, G: CodeGenerator + ?Sized>(
             } else if is_ndarray2 {
                 unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
             } else {
-                codegen_unreachable!(ctx)
+                unreachable!()
             };
 
             let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@@ -898,7 +823,7 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
             match fn_name {
                 "np_argmin" | "np_argmax" => llvm_int64.const_zero().into(),
                 "np_max" | "np_min" => a,
-                _ => codegen_unreachable!(ctx),
+                _ => unreachable!(),
             }
         }
         BasicValueEnum::PointerValue(n)
@@ -953,7 +878,7 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
                         "np_argmax" | "np_max" => {
                             call_max(ctx, (elem_ty, accumulator), (elem_ty, elem))
                         }
-                        _ => codegen_unreachable!(ctx),
+                        _ => unreachable!(),
                     };
 
                     let updated_idx = match (accumulator, result) {
@@ -990,7 +915,7 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
             match fn_name {
                 "np_argmin" | "np_argmax" => ctx.builder.build_load(res_idx, "").unwrap(),
                 "np_max" | "np_min" => ctx.builder.build_load(accumulator_addr, "").unwrap(),
-                _ => codegen_unreachable!(ctx),
+                _ => unreachable!(),
             }
         }
 
@@ -1056,7 +981,7 @@ pub fn call_numpy_maximum<'ctx, G: CodeGenerator + ?Sized>(
             } else if is_ndarray2 {
                 unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
             } else {
-                codegen_unreachable!(ctx)
+                unreachable!()
             };
 
             let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@@ -1086,9 +1011,9 @@ pub fn call_numpy_maximum<'ctx, G: CodeGenerator + ?Sized>(
 /// * `(arg_ty, arg_val)`: The [`Type`] and llvm value of the input argument.
 /// * `fn_name`: The name of the function, only used when throwing an error with [`unsupported_type`]
 /// * `get_ret_elem_type`: A function that takes in the input scalar [`Type`], and returns the function's return scalar [`Type`].
-///   Return a constant [`Type`] here if the return type does not depend on the input type.
+/// Return a constant [`Type`] here if the return type does not depend on the input type.
 /// * `on_scalar`: The function that acts on the scalars of the input. Returns [`Option::None`]
-///   if the scalar type & value are faulty and should panic with [`unsupported_type`].
+/// if the scalar type & value are faulty and should panic with [`unsupported_type`].
 fn helper_call_numpy_unary_elementwise<'ctx, OnScalarFn, RetElemFn, G>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
@@ -1199,9 +1124,9 @@ pub fn call_abs<'ctx, G: CodeGenerator + ?Sized>(
 /// * `$name:ident`: The identifier of the rust function to be generated.
 /// * `$fn_name:literal`: To be passed to the `fn_name` parameter of [`helper_call_numpy_unary_elementwise`]
 /// * `$get_ret_elem_type:expr`: To be passed to the `get_ret_elem_type` parameter of [`helper_call_numpy_unary_elementwise`].
-///   But there is no need to make it a reference.
+/// But there is no need to make it a reference.
 /// * `$on_scalar:expr`: To be passed to the `on_scalar` parameter of [`helper_call_numpy_unary_elementwise`].
-///   But there is no need to make it a reference.
+/// But there is no need to make it a reference.
 macro_rules! create_helper_call_numpy_unary_elementwise {
     ($name:ident, $fn_name:literal, $get_ret_elem_type:expr, $on_scalar:expr) => {
         #[allow(clippy::redundant_closure_call)]
@@ -1228,7 +1153,7 @@ macro_rules! create_helper_call_numpy_unary_elementwise {
 /// * `$name:ident`: The identifier of the rust function to be generated.
 /// * `$fn_name:literal`: To be passed to the `fn_name` parameter of [`helper_call_numpy_unary_elementwise`].
 /// * `$on_scalar:expr`: The closure (see below for its type) that acts on float scalar values and returns
-///   the boolean results of LLVM type `i1`. The returned `i1` value will be converted into an `i8`.
+/// the boolean results of LLVM type `i1`. The returned `i1` value will be converted into an `i8`.
 ///
 /// ```ignore
 /// // Type of `$on_scalar:expr`
@@ -1496,7 +1421,7 @@ pub fn call_numpy_arctan2<'ctx, G: CodeGenerator + ?Sized>(
             } else if is_ndarray2 {
                 unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
             } else {
-                codegen_unreachable!(ctx)
+                unreachable!()
             };
 
             let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@@ -1563,7 +1488,7 @@ pub fn call_numpy_copysign<'ctx, G: CodeGenerator + ?Sized>(
             } else if is_ndarray2 {
                 unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
             } else {
-                codegen_unreachable!(ctx)
+                unreachable!()
             };
 
             let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@@ -1630,7 +1555,7 @@ pub fn call_numpy_fmax<'ctx, G: CodeGenerator + ?Sized>(
             } else if is_ndarray2 {
                 unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
             } else {
-                codegen_unreachable!(ctx)
+                unreachable!()
             };
 
             let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@@ -1697,7 +1622,7 @@ pub fn call_numpy_fmin<'ctx, G: CodeGenerator + ?Sized>(
             } else if is_ndarray2 {
                 unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
             } else {
-                codegen_unreachable!(ctx)
+                unreachable!()
             };
 
             let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@@ -1820,7 +1745,7 @@ pub fn call_numpy_hypot<'ctx, G: CodeGenerator + ?Sized>(
             } else if is_ndarray2 {
                 unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
             } else {
-                codegen_unreachable!(ctx)
+                unreachable!()
             };
 
             let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@@ -1887,7 +1812,7 @@ pub fn call_numpy_nextafter<'ctx, G: CodeGenerator + ?Sized>(
             } else if is_ndarray2 {
                 unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
             } else {
-                codegen_unreachable!(ctx)
+                unreachable!()
             };
 
             let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@@ -1911,501 +1836,3 @@ pub fn call_numpy_nextafter<'ctx, G: CodeGenerator + ?Sized>(
         _ => unsupported_type(ctx, FN_NAME, &[x1_ty, x2_ty]),
     })
 }
-
-/// Allocates a struct with the fields specified by `out_matrices` and returns a pointer to it
-fn build_output_struct<'ctx>(
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    out_matrices: Vec<BasicValueEnum<'ctx>>,
-) -> PointerValue<'ctx> {
-    let field_ty =
-        out_matrices.iter().map(BasicValueEnum::get_type).collect::<Vec<BasicTypeEnum>>();
-    let out_ty = ctx.ctx.struct_type(&field_ty, false);
-    let out_ptr = ctx.builder.build_alloca(out_ty, "").unwrap();
-
-    for (i, v) in out_matrices.into_iter().enumerate() {
-        unsafe {
-            let ptr = ctx
-                .builder
-                .build_in_bounds_gep(
-                    out_ptr,
-                    &[
-                        ctx.ctx.i32_type().const_zero(),
-                        ctx.ctx.i32_type().const_int(i as u64, false),
-                    ],
-                    "",
-                )
-                .unwrap();
-            ctx.builder.build_store(ptr, v).unwrap();
-        }
-    }
-    out_ptr
-}
-
-/// Invokes the `np_linalg_cholesky` linalg function
-pub fn call_np_linalg_cholesky<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    x1: (Type, BasicValueEnum<'ctx>),
-) -> Result<BasicValueEnum<'ctx>, String> {
-    const FN_NAME: &str = "np_linalg_cholesky";
-    let (x1_ty, x1) = x1;
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    if let BasicValueEnum::PointerValue(n1) = x1 {
-        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
-        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-
-        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
-            unsupported_type(ctx, FN_NAME, &[x1_ty]);
-        };
-
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
-        let dim0 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
-                .into_int_value()
-        };
-        let dim1 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
-                .into_int_value()
-        };
-
-        let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim1])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-
-        extern_fns::call_np_linalg_cholesky(ctx, x1, out, None);
-        Ok(out)
-    } else {
-        unsupported_type(ctx, FN_NAME, &[x1_ty])
-    }
-}
-
-/// Invokes the `np_linalg_qr` linalg function
-pub fn call_np_linalg_qr<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    x1: (Type, BasicValueEnum<'ctx>),
-) -> Result<BasicValueEnum<'ctx>, String> {
-    const FN_NAME: &str = "np_linalg_qr";
-    let (x1_ty, x1) = x1;
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    if let BasicValueEnum::PointerValue(n1) = x1 {
-        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
-        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-
-        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
-            unimplemented!("{FN_NAME} operates on float type NdArrays only");
-        };
-
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
-        let dim0 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
-                .into_int_value()
-        };
-        let dim1 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
-                .into_int_value()
-        };
-        let k = llvm_intrinsics::call_int_smin(ctx, dim0, dim1, None);
-
-        let out_q = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, k])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-        let out_r = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[k, dim1])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-
-        extern_fns::call_np_linalg_qr(ctx, x1, out_q, out_r, None);
-
-        let out_ptr = build_output_struct(ctx, vec![out_q, out_r]);
-
-        Ok(ctx.builder.build_load(out_ptr, "QR_Factorization_result").map(Into::into).unwrap())
-    } else {
-        unsupported_type(ctx, FN_NAME, &[x1_ty])
-    }
-}
-
-/// Invokes the `np_linalg_svd` linalg function
-pub fn call_np_linalg_svd<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    x1: (Type, BasicValueEnum<'ctx>),
-) -> Result<BasicValueEnum<'ctx>, String> {
-    const FN_NAME: &str = "np_linalg_svd";
-    let (x1_ty, x1) = x1;
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    if let BasicValueEnum::PointerValue(n1) = x1 {
-        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
-        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-
-        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
-            unsupported_type(ctx, FN_NAME, &[x1_ty]);
-        };
-
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
-
-        let dim0 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
-                .into_int_value()
-        };
-        let dim1 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
-                .into_int_value()
-        };
-        let k = llvm_intrinsics::call_int_smin(ctx, dim0, dim1, None);
-
-        let out_u = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-        let out_s = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[k])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-        let out_vh = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim1, dim1])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-
-        extern_fns::call_np_linalg_svd(ctx, x1, out_u, out_s, out_vh, None);
-
-        let out_ptr = build_output_struct(ctx, vec![out_u, out_s, out_vh]);
-
-        Ok(ctx.builder.build_load(out_ptr, "SVD_Factorization_result").map(Into::into).unwrap())
-    } else {
-        unsupported_type(ctx, FN_NAME, &[x1_ty])
-    }
-}
-
-/// Invokes the `np_linalg_inv` linalg function
-pub fn call_np_linalg_inv<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    x1: (Type, BasicValueEnum<'ctx>),
-) -> Result<BasicValueEnum<'ctx>, String> {
-    const FN_NAME: &str = "np_linalg_inv";
-    let (x1_ty, x1) = x1;
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    if let BasicValueEnum::PointerValue(n1) = x1 {
-        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
-        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-
-        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
-            unsupported_type(ctx, FN_NAME, &[x1_ty]);
-        };
-
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
-        let dim0 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
-                .into_int_value()
-        };
-        let dim1 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
-                .into_int_value()
-        };
-
-        let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim1])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-
-        extern_fns::call_np_linalg_inv(ctx, x1, out, None);
-        Ok(out)
-    } else {
-        unsupported_type(ctx, FN_NAME, &[x1_ty])
-    }
-}
-
-/// Invokes the `np_linalg_pinv` linalg function
-pub fn call_np_linalg_pinv<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    x1: (Type, BasicValueEnum<'ctx>),
-) -> Result<BasicValueEnum<'ctx>, String> {
-    const FN_NAME: &str = "np_linalg_pinv";
-    let (x1_ty, x1) = x1;
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    if let BasicValueEnum::PointerValue(n1) = x1 {
-        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
-        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-
-        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
-            unsupported_type(ctx, FN_NAME, &[x1_ty]);
-        };
-
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
-
-        let dim0 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
-                .into_int_value()
-        };
-        let dim1 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
-                .into_int_value()
-        };
-
-        let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim1, dim0])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-
-        extern_fns::call_np_linalg_pinv(ctx, x1, out, None);
-        Ok(out)
-    } else {
-        unsupported_type(ctx, FN_NAME, &[x1_ty])
-    }
-}
-
-/// Invokes the `sp_linalg_lu` linalg function
-pub fn call_sp_linalg_lu<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    x1: (Type, BasicValueEnum<'ctx>),
-) -> Result<BasicValueEnum<'ctx>, String> {
-    const FN_NAME: &str = "sp_linalg_lu";
-    let (x1_ty, x1) = x1;
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    if let BasicValueEnum::PointerValue(n1) = x1 {
-        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
-        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-
-        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
-            unsupported_type(ctx, FN_NAME, &[x1_ty]);
-        };
-
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
-
-        let dim0 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
-                .into_int_value()
-        };
-        let dim1 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
-                .into_int_value()
-        };
-        let k = llvm_intrinsics::call_int_smin(ctx, dim0, dim1, None);
-
-        let out_l = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, k])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-        let out_u = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[k, dim1])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-
-        extern_fns::call_sp_linalg_lu(ctx, x1, out_l, out_u, None);
-
-        let out_ptr = build_output_struct(ctx, vec![out_l, out_u]);
-        Ok(ctx.builder.build_load(out_ptr, "LU_Factorization_result").map(Into::into).unwrap())
-    } else {
-        unsupported_type(ctx, FN_NAME, &[x1_ty])
-    }
-}
-
-/// Invokes the `np_linalg_matrix_power` linalg function
-pub fn call_np_linalg_matrix_power<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    x1: (Type, BasicValueEnum<'ctx>),
-    x2: (Type, BasicValueEnum<'ctx>),
-) -> Result<BasicValueEnum<'ctx>, String> {
-    const FN_NAME: &str = "np_linalg_matrix_power";
-    let (x1_ty, x1) = x1;
-    let (x2_ty, x2) = x2;
-    let x2 = call_float(generator, ctx, (x2_ty, x2)).unwrap();
-
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    if let (BasicValueEnum::PointerValue(n1), BasicValueEnum::FloatValue(n2)) = (x1, x2) {
-        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
-        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-
-        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
-            unsupported_type(ctx, FN_NAME, &[x1_ty, x2_ty]);
-        };
-
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
-        // Changing second parameter to a `NDArray` for uniformity in function call
-        let n2_array = numpy::create_ndarray_const_shape(
-            generator,
-            ctx,
-            elem_ty,
-            &[llvm_usize.const_int(1, false)],
-        )
-        .unwrap();
-        unsafe {
-            n2_array.data().set_unchecked(
-                ctx,
-                generator,
-                &llvm_usize.const_zero(),
-                n2.as_basic_value_enum(),
-            );
-        };
-        let n2_array = n2_array.as_base_value().as_basic_value_enum();
-
-        let outdim0 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
-                .into_int_value()
-        };
-        let outdim1 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
-                .into_int_value()
-        };
-
-        let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[outdim0, outdim1])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-
-        extern_fns::call_np_linalg_matrix_power(ctx, x1, n2_array, out, None);
-        Ok(out)
-    } else {
-        unsupported_type(ctx, FN_NAME, &[x1_ty, x2_ty])
-    }
-}
-
-/// Invokes the `np_linalg_det` linalg function
-pub fn call_np_linalg_det<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    x1: (Type, BasicValueEnum<'ctx>),
-) -> Result<BasicValueEnum<'ctx>, String> {
-    const FN_NAME: &str = "np_linalg_matrix_power";
-    let (x1_ty, x1) = x1;
-
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-    if let BasicValueEnum::PointerValue(_) = x1 {
-        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
-        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-
-        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
-            unsupported_type(ctx, FN_NAME, &[x1_ty]);
-        };
-
-        // Changing second parameter to a `NDArray` for uniformity in function call
-        let out = numpy::create_ndarray_const_shape(
-            generator,
-            ctx,
-            elem_ty,
-            &[llvm_usize.const_int(1, false)],
-        )
-        .unwrap();
-        extern_fns::call_np_linalg_det(ctx, x1, out.as_base_value().as_basic_value_enum(), None);
-        let res =
-            unsafe { out.data().get_unchecked(ctx, generator, &llvm_usize.const_zero(), None) };
-        Ok(res)
-    } else {
-        unsupported_type(ctx, FN_NAME, &[x1_ty])
-    }
-}
-
-/// Invokes the `sp_linalg_schur` linalg function
-pub fn call_sp_linalg_schur<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    x1: (Type, BasicValueEnum<'ctx>),
-) -> Result<BasicValueEnum<'ctx>, String> {
-    const FN_NAME: &str = "sp_linalg_schur";
-    let (x1_ty, x1) = x1;
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    if let BasicValueEnum::PointerValue(n1) = x1 {
-        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
-        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-
-        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
-            unsupported_type(ctx, FN_NAME, &[x1_ty]);
-        };
-
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
-
-        let dim0 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
-                .into_int_value()
-        };
-        let out_t = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-        let out_z = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-
-        extern_fns::call_sp_linalg_schur(ctx, x1, out_t, out_z, None);
-
-        let out_ptr = build_output_struct(ctx, vec![out_t, out_z]);
-        Ok(ctx.builder.build_load(out_ptr, "Schur_Factorization_result").map(Into::into).unwrap())
-    } else {
-        unsupported_type(ctx, FN_NAME, &[x1_ty])
-    }
-}
-
-/// Invokes the `sp_linalg_hessenberg` linalg function
-pub fn call_sp_linalg_hessenberg<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    x1: (Type, BasicValueEnum<'ctx>),
-) -> Result<BasicValueEnum<'ctx>, String> {
-    const FN_NAME: &str = "sp_linalg_hessenberg";
-    let (x1_ty, x1) = x1;
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    if let BasicValueEnum::PointerValue(n1) = x1 {
-        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
-        let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-
-        let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
-            unsupported_type(ctx, FN_NAME, &[x1_ty]);
-        };
-
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
-
-        let dim0 = unsafe {
-            n1.dim_sizes()
-                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
-                .into_int_value()
-        };
-        let out_h = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-        let out_q = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
-            .unwrap()
-            .as_base_value()
-            .as_basic_value_enum();
-        extern_fns::call_sp_linalg_hessenberg(ctx, x1, out_h, out_q, None);
-
-        let out_ptr = build_output_struct(ctx, vec![out_h, out_q]);
-        Ok(ctx
-            .builder
-            .build_load(out_ptr, "Hessenberg_decomposition_result")
-            .map(Into::into)
-            .unwrap())
-    } else {
-        unsupported_type(ctx, FN_NAME, &[x1_ty])
-    }
-}

nac3core/src/codegen/classes.rs

@@ -1,16 +1,17 @@
-use inkwell::{
+use crate::codegen::{
-    context::Context,
-    types::{AnyTypeEnum, ArrayType, BasicType, BasicTypeEnum, IntType, PointerType, StructType},
-    values::{ArrayValue, BasicValue, BasicValueEnum, IntValue, PointerValue, StructValue},
-    AddressSpace, IntPredicate,
-};
-
-use super::{
     irrt::{call_ndarray_calc_size, call_ndarray_flatten_index},
     llvm_intrinsics::call_int_umin,
     stmt::gen_for_callback_incrementing,
     CodeGenContext, CodeGenerator,
 };
+use inkwell::context::Context;
+use inkwell::types::{ArrayType, BasicType, StructType};
+use inkwell::values::{ArrayValue, BasicValue, StructValue};
+use inkwell::{
+    types::{AnyTypeEnum, BasicTypeEnum, IntType, PointerType},
+    values::{BasicValueEnum, IntValue, PointerValue},
+    AddressSpace, IntPredicate,
+};
 
 /// A LLVM type that is used to represent a non-primitive type in NAC3.
 pub trait ProxyType<'ctx>: Into<Self::Base> {
@@ -1249,13 +1250,11 @@ impl<'ctx> NDArrayType<'ctx> {
 
     /// Returns the element type of this `ndarray` type.
     #[must_use]
-    pub fn element_type(&self) -> AnyTypeEnum<'ctx> {
+    pub fn element_type(&self) -> BasicTypeEnum<'ctx> {
         self.as_base_type()
             .get_element_type()
             .into_struct_type()
             .get_field_type_at_index(2)
-            .map(BasicTypeEnum::into_pointer_type)
-            .map(PointerType::get_element_type)
             .unwrap()
     }
 }
@@ -1405,7 +1404,7 @@ impl<'ctx> NDArrayValue<'ctx> {
 
     /// Returns the double-indirection pointer to the `data` array, as if by calling `getelementptr`
     /// on the field.
-    pub fn ptr_to_data(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
+    fn ptr_to_data(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
         let llvm_i32 = ctx.ctx.i32_type();
         let var_name = self.name.map(|v| format!("{v}.data.addr")).unwrap_or_default();
 

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>,
 }
@@ -27,7 +25,6 @@ pub struct ConcreteFuncArg {
     pub name: StrRef,
     pub ty: ConcreteType,
     pub default_value: Option<SymbolValue>,
-    pub is_vararg: bool,
 }
 
 #[derive(Clone, Debug)]
@@ -49,7 +46,6 @@ pub enum ConcreteTypeEnum {
     TPrimitive(Primitive),
     TTuple {
         ty: Vec<ConcreteType>,
-        is_vararg_ctx: bool,
     },
     TObj {
         obj_id: DefinitionId,
@@ -106,16 +102,8 @@ impl ConcreteTypeStore {
                 .iter()
                 .map(|arg| ConcreteFuncArg {
                     name: arg.name,
-                    ty: if arg.is_vararg {
+                    ty: self.from_unifier_type(unifier, primitives, arg.ty, cache),
-                        let tuple_ty = unifier
-                            .add_ty(TypeEnum::TTuple { ty: vec![arg.ty], is_vararg_ctx: true });
-
-                        self.from_unifier_type(unifier, primitives, tuple_ty, cache)
-                    } else {
-                        self.from_unifier_type(unifier, primitives, arg.ty, cache)
-                    },
                     default_value: arg.default_value.clone(),
-                    is_vararg: arg.is_vararg,
                 })
                 .collect(),
             ret: self.from_unifier_type(unifier, primitives, signature.ret, cache),
@@ -170,12 +158,11 @@ impl ConcreteTypeStore {
             cache.insert(ty, None);
             let ty_enum = unifier.get_ty(ty);
             let result = match &*ty_enum {
-                TypeEnum::TTuple { ty, is_vararg_ctx } => ConcreteTypeEnum::TTuple {
+                TypeEnum::TTuple { ty } => ConcreteTypeEnum::TTuple {
                     ty: ty
                         .iter()
                         .map(|t| self.from_unifier_type(unifier, primitives, *t, cache))
                         .collect(),
-                    is_vararg_ctx: *is_vararg_ctx,
                 },
                 TypeEnum::TObj { obj_id, fields, params } => ConcreteTypeEnum::TObj {
                     obj_id: *obj_id,
@@ -261,12 +248,11 @@ impl ConcreteTypeStore {
                 *cache.get_mut(&cty).unwrap() = Some(ty);
                 return ty;
             }
-            ConcreteTypeEnum::TTuple { ty, is_vararg_ctx } => TypeEnum::TTuple {
+            ConcreteTypeEnum::TTuple { ty } => TypeEnum::TTuple {
                 ty: ty
                     .iter()
                     .map(|cty| self.to_unifier_type(unifier, primitives, *cty, cache))
                     .collect(),
-                is_vararg_ctx: *is_vararg_ctx,
             },
             ConcreteTypeEnum::TVirtual { ty } => {
                 TypeEnum::TVirtual { ty: self.to_unifier_type(unifier, primitives, *ty, cache) }
@@ -291,7 +277,6 @@ impl ConcreteTypeStore {
                         name: arg.name,
                         ty: self.to_unifier_type(unifier, primitives, arg.ty, cache),
                         default_value: arg.default_value.clone(),
-                        is_vararg: false,
                     })
                     .collect(),
                 ret: self.to_unifier_type(unifier, primitives, *ret, cache),

nac3core/src/codegen/extern_fns.rs

@@ -1,10 +1,8 @@
-use inkwell::{
+use inkwell::attributes::{Attribute, AttributeLoc};
-    attributes::{Attribute, AttributeLoc},
+use inkwell::values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue};
-    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`
@@ -15,11 +13,11 @@ use super::CodeGenContext;
 /// * `$extern_fn:literal`: Name of underlying extern function
 ///
 /// Optional Arguments:
-/// * `$(,$attributes:literal)*)`: Attributes linked with the extern function.
+/// * `$(,$attributes:literal)*)`: Attributes linked with the extern function
-///   The default attributes are "mustprogress", "nofree", "nounwind", "willreturn", and "writeonly".
+/// The default attributes are "mustprogress", "nofree", "nounwind", "willreturn", and "writeonly"
-///   These will be used unless other attributes are specified
+/// These will be used unless other attributes are specified
 /// * `$(,$args:ident)*`: Operands of the extern function
-///   The data type of these operands will be set to `FloatValue`
+/// The data type of these operands will be set to `FloatValue`
 ///  
 macro_rules! generate_extern_fn {
     ("unary", $fn_name:ident, $extern_fn:literal) => {
@@ -132,62 +130,3 @@ pub fn call_ldexp<'ctx>(
         .map(Either::unwrap_left)
         .unwrap()
 }
-
-/// Macro to generate `np_linalg` and `sp_linalg` functions
-/// The function takes as input `NDArray` and returns ()
-///
-/// Arguments:
-/// * `$fn_name:ident`: The identifier of the rust function to be generated
-/// * `$extern_fn:literal`: Name of underlying extern function
-/// * (2/3/4): Number of `NDArray` that function takes as input
-///
-/// Note:
-/// The operands and resulting `NDArray` are both passed as input to the funcion
-/// It is the responsibility of caller to ensure that output `NDArray` is properly allocated on stack
-/// The function changes the content of the output `NDArray` in-place
-macro_rules! generate_linalg_extern_fn {
-    ($fn_name:ident, $extern_fn:literal, 2) => {
-        generate_linalg_extern_fn!($fn_name, $extern_fn, mat1, mat2);
-    };
-    ($fn_name:ident, $extern_fn:literal, 3) => {
-        generate_linalg_extern_fn!($fn_name, $extern_fn, mat1, mat2, mat3);
-    };
-    ($fn_name:ident, $extern_fn:literal, 4) => {
-        generate_linalg_extern_fn!($fn_name, $extern_fn, mat1, mat2, mat3, mat4);
-    };
-    ($fn_name:ident, $extern_fn:literal $(,$input_matrix:ident)*) => {
-        #[doc = concat!("Invokes the linalg `", stringify!($extern_fn), " function." )]
-        pub fn $fn_name<'ctx>(
-            ctx: &mut CodeGenContext<'ctx, '_>
-            $(,$input_matrix: BasicValueEnum<'ctx>)*,
-            name: Option<&str>,
-        ){
-            const FN_NAME: &str = $extern_fn;
-            let extern_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
-                let fn_type = ctx.ctx.void_type().fn_type(&[$($input_matrix.get_type().into()),*], false);
-
-                let func = ctx.module.add_function(FN_NAME, fn_type, None);
-                for attr in ["mustprogress", "nofree", "nounwind", "willreturn", "writeonly"] {
-                    func.add_attribute(
-                        AttributeLoc::Function,
-                        ctx.ctx.create_enum_attribute(Attribute::get_named_enum_kind_id(attr), 0),
-                    );
-                }
-                func
-            });
-
-            ctx.builder.build_call(extern_fn, &[$($input_matrix.into(),)*], name.unwrap_or_default()).unwrap();
-        }
-    };
-}
-
-generate_linalg_extern_fn!(call_np_linalg_cholesky, "np_linalg_cholesky", 2);
-generate_linalg_extern_fn!(call_np_linalg_qr, "np_linalg_qr", 3);
-generate_linalg_extern_fn!(call_np_linalg_svd, "np_linalg_svd", 4);
-generate_linalg_extern_fn!(call_np_linalg_inv, "np_linalg_inv", 2);
-generate_linalg_extern_fn!(call_np_linalg_pinv, "np_linalg_pinv", 2);
-generate_linalg_extern_fn!(call_np_linalg_matrix_power, "np_linalg_matrix_power", 3);
-generate_linalg_extern_fn!(call_np_linalg_det, "np_linalg_det", 2);
-generate_linalg_extern_fn!(call_sp_linalg_lu, "sp_linalg_lu", 3);
-generate_linalg_extern_fn!(call_sp_linalg_schur, "sp_linalg_schur", 3);
-generate_linalg_extern_fn!(call_sp_linalg_hessenberg, "sp_linalg_hessenberg", 3);

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;
@@ -59,7 +57,6 @@ pub trait CodeGenerator {
     /// - fun: Function signature, definition ID and the substitution key.
     /// - params: Function parameters. Note that this does not include the object even if the
     ///   function is a class method.
-    ///
     /// Note that this function should check if the function is generated in another thread (due to
     /// possible race condition), see the default implementation for an example.
     fn gen_func_instance<'ctx>(
@@ -134,39 +131,6 @@ pub trait CodeGenerator {
         gen_assign(self, ctx, target, value, value_ty)
     }
 
-    /// Generate code for an assignment expression where LHS is a `"target_list"`.
-    ///
-    /// See <https://docs.python.org/3/reference/simple_stmts.html#assignment-statements>.
-    fn gen_assign_target_list<'ctx>(
-        &mut self,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        targets: &Vec<Expr<Option<Type>>>,
-        value: ValueEnum<'ctx>,
-        value_ty: Type,
-    ) -> Result<(), String>
-    where
-        Self: Sized,
-    {
-        gen_assign_target_list(self, ctx, targets, value, value_ty)
-    }
-
-    /// Generate code for an item assignment.
-    ///
-    /// i.e., `target[key] = value`
-    fn gen_setitem<'ctx>(
-        &mut self,
-        ctx: &mut CodeGenContext<'ctx, '_>,
-        target: &Expr<Option<Type>>,
-        key: &Expr<Option<Type>>,
-        value: ValueEnum<'ctx>,
-        value_ty: Type,
-    ) -> Result<(), String>
-    where
-        Self: Sized,
-    {
-        gen_setitem(self, ctx, target, key, value, value_ty)
-    }
-
     /// Generate code for a while expression.
     /// Return true if the while loop must early return
     fn gen_while(

nac3core/src/codegen/irrt/error_context.rs

@@ -0,0 +1,198 @@
+use super::util::{function::CallFunction, get_sizet_dependent_function_name};
+use crate::codegen::{
+    model::*,
+    structure::{cslice::CSlice, exception::ExceptionId},
+    CodeGenContext, CodeGenerator,
+};
+
+#[allow(clippy::struct_field_names)]
+pub struct ErrorContextExceptionsFields<F: FieldVisitor> {
+    pub index_error: F::Field<IntModel<ExceptionId>>,
+    pub value_error: F::Field<IntModel<ExceptionId>>,
+    pub assertion_error: F::Field<IntModel<ExceptionId>>,
+    pub runtime_error: F::Field<IntModel<ExceptionId>>,
+    pub type_error: F::Field<IntModel<ExceptionId>>,
+}
+
+/// Corresponds to IRRT's `struct ErrorContextExceptions`
+#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
+pub struct ErrorContextExceptions;
+
+impl StructKind for ErrorContextExceptions {
+    type Fields<F: FieldVisitor> = ErrorContextExceptionsFields<F>;
+
+    fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            index_error: visitor.add("index_error"),
+            value_error: visitor.add("value_error"),
+            assertion_error: visitor.add("assertion_error"),
+            runtime_error: visitor.add("runtime_error"),
+            type_error: visitor.add("type_error"),
+        }
+    }
+}
+
+pub struct ErrorContextFields<F: FieldVisitor> {
+    pub exceptions: F::Field<PtrModel<StructModel<ErrorContextExceptions>>>,
+    pub exception_id: F::Field<IntModel<ExceptionId>>,
+    pub msg: F::Field<PtrModel<IntModel<Byte>>>,
+    pub param1: F::Field<IntModel<Int64>>,
+    pub param2: F::Field<IntModel<Int64>>,
+    pub param3: F::Field<IntModel<Int64>>,
+}
+
+/// Corresponds to IRRT's `struct ErrorContext`
+#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
+pub struct ErrorContext;
+
+impl StructKind for ErrorContext {
+    type Fields<F: FieldVisitor> = ErrorContextFields<F>;
+
+    fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            exceptions: visitor.add("exceptions"),
+            exception_id: visitor.add("exception_id"),
+            msg: visitor.add("msg"),
+            param1: visitor.add("param1"),
+            param2: visitor.add("param2"),
+            param3: visitor.add("param3"),
+        }
+    }
+}
+
+/// Build an [`ErrorContextExceptions`] loaded with resolved [`ExceptionID`]s according to the [`SymbolResolver`].
+fn build_error_context_exceptions<'ctx>(
+    tyctx: TypeContext<'ctx>,
+    ctx: &CodeGenContext<'ctx, '_>,
+) -> Ptr<'ctx, StructModel<ErrorContextExceptions>> {
+    let exceptions =
+        StructModel(ErrorContextExceptions).alloca(tyctx, ctx, "error_context_exceptions");
+    let i32_model = IntModel(Int32);
+
+    let get_string_id = |string_id| {
+        i32_model.constant(tyctx, ctx.ctx, ctx.resolver.get_string_id(string_id) as u64)
+    };
+
+    exceptions.gep(ctx, |f| f.index_error).store(ctx, get_string_id("0:IndexError"));
+    exceptions.gep(ctx, |f| f.value_error).store(ctx, get_string_id("0:ValueError"));
+    exceptions.gep(ctx, |f| f.assertion_error).store(ctx, get_string_id("0:AssertionError"));
+    exceptions.gep(ctx, |f| f.runtime_error).store(ctx, get_string_id("0:RuntimeError"));
+    exceptions.gep(ctx, |f| f.type_error).store(ctx, get_string_id("0:TypeError"));
+
+    exceptions
+}
+
+pub fn call_nac3_error_context_initialize<'ctx>(
+    tyctx: TypeContext<'ctx>,
+    ctx: &CodeGenContext<'ctx, '_>,
+    perrctx: Ptr<'ctx, StructModel<ErrorContext>>,
+    pexceptions: Ptr<'ctx, StructModel<ErrorContextExceptions>>,
+) {
+    CallFunction::begin(tyctx, ctx, "__nac3_error_context_initialize")
+        .arg("errctx", perrctx)
+        .arg("exceptions", pexceptions)
+        .returning_void();
+}
+
+pub fn call_nac3_error_context_has_exception<'ctx>(
+    tyctx: TypeContext<'ctx>,
+    ctx: &CodeGenContext<'ctx, '_>,
+    perrctx: Ptr<'ctx, StructModel<ErrorContext>>,
+) -> Int<'ctx, Bool> {
+    CallFunction::begin(tyctx, ctx, "__nac3_error_context_has_exception")
+        .arg("errctx", perrctx)
+        .returning("has_exception")
+}
+
+pub fn call_nac3_error_context_get_exception_str<'ctx>(
+    tyctx: TypeContext<'ctx>,
+    ctx: &CodeGenContext<'ctx, '_>,
+    perrctx: Ptr<'ctx, StructModel<ErrorContext>>,
+    dst_str: Ptr<'ctx, StructModel<CSlice>>,
+) {
+    CallFunction::begin(
+        tyctx,
+        ctx,
+        &get_sizet_dependent_function_name(tyctx, "__nac3_error_context_get_exception_str"),
+    )
+    .arg("errctx", perrctx)
+    .arg("dst_str", dst_str)
+    .returning_void();
+}
+
+/// Setup a [`ErrorContext`] that could be passed to IRRT functions taking in a `ErrorContext* errctx`
+/// for error reporting purposes.
+///
+/// Also see: [`check_error_context`]
+pub fn setup_error_context<'ctx>(
+    tyctx: TypeContext<'ctx>,
+    ctx: &CodeGenContext<'ctx, '_>,
+) -> Ptr<'ctx, StructModel<ErrorContext>> {
+    let errctx_model = StructModel(ErrorContext);
+
+    let exceptions = build_error_context_exceptions(tyctx, ctx);
+    let errctx_ptr = errctx_model.alloca(tyctx, ctx, "errctx");
+
+    call_nac3_error_context_initialize(tyctx, ctx, errctx_ptr, exceptions);
+
+    errctx_ptr
+}
+
+/// Check a [`ErrorContext`] to see if it contains error. **If there is an error,
+/// a Pythonic exception will be raised in the firmware**.
+pub fn check_error_context<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    perrctx: Ptr<'ctx, StructModel<ErrorContext>>,
+) {
+    let tyctx = generator.type_context(ctx.ctx);
+    let cslice_model = StructModel(CSlice);
+
+    let current_bb = ctx.builder.get_insert_block().unwrap();
+    let irrt_has_exception_bb = ctx.ctx.insert_basic_block_after(current_bb, "irrt_has_exception");
+    let end_bb = ctx.ctx.insert_basic_block_after(irrt_has_exception_bb, "end");
+
+    // Inserting into `current_bb`
+    let has_exception = call_nac3_error_context_has_exception(tyctx, ctx, perrctx);
+    ctx.builder
+        .build_conditional_branch(has_exception.value, irrt_has_exception_bb, end_bb)
+        .unwrap();
+
+    // Inserting into `irrt_has_exception_bb`
+    ctx.builder.position_at_end(irrt_has_exception_bb);
+
+    // Load all the values for `ctx.make_assert_impl_by_id`
+    let pexception_str = cslice_model.alloca(tyctx, ctx, "exception_str");
+    call_nac3_error_context_get_exception_str(tyctx, ctx, perrctx, pexception_str);
+
+    let exception_id = perrctx.gep(ctx, |f| f.exception_id).load(tyctx, ctx, "exception_id");
+    let msg = pexception_str.load(tyctx, ctx, "msg");
+    let param1 = perrctx.gep(ctx, |f| f.param1).load(tyctx, ctx, "param1");
+    let param2 = perrctx.gep(ctx, |f| f.param2).load(tyctx, ctx, "param2");
+    let param3 = perrctx.gep(ctx, |f| f.param3).load(tyctx, ctx, "param3");
+
+    ctx.raise_exn_impl(
+        generator,
+        exception_id,
+        msg,
+        [Some(param1), Some(param2), Some(param3)],
+        ctx.current_loc,
+    );
+
+    // Position to `end_bb` for continuation
+    ctx.builder.position_at_end(end_bb);
+}
+
+pub fn call_nac3_dummy_raise<G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext,
+) {
+    let tyctx = generator.type_context(ctx.ctx);
+
+    let errctx = setup_error_context(tyctx, ctx);
+    CallFunction::begin(tyctx, ctx, "__nac3_error_dummy_raise")
+        .arg("errctx", errctx)
+        .returning_void();
+
+    check_error_context(generator, ctx, errctx);
+}

nac3core/src/codegen/irrt/mod.rs

@@ -1,30 +1,35 @@
+use crate::typecheck::typedef::Type;
+
+pub mod error_context;
+pub mod ndarray;
+pub mod slice;
+mod test;
+mod util;
+
+use super::model::*;
+use super::{
+    classes::{
+        ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue,
+        TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
+    },
+    llvm_intrinsics, CodeGenContext, CodeGenerator,
+};
+use crate::codegen::classes::TypedArrayLikeAccessor;
+use crate::codegen::stmt::gen_for_callback_incrementing;
 use inkwell::{
     attributes::{Attribute, AttributeLoc},
     context::Context,
     memory_buffer::MemoryBuffer,
     module::Module,
     types::{BasicTypeEnum, IntType},
-    values::{BasicValue, BasicValueEnum, CallSiteValue, FloatValue, IntValue},
+    values::{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 +45,6 @@ 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 +62,7 @@ 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(|| {
@@ -435,14 +421,29 @@ pub fn list_slice_assignment<'ctx, G: CodeGenerator + ?Sized>(
         .unwrap();
     let cond_1 = ctx.builder.build_and(dest_step_eq_one, src_slt_dest, "slice_cond_1").unwrap();
     let cond = ctx.builder.build_or(src_eq_dest, cond_1, "slice_cond").unwrap();
-    ctx.make_assert(
+
-        generator,
+    // TODO: Temporary fix. Rewrite `list_slice_assignment` later
-        cond,
+    // Exception params should have been i64
-        "0:ValueError",
+    {
-        "attempt to assign sequence of size {0} to slice of size {1} with step size {2}",
+        let type_context = generator.type_context(ctx.ctx);
-        [Some(src_slice_len), Some(dest_slice_len), Some(dest_idx.2)],
+        let param_model = IntModel(Int64);
-        ctx.current_loc,
+
-    );
+        let src_slice_len =
+            param_model.s_extend_or_bit_cast(type_context, ctx, src_slice_len, "src_slice_len");
+        let dest_slice_len =
+            param_model.s_extend_or_bit_cast(type_context, ctx, dest_slice_len, "dest_slice_len");
+        let dest_idx_2 =
+            param_model.s_extend_or_bit_cast(type_context, ctx, dest_idx.2, "dest_idx_2");
+
+        ctx.make_assert(
+            generator,
+            cond,
+            "0:ValueError",
+            "attempt to assign sequence of size {0} to slice of size {1} with step size {2}",
+            [Some(src_slice_len.value), Some(dest_slice_len.value), Some(dest_idx_2.value)],
+            ctx.current_loc,
+        );
+    }
 
     let new_len = {
         let args = vec![
@@ -462,7 +463,7 @@ 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()
             }
@@ -589,8 +590,7 @@ pub fn call_j0<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> Flo
 ///
 /// * `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
+/// or [`None`] if starting from the first dimension and ending at the last dimension respectively.
-///   respectively.
 pub fn call_ndarray_calc_size<'ctx, G, Dims>(
     generator: &G,
     ctx: &CodeGenContext<'ctx, '_>,
@@ -607,7 +607,7 @@ where
     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),
+        bw => unreachable!("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()],
@@ -642,7 +642,7 @@ where
 ///
 /// * `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`.
+/// `NDArray`.
 pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
     generator: &G,
     ctx: &mut CodeGenContext<'ctx, '_>,
@@ -658,7 +658,7 @@ pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
     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),
+        bw => unreachable!("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(|| {
@@ -727,7 +727,7 @@ where
     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),
+        bw => unreachable!("Unsupported size type bit width: {}", bw),
     };
     let ndarray_flatten_index_fn =
         ctx.module.get_function(ndarray_flatten_index_fn_name).unwrap_or_else(|| {
@@ -766,7 +766,7 @@ where
 /// multidimensional index.
 ///
 /// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
-///   `NDArray`.
+/// `NDArray`.
 /// * `indices` - The multidimensional index to compute the flattened index for.
 pub fn call_ndarray_flatten_index<'ctx, G, Index>(
     generator: &mut G,
@@ -795,7 +795,7 @@ pub fn call_ndarray_calc_broadcast<'ctx, G: CodeGenerator + ?Sized>(
     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),
+        bw => unreachable!("Unsupported size type bit width: {}", bw),
     };
     let ndarray_calc_broadcast_fn =
         ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
@@ -915,7 +915,7 @@ pub fn call_ndarray_calc_broadcast_index<
     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),
+        bw => unreachable!("Unsupported size type bit width: {}", bw),
     };
     let ndarray_calc_broadcast_fn =
         ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {

nac3core/src/codegen/irrt/ndarray/basic.rs

@@ -0,0 +1,153 @@
+use crate::codegen::irrt::error_context::{check_error_context, setup_error_context};
+use crate::codegen::irrt::slice::SliceIndex;
+use crate::codegen::irrt::util::function::CallFunction;
+use crate::codegen::irrt::util::get_sizet_dependent_function_name;
+use crate::codegen::model::*;
+use crate::codegen::structure::ndarray::NpArray;
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+pub fn call_nac3_ndarray_size<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray_ptr: Ptr<'ctx, StructModel<NpArray>>,
+) -> Int<'ctx, SizeT> {
+    let tyctx = generator.type_context(ctx.ctx);
+
+    CallFunction::begin(
+        tyctx,
+        ctx,
+        &get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_size"),
+    )
+    .arg("ndarray", ndarray_ptr)
+    .returning("size")
+}
+
+pub fn call_nac3_ndarray_nbytes<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray_ptr: Ptr<'ctx, StructModel<NpArray>>,
+) -> Int<'ctx, SizeT> {
+    let tyctx = generator.type_context(ctx.ctx);
+
+    CallFunction::begin(
+        tyctx,
+        ctx,
+        &get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_nbytes"),
+    )
+    .arg("ndarray", ndarray_ptr)
+    .returning("nbytes")
+}
+
+pub fn call_nac3_ndarray_len<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray_ptr: Ptr<'ctx, StructModel<NpArray>>,
+) -> Int<'ctx, SliceIndex> {
+    let tyctx = generator.type_context(ctx.ctx);
+    let slice_index_model = IntModel(SliceIndex::default());
+
+    let dst_len = slice_index_model.alloca(tyctx, ctx, "dst_len");
+
+    let errctx = setup_error_context(tyctx, ctx);
+    CallFunction::begin(
+        tyctx,
+        ctx,
+        &get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_len"),
+    )
+    .arg("errctx", errctx)
+    .arg("ndarray", ndarray_ptr)
+    .arg("dst_len", dst_len)
+    .returning_void();
+    check_error_context(generator, ctx, errctx);
+
+    dst_len.load(tyctx, ctx, "len")
+}
+
+pub fn call_nac3_ndarray_util_assert_shape_no_negative<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndims: Int<'ctx, SizeT>,
+    shape: Ptr<'ctx, IntModel<SizeT>>,
+) {
+    let tyctx = generator.type_context(ctx.ctx);
+
+    let errctx = setup_error_context(tyctx, ctx);
+    CallFunction::begin(
+        tyctx,
+        ctx,
+        &get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_util_assert_shape_no_negative"),
+    )
+    .arg("errctx", errctx)
+    .arg("ndims", ndims)
+    .arg("shape", shape)
+    .returning_void();
+    check_error_context(generator, ctx, errctx);
+}
+
+pub fn call_nac3_ndarray_set_strides_by_shape<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray_ptr: Ptr<'ctx, StructModel<NpArray>>,
+) {
+    let tyctx = generator.type_context(ctx.ctx);
+
+    CallFunction::begin(
+        tyctx,
+        ctx,
+        &get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_set_strides_by_shape"),
+    )
+    .arg("ndarray", ndarray_ptr)
+    .returning_void();
+}
+
+pub fn call_nac3_ndarray_is_c_contiguous<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarray_ptr: Ptr<'ctx, StructModel<NpArray>>,
+) -> Int<'ctx, Bool> {
+    let tyctx = generator.type_context(ctx.ctx);
+
+    CallFunction::begin(
+        tyctx,
+        ctx,
+        &get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_is_c_contiguous"),
+    )
+    .arg("ndarray", ndarray_ptr)
+    .returning("is_c_contiguous")
+}
+
+pub fn call_nac3_ndarray_copy_data<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    src_ndarray: Ptr<'ctx, StructModel<NpArray>>,
+    dst_ndarray: Ptr<'ctx, StructModel<NpArray>>,
+) {
+    let tyctx = generator.type_context(ctx.ctx);
+
+    CallFunction::begin(
+        tyctx,
+        ctx,
+        &get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_copy_data"),
+    )
+    .arg("src_ndarray", src_ndarray)
+    .arg("dst_ndarray", dst_ndarray)
+    .returning_void();
+}
+
+pub fn call_nac3_ndarray_get_nth_pelement<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    pndarray: Ptr<'ctx, StructModel<NpArray>>,
+    index: Int<'ctx, SizeT>,
+) -> Ptr<'ctx, IntModel<Byte>> {
+    let tyctx = generator.type_context(ctx.ctx);
+
+    CallFunction::begin(
+        tyctx,
+        ctx,
+        &get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_get_nth_pelement"),
+    )
+    .arg("ndarray", pndarray)
+    .arg("index", index)
+    .returning("pelement")
+}

nac3core/src/codegen/irrt/ndarray/broadcast.rs

@@ -0,0 +1,74 @@
+use crate::codegen::{
+    irrt::{
+        error_context::{check_error_context, setup_error_context},
+        util::{function::CallFunction, get_sizet_dependent_function_name},
+    },
+    model::*,
+    structure::ndarray::NpArray,
+    CodeGenContext, CodeGenerator,
+};
+
+pub fn call_nac3_ndarray_broadcast_to<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    src_ndarray: Ptr<'ctx, StructModel<NpArray>>,
+    dst_ndarray: Ptr<'ctx, StructModel<NpArray>>,
+) {
+    let tyctx = generator.type_context(ctx.ctx);
+
+    let perrctx = setup_error_context(tyctx, ctx);
+    CallFunction::begin(
+        tyctx,
+        ctx,
+        &get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_broadcast_to"),
+    )
+    .arg("errctx", perrctx)
+    .arg("src_ndarray", src_ndarray)
+    .arg("dst_ndarray", dst_ndarray)
+    .returning_void();
+
+    check_error_context(generator, ctx, perrctx);
+}
+
+/// Fields of [`ShapeEntry`]
+pub struct ShapeEntryFields<F: FieldVisitor> {
+    pub ndims: F::Field<IntModel<SizeT>>,
+    pub shape: F::Field<PtrModel<IntModel<SizeT>>>,
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct ShapeEntry;
+
+impl StructKind for ShapeEntry {
+    type Fields<F: FieldVisitor> = ShapeEntryFields<F>;
+
+    fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
+        Self::Fields { ndims: visitor.add("ndims"), shape: visitor.add("shape") }
+    }
+}
+
+pub fn call_nac3_ndarray_broadcast_shapes<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    num_shape_entries: Int<'ctx, SizeT>,
+    shape_entries: Ptr<'ctx, StructModel<ShapeEntry>>,
+    dst_ndims: Int<'ctx, SizeT>,
+    dst_shape: Ptr<'ctx, IntModel<SizeT>>,
+) {
+    let tyctx = generator.type_context(ctx.ctx);
+
+    let perrctx = setup_error_context(tyctx, ctx);
+    CallFunction::begin(
+        tyctx,
+        ctx,
+        &get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_broadcast_shapes"),
+    )
+    .arg("errctx", perrctx)
+    .arg("num_shapes", num_shape_entries)
+    .arg("shapes", shape_entries)
+    .arg("dst_ndims", dst_ndims)
+    .arg("dst_shape", dst_shape)
+    .returning_void();
+
+    check_error_context(generator, ctx, perrctx);
+}

nac3core/src/codegen/irrt/ndarray/indexing.rs

@@ -0,0 +1,170 @@
+use crate::codegen::{
+    irrt::{
+        error_context::{check_error_context, setup_error_context},
+        slice::{RustUserSlice, SliceIndex, UserSlice},
+        util::{function::CallFunction, get_sizet_dependent_function_name},
+    },
+    model::*,
+    structure::ndarray::NpArray,
+    CodeGenContext, CodeGenerator,
+};
+
+pub type NDIndexType = Byte;
+
+#[derive(Debug, Clone, Copy)]
+pub struct NDIndexFields<F: FieldVisitor> {
+    pub type_: F::Field<IntModel<NDIndexType>>, // Defined to be uint8_t in IRRT
+    pub data: F::Field<PtrModel<IntModel<Byte>>>,
+}
+
+#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
+pub struct NDIndex;
+
+impl StructKind for NDIndex {
+    type Fields<F: FieldVisitor> = NDIndexFields<F>;
+
+    fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
+        Self::Fields { type_: visitor.add("type"), data: visitor.add("data") }
+    }
+}
+
+// An enum variant to store the content
+// and type of an NDIndex in high level.
+#[derive(Debug, Clone)]
+pub enum RustNDIndex<'ctx> {
+    SingleElement(Int<'ctx, SliceIndex>),
+    Slice(RustUserSlice<'ctx>),
+}
+
+impl<'ctx> RustNDIndex<'ctx> {
+    fn get_type_id(&self) -> u64 {
+        // Defined in IRRT, must be in sync
+        match self {
+            RustNDIndex::SingleElement(_) => 0,
+            RustNDIndex::Slice(_) => 1,
+        }
+    }
+
+    fn write_to_ndindex(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        dst_ndindex_ptr: Ptr<'ctx, StructModel<NDIndex>>,
+    ) {
+        let ndindex_type_model = IntModel(NDIndexType::default());
+        let slice_index_model = IntModel(SliceIndex::default());
+        let user_slice_model = StructModel(UserSlice);
+
+        // Set `dst_ndindex_ptr->type`
+        dst_ndindex_ptr
+            .gep(ctx, |f| f.type_)
+            .store(ctx, ndindex_type_model.constant(tyctx, ctx.ctx, self.get_type_id()));
+
+        // Set `dst_ndindex_ptr->data`
+        let data = match self {
+            RustNDIndex::SingleElement(in_index) => {
+                let index_ptr = slice_index_model.alloca(tyctx, ctx, "index");
+                index_ptr.store(ctx, *in_index);
+                index_ptr.transmute(tyctx, ctx, IntModel(Byte), "")
+            }
+            RustNDIndex::Slice(in_rust_slice) => {
+                let user_slice_ptr = user_slice_model.alloca(tyctx, ctx, "user_slice");
+                in_rust_slice.write_to_user_slice(tyctx, ctx, user_slice_ptr);
+                user_slice_ptr.transmute(tyctx, ctx, IntModel(Byte), "")
+            }
+        };
+        dst_ndindex_ptr.gep(ctx, |f| f.data).store(ctx, data);
+    }
+
+    /// Allocate an array of `NDIndex`es on the stack and return its stack pointer.
+    pub fn alloca_ndindexes(
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        in_ndindexes: &[RustNDIndex<'ctx>],
+    ) -> (Int<'ctx, SizeT>, Ptr<'ctx, StructModel<NDIndex>>) {
+        let sizet_model = IntModel(SizeT);
+        let ndindex_model = StructModel(NDIndex);
+
+        let num_ndindexes = sizet_model.constant(tyctx, ctx.ctx, in_ndindexes.len() as u64);
+        let ndindexes = ndindex_model.array_alloca(tyctx, ctx, num_ndindexes.value, "ndindexes");
+        for (i, in_ndindex) in in_ndindexes.iter().enumerate() {
+            let i = sizet_model.constant(tyctx, ctx.ctx, i as u64);
+            let pndindex = ndindexes.offset(tyctx, ctx, i.value, "");
+            in_ndindex.write_to_ndindex(tyctx, ctx, pndindex);
+        }
+
+        (num_ndindexes, ndindexes)
+    }
+
+    #[must_use]
+    pub fn deduce_ndims_after_indexing(indices: &[RustNDIndex], original_ndims: u64) -> u64 {
+        let mut final_ndims = original_ndims;
+        for index in indices {
+            match index {
+                RustNDIndex::SingleElement(_) => {
+                    final_ndims -= 1;
+                }
+                RustNDIndex::Slice(_) => {}
+            }
+        }
+        final_ndims
+    }
+}
+
+pub fn call_nac3_ndarray_indexing_deduce_ndims_after_indexing<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndims: Int<'ctx, SizeT>,
+    num_ndindexes: Int<'ctx, SizeT>,
+    ndindexs: Ptr<'ctx, StructModel<NDIndex>>,
+) -> Int<'ctx, SizeT> {
+    let tyctx = generator.type_context(ctx.ctx);
+    let sizet_model = IntModel(SizeT);
+
+    let pfinal_ndims = sizet_model.alloca(tyctx, ctx, "pfinal_ndims");
+
+    let errctx_ptr = setup_error_context(tyctx, ctx);
+    CallFunction::begin(
+        tyctx,
+        ctx,
+        &get_sizet_dependent_function_name(
+            tyctx,
+            "__nac3_ndarray_indexing_deduce_ndims_after_indexing",
+        ),
+    )
+    .arg("errctx", errctx_ptr)
+    .arg("result", pfinal_ndims)
+    .arg("ndims", ndims)
+    .arg("num_ndindexs", num_ndindexes)
+    .arg("ndindexs", ndindexs)
+    .returning_void();
+    check_error_context(generator, ctx, errctx_ptr);
+
+    pfinal_ndims.load(tyctx, ctx, "final_ndims")
+}
+
+pub fn call_nac3_ndarray_index<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    num_indexes: Int<'ctx, SizeT>,
+    indexes: Ptr<'ctx, StructModel<NDIndex>>,
+    src_ndarray: Ptr<'ctx, StructModel<NpArray>>,
+    dst_ndarray: Ptr<'ctx, StructModel<NpArray>>,
+) {
+    let tyctx = generator.type_context(ctx.ctx);
+
+    let perrctx = setup_error_context(tyctx, ctx);
+    CallFunction::begin(
+        tyctx,
+        ctx,
+        &get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_index"),
+    )
+    .arg("errctx", perrctx)
+    .arg("num_indexes", num_indexes)
+    .arg("indexes", indexes)
+    .arg("src_ndarray", src_ndarray)
+    .arg("dst_ndarray", dst_ndarray)
+    .returning_void();
+
+    check_error_context(generator, ctx, perrctx);
+}

nac3core/src/codegen/irrt/ndarray/mod.rs

@@ -0,0 +1,4 @@
+pub mod basic;
+pub mod broadcast;
+pub mod indexing;
+pub mod reshape;

nac3core/src/codegen/irrt/ndarray/reshape.rs

@@ -0,0 +1,31 @@
+use crate::codegen::{
+    irrt::{
+        error_context::{check_error_context, setup_error_context},
+        util::{function::CallFunction, get_sizet_dependent_function_name},
+    },
+    model::*,
+    CodeGenContext, CodeGenerator,
+};
+
+pub fn call_nac3_ndarray_resolve_and_check_new_shape<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    size: Int<'ctx, SizeT>,
+    new_ndims: Int<'ctx, SizeT>,
+    new_shape: Ptr<'ctx, IntModel<SizeT>>,
+) {
+    let tyctx = generator.type_context(ctx.ctx);
+
+    let perrctx = setup_error_context(tyctx, ctx);
+    CallFunction::begin(
+        tyctx,
+        ctx,
+        &get_sizet_dependent_function_name(tyctx, "__nac3_ndarray_resolve_and_check_new_shape"),
+    )
+    .arg("errctx", perrctx)
+    .arg("size", size)
+    .arg("new_ndims", new_ndims)
+    .arg("new_shape", new_shape)
+    .returning_void();
+    check_error_context(generator, ctx, perrctx);
+}

nac3core/src/codegen/irrt/slice.rs

@@ -0,0 +1,81 @@
+use crate::codegen::{model::*, CodeGenContext};
+
+// nac3core's slicing index/length values are always int32_t
+pub type SliceIndex = Int32;
+
+#[derive(Debug, Clone)]
+pub struct UserSliceFields<F: FieldVisitor> {
+    pub start_defined: F::Field<IntModel<Bool>>,
+    pub start: F::Field<IntModel<SliceIndex>>,
+    pub stop_defined: F::Field<IntModel<Bool>>,
+    pub stop: F::Field<IntModel<SliceIndex>>,
+    pub step_defined: F::Field<IntModel<Bool>>,
+    pub step: F::Field<IntModel<SliceIndex>>,
+}
+
+#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
+pub struct UserSlice;
+
+impl StructKind for UserSlice {
+    type Fields<F: FieldVisitor> = UserSliceFields<F>;
+
+    fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            start_defined: visitor.add("start_defined"),
+            start: visitor.add("start"),
+            stop_defined: visitor.add("stop_defined"),
+            stop: visitor.add("stop"),
+            step_defined: visitor.add("step_defined"),
+            step: visitor.add("step"),
+        }
+    }
+}
+
+#[derive(Debug, Clone)]
+pub struct RustUserSlice<'ctx> {
+    pub start: Option<Int<'ctx, SliceIndex>>,
+    pub stop: Option<Int<'ctx, SliceIndex>>,
+    pub step: Option<Int<'ctx, SliceIndex>>,
+}
+
+impl<'ctx> RustUserSlice<'ctx> {
+    // Set the values of an LLVM UserSlice
+    // in the format of Python's `slice()`
+    pub fn write_to_user_slice(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        dst_slice_ptr: Ptr<'ctx, StructModel<UserSlice>>,
+    ) {
+        let bool_model = IntModel(Bool);
+
+        let false_ = bool_model.constant(tyctx, ctx.ctx, 0);
+        let true_ = bool_model.constant(tyctx, ctx.ctx, 1);
+
+        // TODO: Code duplication. Probably okay...?
+
+        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_),
+        }
+    }
+}

nac3core/src/codegen/irrt/test.rs

@@ -0,0 +1,26 @@
+#[cfg(test)]
+mod tests {
+    use std::{path::Path, process::Command};
+
+    #[test]
+    fn run_irrt_test() {
+        assert!(
+            cfg!(feature = "test"),
+            "Please do `cargo test -F test` to compile `irrt_test.out` and run test"
+        );
+
+        let irrt_test_out_path = Path::new(concat!(env!("OUT_DIR"), "/irrt_test.out"));
+        let output = Command::new(irrt_test_out_path.to_str().unwrap()).output().unwrap();
+
+        if !output.status.success() {
+            eprintln!("irrt_test failed with status {}:", output.status);
+            eprintln!("====== stdout ======");
+            eprintln!("{}", String::from_utf8(output.stdout).unwrap());
+            eprintln!("====== stderr ======");
+            eprintln!("{}", String::from_utf8(output.stderr).unwrap());
+            eprintln!("====================");
+
+            panic!("irrt_test failed");
+        }
+    }
+}

nac3core/src/codegen/irrt/util.rs

@@ -0,0 +1,103 @@
+use crate::codegen::model::*;
+
+// 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(tyctx: TypeContext<'_>, name: &str) -> String {
+    let mut name = name.to_owned();
+    match tyctx.size_type.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
+}
+
+pub mod function {
+    use crate::codegen::{model::*, CodeGenContext};
+    use inkwell::{
+        types::{BasicMetadataTypeEnum, BasicType, FunctionType},
+        values::{AnyValue, BasicMetadataValueEnum, BasicValue, BasicValueEnum, CallSiteValue},
+    };
+    use itertools::Itertools;
+
+    #[derive(Debug, Clone, Copy)]
+    struct Arg<'ctx> {
+        ty: BasicMetadataTypeEnum<'ctx>,
+        val: BasicMetadataValueEnum<'ctx>,
+    }
+
+    /// Helper structure to reduce IRRT Inkwell function call boilerplate
+    /// TODO: Optimize
+    pub struct CallFunction<'ctx, 'a, 'b, 'c> {
+        tyctx: TypeContext<'ctx>,
+        ctx: &'b CodeGenContext<'ctx, 'a>,
+        /// Function name
+        name: &'c str,
+        /// Call arguments
+        args: Vec<Arg<'ctx>>,
+    }
+
+    impl<'ctx, 'a, 'b, 'c> CallFunction<'ctx, 'a, 'b, 'c> {
+        pub fn begin(
+            tyctx: TypeContext<'ctx>,
+            ctx: &'b CodeGenContext<'ctx, 'a>,
+            name: &'c str,
+        ) -> Self {
+            CallFunction { tyctx, ctx, name, args: Vec::new() }
+        }
+
+        /// Push a call argument to the function call.
+        ///
+        /// The `_name` parameter is there for self-documentation purposes.
+        #[allow(clippy::needless_pass_by_value)]
+        pub fn arg<M: Model>(mut self, _name: &str, arg: Instance<'ctx, M>) -> Self {
+            let arg = Arg {
+                ty: arg.model.get_type(self.tyctx, self.ctx.ctx).as_basic_type_enum().into(),
+                val: arg.value.as_basic_value_enum().into(),
+            };
+            self.args.push(arg);
+            self
+        }
+
+        /// Like [`CallFunction::returning_`] but `return_model` is automatically inferred.
+        pub fn returning<M: Model>(self, name: &str) -> Instance<'ctx, M> {
+            self.returning_(name, M::default())
+        }
+
+        /// Call the function and expect the function to return a value of type of `return_model`.
+        pub fn returning_<M: Model>(self, name: &str, return_model: M) -> Instance<'ctx, M> {
+            let ret_ty = return_model.get_type(self.tyctx, 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.tyctx, self.ctx.ctx, ret).unwrap(); // Must work
+            ret
+        }
+
+        /// 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, declare the function if it doesn't exist - it will be defined by other
+            // components of NAC3.
+            let func = self.ctx.module.get_function(self.name).unwrap_or_else(|| {
+                let tys = self.args.iter().map(|arg| arg.ty).collect_vec();
+                let fn_type = make_fn_type(&tys);
+                self.ctx.module.add_function(self.name, fn_type, None)
+            });
+
+            let vals = self.args.iter().map(|arg| arg.val).collect_vec();
+            self.ctx.builder.build_call(func, &vals, return_value_name).unwrap()
+        }
+    }
+}

nac3core/src/codegen/llvm_intrinsics.rs

@@ -1,14 +1,12 @@
-use inkwell::{
+use crate::codegen::CodeGenContext;
-    context::Context,
+use inkwell::context::Context;
-    intrinsics::Intrinsic,
+use inkwell::intrinsics::Intrinsic;
-    types::{AnyTypeEnum::IntType, FloatType},
+use inkwell::types::AnyTypeEnum::IntType;
-    values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue, PointerValue},
+use inkwell::types::FloatType;
-    AddressSpace,
+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 {
@@ -37,40 +35,6 @@ fn get_float_intrinsic_repr(ctx: &Context, ft: FloatType) -> &'static str {
     unreachable!()
 }
 
-/// Invokes the [`llvm.va_start`](https://llvm.org/docs/LangRef.html#llvm-va-start-intrinsic)
-/// intrinsic.
-pub fn call_va_start<'ctx>(ctx: &CodeGenContext<'ctx, '_>, arglist: PointerValue<'ctx>) {
-    const FN_NAME: &str = "llvm.va_start";
-
-    let intrinsic_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
-        let llvm_void = ctx.ctx.void_type();
-        let llvm_i8 = ctx.ctx.i8_type();
-        let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
-        let fn_type = llvm_void.fn_type(&[llvm_p0i8.into()], false);
-
-        ctx.module.add_function(FN_NAME, fn_type, None)
-    });
-
-    ctx.builder.build_call(intrinsic_fn, &[arglist.into()], "").unwrap();
-}
-
-/// Invokes the [`llvm.va_start`](https://llvm.org/docs/LangRef.html#llvm-va-start-intrinsic)
-/// intrinsic.
-pub fn call_va_end<'ctx>(ctx: &CodeGenContext<'ctx, '_>, arglist: PointerValue<'ctx>) {
-    const FN_NAME: &str = "llvm.va_end";
-
-    let intrinsic_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
-        let llvm_void = ctx.ctx.void_type();
-        let llvm_i8 = ctx.ctx.i8_type();
-        let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
-        let fn_type = llvm_void.fn_type(&[llvm_p0i8.into()], false);
-
-        ctx.module.add_function(FN_NAME, fn_type, None)
-    });
-
-    ctx.builder.build_call(intrinsic_fn, &[arglist.into()], "").unwrap();
-}
-
 /// Invokes the [`llvm.stacksave`](https://llvm.org/docs/LangRef.html#llvm-stacksave-intrinsic)
 /// intrinsic.
 pub fn call_stacksave<'ctx>(
@@ -185,7 +149,7 @@ 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 +157,7 @@ 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()
     };
@@ -207,9 +171,8 @@ pub fn call_memcpy_generic<'ctx>(
 /// * `$ctx:ident`: Reference to the current Code Generation Context
 /// * `$name:ident`: Optional name to be assigned to the llvm build call (Option<&str>)
 /// * `$llvm_name:literal`: Name of underlying llvm intrinsic function
-/// * `$map_fn:ident`: Mapping function to be applied on `BasicValue` (`BasicValue` -> Function Return Type).
+/// * `$map_fn:ident`: Mapping function to be applied on `BasicValue` (`BasicValue` -> Function Return Type)
-///   Use `BasicValueEnum::into_int_value` for Integer return type and
+/// Use `BasicValueEnum::into_int_value` for Integer return type and `BasicValueEnum::into_float_value` for Float return type
-///   `BasicValueEnum::into_float_value` for Float return type
 /// * `$llvm_ty:ident`: Type of first operand
 /// * `,($val:ident)*`: Comma separated list of operands
 macro_rules! generate_llvm_intrinsic_fn_body {
@@ -225,8 +188,8 @@ macro_rules! generate_llvm_intrinsic_fn_body {
 /// Arguments:
 /// * `float/int`: Indicates the return and argument type of the function
 /// * `$fn_name:ident`: The identifier of the rust function to be generated
-/// * `$llvm_name:literal`: Name of underlying llvm intrinsic function.
+/// * `$llvm_name:literal`: Name of underlying llvm intrinsic function
-///   Omit "llvm." prefix from the function name i.e. use "ceil" instead of "llvm.ceil"
+/// Omit "llvm." prefix from the function name i.e. use "ceil" instead of "llvm.ceil"
 /// * `$val:ident`: The operand for unary operations
 /// * `$val1:ident`, `$val2:ident`: The operands for binary operations
 macro_rules! generate_llvm_intrinsic_fn {

nac3core/src/codegen/mod.rs

@@ -1,12 +1,12 @@
-use std::{
+use crate::{
-    collections::{HashMap, HashSet},
+    codegen::classes::{ListType, ProxyType, RangeType},
-    sync::{
+    symbol_resolver::{StaticValue, SymbolResolver},
-        atomic::{AtomicBool, Ordering},
+    toplevel::{helper::PrimDef, TopLevelContext, TopLevelDef},
-        Arc,
+    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 +24,16 @@ use inkwell::{
     AddressSpace, IntPredicate, OptimizationLevel,
 };
 use itertools::Itertools;
-use parking_lot::{Condvar, Mutex};
+use model::*;
-
 use nac3parser::ast::{Location, Stmt, StrRef};
-
+use parking_lot::{Condvar, Mutex};
-use crate::{
+use std::collections::{HashMap, HashSet};
-    symbol_resolver::{StaticValue, SymbolResolver},
+use std::sync::{
-    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, TopLevelContext, TopLevelDef},
+    atomic::{AtomicBool, Ordering},
-    typecheck::{
+    Arc,
-        type_inferencer::{CodeLocation, PrimitiveStore},
-        typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
-    },
 };
-use classes::{ListType, NDArrayType, ProxyType, RangeType};
+use std::thread;
-use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
+use structure::{cslice::CSlice, exception::Exception, ndarray::NpArray};
-pub use generator::{CodeGenerator, DefaultCodeGenerator};
 
 pub mod builtin_fns;
 pub mod classes;
@@ -48,27 +43,18 @@ pub mod extern_fns;
 mod generator;
 pub mod irrt;
 pub mod llvm_intrinsics;
+pub mod model;
 pub mod numpy;
+pub mod numpy_new;
 pub mod stmt;
+pub mod structure;
+pub mod util;
 
 #[cfg(test)]
 mod test;
 
-mod macros {
+use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
-    /// Codegen-variant of [`std::unreachable`] which accepts an instance of [`CodeGenContext`] as
+pub use generator::{CodeGenerator, DefaultCodeGenerator};
-    /// 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;
-}
 
 #[derive(Default)]
 pub struct StaticValueStore {
@@ -188,11 +174,11 @@ pub struct CodeGenContext<'ctx, 'a> {
     pub registry: &'a WorkerRegistry,
 
     /// Cache for constant strings.
-    pub const_strings: HashMap<String, BasicValueEnum<'ctx>>,
+    pub const_strings: HashMap<String, Struct<'ctx, CSlice>>,
 
     /// [`BasicBlock`] containing all `alloca` statements for the current function.
     pub init_bb: BasicBlock<'ctx>,
-    pub exception_val: Option<PointerValue<'ctx>>,
+    pub exception_val: Option<Ptr<'ctx, StructModel<Exception>>>,
 
     /// The header and exit basic blocks of a loop in this context. See
     /// <https://llvm.org/docs/LoopTerminology.html> for explanation of these terminology.
@@ -464,7 +450,7 @@ pub struct CodeGenTask {
 fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
     ctx: &'ctx Context,
     module: &Module<'ctx>,
-    generator: &G,
+    generator: &mut G,
     unifier: &mut Unifier,
     top_level: &TopLevelContext,
     type_cache: &mut HashMap<Type, BasicTypeEnum<'ctx>>,
@@ -509,12 +495,9 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
                         }
 
                         TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-                            let (dtype, _) = unpack_ndarray_var_tys(unifier, ty);
+                            let tyctx = generator.type_context(ctx);
-                            let element_type = get_llvm_type(
+                            let pndarray_model = PtrModel(StructModel(NpArray));
-                                ctx, module, generator, unifier, top_level, type_cache, dtype,
+                            pndarray_model.get_type(tyctx, ctx).into()
-                            );
-
-                            NDArrayType::new(generator, ctx, element_type).as_base_type().into()
                         }
 
                         _ => unreachable!(
@@ -558,10 +541,8 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
                 };
                 return ty;
             }
-            TTuple { ty, is_vararg_ctx } => {
+            TTuple { ty } => {
                 // a struct with fields in the order present in the tuple
-                assert!(!is_vararg_ctx, "Tuples in vararg context must be instantiated with the correct number of arguments before calling get_llvm_type");
-
                 let fields = ty
                     .iter()
                     .map(|ty| {
@@ -591,7 +572,7 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
 fn get_llvm_abi_type<'ctx, G: CodeGenerator + ?Sized>(
     ctx: &'ctx Context,
     module: &Module<'ctx>,
-    generator: &G,
+    generator: &mut G,
     unifier: &mut Unifier,
     top_level: &TopLevelContext,
     type_cache: &mut HashMap<Type, BasicTypeEnum<'ctx>>,
@@ -600,11 +581,11 @@ fn get_llvm_abi_type<'ctx, G: CodeGenerator + ?Sized>(
 ) -> BasicTypeEnum<'ctx> {
     // If the type is used in the definition of a function, return `i1` instead of `i8` for ABI
     // consistency.
-    if unifier.unioned(ty, primitives.bool) {
+    return if unifier.unioned(ty, primitives.bool) {
         ctx.bool_type().into()
     } else {
         get_llvm_type(ctx, module, generator, unifier, top_level, type_cache, ty)
-    }
+    };
 }
 
 /// Whether `sret` is needed for a return value with type `ty`.
@@ -629,40 +610,6 @@ fn need_sret(ty: BasicTypeEnum) -> bool {
     need_sret_impl(ty, true)
 }
 
-/// Returns the [`BasicTypeEnum`] representing a `va_list` struct for variadic arguments.
-fn get_llvm_valist_type<'ctx>(ctx: &'ctx Context, triple: &TargetTriple) -> BasicTypeEnum<'ctx> {
-    let triple = TargetMachine::normalize_triple(triple);
-    let triple = triple.as_str().to_str().unwrap();
-    let arch = triple.split('-').next().unwrap();
-
-    let llvm_pi8 = ctx.i8_type().ptr_type(AddressSpace::default());
-
-    // Referenced from parseArch() in llvm/lib/Support/Triple.cpp
-    match arch {
-        "i386" | "i486" | "i586" | "i686" | "riscv32" => {
-            ctx.i8_type().ptr_type(AddressSpace::default()).into()
-        }
-        "amd64" | "x86_64" | "x86_64h" => {
-            let llvm_i32 = ctx.i32_type();
-
-            let va_list_tag = ctx.opaque_struct_type("struct.__va_list_tag");
-            va_list_tag.set_body(
-                &[llvm_i32.into(), llvm_i32.into(), llvm_pi8.into(), llvm_pi8.into()],
-                false,
-            );
-            va_list_tag.into()
-        }
-        "armv7" => {
-            let va_list = ctx.opaque_struct_type("struct.__va_list");
-            va_list.set_body(&[llvm_pi8.into()], false);
-            va_list.into()
-        }
-        triple => {
-            todo!("Unsupported platform for varargs: {triple}")
-        }
-    }
-}
-
 /// Implementation for generating LLVM IR for a function.
 pub fn gen_func_impl<
     'ctx,
@@ -720,43 +667,20 @@ pub fn gen_func_impl<
         ..primitives
     };
 
-    let mut type_cache: HashMap<_, _> = [
+    let type_context = generator.type_context(context);
+    let cslice_model = StructModel(CSlice);
+    let pexn_model = PtrModel(StructModel(Exception));
+
+    let mut type_cache: HashMap<_, BasicTypeEnum<'ctx>> = [
         (primitives.int32, context.i32_type().into()),
         (primitives.int64, context.i64_type().into()),
         (primitives.uint32, context.i32_type().into()),
         (primitives.uint64, context.i64_type().into()),
         (primitives.float, context.f64_type().into()),
         (primitives.bool, context.i8_type().into()),
-        (primitives.str, {
+        (primitives.str, cslice_model.get_type(type_context, context).into()),
-            let name = "str";
-            match module.get_struct_type(name) {
-                None => {
-                    let str_type = context.opaque_struct_type("str");
-                    let fields = [
-                        context.i8_type().ptr_type(AddressSpace::default()).into(),
-                        generator.get_size_type(context).into(),
-                    ];
-                    str_type.set_body(&fields, false);
-                    str_type.into()
-                }
-                Some(t) => t.as_basic_type_enum(),
-            }
-        }),
         (primitives.range, RangeType::new(context).as_base_type().into()),
-        (primitives.exception, {
+        (primitives.exception, pexn_model.get_type(type_context, context).into()),
-            let name = "Exception";
-            if let Some(t) = module.get_struct_type(name) {
-                t.ptr_type(AddressSpace::default()).as_basic_type_enum()
-            } else {
-                let exception = context.opaque_struct_type("Exception");
-                let int32 = context.i32_type().into();
-                let int64 = context.i64_type().into();
-                let str_ty = module.get_struct_type("str").unwrap().as_basic_type_enum();
-                let fields = [int32, str_ty, int32, int32, str_ty, str_ty, int64, int64, int64];
-                exception.set_body(&fields, false);
-                exception.ptr_type(AddressSpace::default()).as_basic_type_enum()
-            }
-        }),
     ]
     .iter()
     .copied()
@@ -774,7 +698,6 @@ pub fn gen_func_impl<
                 name: arg.name,
                 ty: task.store.to_unifier_type(&mut unifier, &primitives, arg.ty, &mut cache),
                 default_value: arg.default_value.clone(),
-                is_vararg: arg.is_vararg,
             })
             .collect_vec(),
         task.store.to_unifier_type(&mut unifier, &primitives, *ret, &mut cache),
@@ -797,10 +720,7 @@ pub fn gen_func_impl<
     let has_sret = ret_type.map_or(false, |ty| need_sret(ty));
     let mut params = args
         .iter()
-        .filter(|arg| !arg.is_vararg)
         .map(|arg| {
-            debug_assert!(!arg.is_vararg);
-
             get_llvm_abi_type(
                 context,
                 &module,
@@ -819,12 +739,9 @@ pub fn gen_func_impl<
         params.insert(0, ret_type.unwrap().ptr_type(AddressSpace::default()).into());
     }
 
-    debug_assert!(matches!(args.iter().filter(|arg| arg.is_vararg).count(), 0..=1));
-    let vararg_arg = args.iter().find(|arg| arg.is_vararg);
-
     let fn_type = match ret_type {
-        Some(ret_type) if !has_sret => ret_type.fn_type(&params, vararg_arg.is_some()),
+        Some(ret_type) if !has_sret => ret_type.fn_type(&params, false),
-        _ => context.void_type().fn_type(&params, vararg_arg.is_some()),
+        _ => context.void_type().fn_type(&params, false),
     };
 
     let symbol = &task.symbol_name;
@@ -852,10 +769,9 @@ 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);
-    for (n, arg) in args.iter().enumerate().filter(|(_, arg)| !arg.is_vararg) {
+    for (n, arg) in args.iter().enumerate() {
         let param = fn_val.get_nth_param((n as u32) + offset).unwrap();
         let local_type = get_llvm_type(
             context,
@@ -888,8 +804,6 @@ pub fn gen_func_impl<
         var_assignment.insert(arg.name, (alloca, None, 0));
     }
 
-    // TODO: Save vararg parameters as list
-
     let return_buffer = if has_sret {
         Some(fn_val.get_nth_param(0).unwrap().into_pointer_value())
     } else {
@@ -1112,9 +1026,3 @@ fn gen_in_range_check<'ctx>(
 
     ctx.builder.build_int_compare(IntPredicate::SLT, lo, hi, "cmp").unwrap()
 }
-
-/// Returns the internal name for the `va_count` argument, used to indicate the number of arguments
-/// passed to the variadic function.
-fn get_va_count_arg_name(arg_name: StrRef) -> StrRef {
-    format!("__{}_va_count", &arg_name).into()
-}

nac3core/src/codegen/model/core.rs

@@ -0,0 +1,161 @@
+use std::fmt;
+
+use inkwell::{context::Context, types::*, values::*};
+
+use super::*;
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+#[derive(Clone, Copy)]
+pub struct TypeContext<'ctx> {
+    pub size_type: IntType<'ctx>,
+}
+
+pub trait HasTypeContext {
+    fn type_context<'ctx>(&self, ctx: &'ctx Context) -> TypeContext<'ctx>;
+}
+
+impl<T: CodeGenerator + ?Sized> HasTypeContext for T {
+    fn type_context<'ctx>(&self, ctx: &'ctx Context) -> TypeContext<'ctx> {
+        TypeContext { size_type: self.get_size_type(ctx) }
+    }
+}
+
+#[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
+    }
+}
+
+/// A [`Model`] is a singleton object that uniquely identifies a [`BasicType`]
+/// solely from a [`CodeGenerator`] and a [`Context`].
+pub trait Model: CheckType + fmt::Debug + Clone + Copy + Default {
+    type Value<'ctx>: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>>;
+    type Type<'ctx>: BasicType<'ctx>;
+
+    /// Return the [`BasicType`] of this model.
+    fn get_type<'ctx>(&self, tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> Self::Type<'ctx>;
+
+    /// Check if a [`BasicType`] is the same type of this model.
+    fn check_type<'ctx, T: BasicType<'ctx>>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &'ctx Context,
+        ty: T,
+    ) -> Result<(), ModelError> {
+        let ty = ty.as_basic_type_enum();
+        self.check_type_impl(tyctx, ctx, ty.as_basic_type_enum())
+    }
+
+    /// 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.
+    fn believe_value<'ctx>(&self, value: Self::Value<'ctx>) -> 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<'ctx, V: BasicValue<'ctx>>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &'ctx Context,
+        value: V,
+    ) -> Result<Instance<'ctx, Self>, ModelError> {
+        let value = value.as_basic_value_enum();
+        self.check_type(tyctx, ctx, value.get_type())
+            .map_err(|err| err.under_context("the value {value:?}"))?;
+
+        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<'ctx>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        name: &str,
+    ) -> Ptr<'ctx, Self> {
+        let pmodel = PtrModel(*self);
+        let p = ctx.builder.build_alloca(self.get_type(tyctx, ctx.ctx), name).unwrap();
+        pmodel.believe_value(p)
+    }
+
+    // Allocate an array on the stack and return its pointer.
+    fn array_alloca<'ctx>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        len: IntValue<'ctx>,
+        name: &str,
+    ) -> Ptr<'ctx, Self> {
+        let pmodel = PtrModel(*self);
+        let p = ctx.builder.build_array_alloca(self.get_type(tyctx, ctx.ctx), len, name).unwrap();
+        pmodel.believe_value(p)
+    }
+
+    fn var_alloca<'ctx, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&str>,
+    ) -> Result<Ptr<'ctx, Self>, String> {
+        let tyctx = generator.type_context(ctx.ctx);
+
+        let pmodel = PtrModel(*self);
+        let p = generator.gen_var_alloc(
+            ctx,
+            self.get_type(tyctx, ctx.ctx).as_basic_type_enum(),
+            name,
+        )?;
+        Ok(pmodel.believe_value(p))
+    }
+
+    fn array_var_alloca<'ctx, G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        len: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> Result<Ptr<'ctx, Self>, String> {
+        let tyctx = generator.type_context(ctx.ctx);
+
+        // TODO: Remove ArraySliceValue
+        let pmodel = PtrModel(*self);
+        let p = generator.gen_array_var_alloc(
+            ctx,
+            self.get_type(tyctx, ctx.ctx).as_basic_type_enum(),
+            len,
+            name,
+        )?;
+        Ok(pmodel.believe_value(PointerValue::from(p)))
+    }
+}
+
+#[derive(Debug, Clone, Copy)]
+pub struct Instance<'ctx, M: Model> {
+    /// 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<'ctx>,
+}
+
+// NOTE: Must be Rust object-safe - This must be typeable for a Rust trait object.
+pub trait CheckType {
+    fn check_type_impl<'ctx>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &'ctx Context,
+        ty: BasicTypeEnum<'ctx>,
+    ) -> Result<(), ModelError>;
+}

nac3core/src/codegen/model/int.rs

@@ -0,0 +1,228 @@
+use std::fmt;
+
+use inkwell::{
+    context::Context,
+    types::{BasicTypeEnum, IntType},
+    values::IntValue,
+    IntPredicate,
+};
+
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+use super::*;
+
+pub trait IntKind: fmt::Debug + Clone + Copy + Default {
+    fn get_int_type<'ctx>(&self, tyctx: TypeContext<'ctx>, 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 IntKind for Bool {
+    fn get_int_type<'ctx>(&self, _tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> IntType<'ctx> {
+        ctx.bool_type()
+    }
+}
+
+impl IntKind for Byte {
+    fn get_int_type<'ctx>(&self, _tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> IntType<'ctx> {
+        ctx.i8_type()
+    }
+}
+
+impl IntKind for Int32 {
+    fn get_int_type<'ctx>(&self, _tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> IntType<'ctx> {
+        ctx.i32_type()
+    }
+}
+
+impl IntKind for Int64 {
+    fn get_int_type<'ctx>(&self, _tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> IntType<'ctx> {
+        ctx.i64_type()
+    }
+}
+
+impl IntKind for SizeT {
+    fn get_int_type<'ctx>(&self, tyctx: TypeContext<'ctx>, _ctx: &'ctx Context) -> IntType<'ctx> {
+        tyctx.size_type
+    }
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct IntModel<N: IntKind>(pub N);
+pub type Int<'ctx, N> = Instance<'ctx, IntModel<N>>;
+
+impl<N: IntKind> CheckType for IntModel<N> {
+    fn check_type_impl<'ctx>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &'ctx Context,
+        ty: BasicTypeEnum<'ctx>,
+    ) -> Result<(), ModelError> {
+        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(tyctx, 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<N: IntKind> Model for IntModel<N> {
+    type Value<'ctx> = IntValue<'ctx>;
+    type Type<'ctx> = IntType<'ctx>;
+
+    #[must_use]
+    fn get_type<'ctx>(&self, tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> Self::Type<'ctx> {
+        self.0.get_int_type(tyctx, ctx)
+    }
+}
+
+impl<N: IntKind> IntModel<N> {
+    pub fn constant<'ctx>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &'ctx Context,
+        value: u64,
+    ) -> Int<'ctx, N> {
+        let value = self.get_type(tyctx, ctx).const_int(value, false);
+        self.believe_value(value)
+    }
+
+    pub fn const_0<'ctx>(&self, tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> Int<'ctx, N> {
+        self.constant(tyctx, ctx, 0)
+    }
+
+    pub fn const_1<'ctx>(&self, tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> Int<'ctx, N> {
+        self.constant(tyctx, ctx, 1)
+    }
+
+    pub fn s_extend_or_bit_cast<'ctx>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+        name: &str,
+    ) -> Int<'ctx, N> {
+        let value = ctx
+            .builder
+            .build_int_s_extend_or_bit_cast(value, self.get_type(tyctx, ctx.ctx), name)
+            .unwrap();
+        self.believe_value(value)
+    }
+
+    pub fn truncate<'ctx>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        value: IntValue<'ctx>,
+        name: &str,
+    ) -> Int<'ctx, N> {
+        let value =
+            ctx.builder.build_int_truncate(value, self.get_type(tyctx, ctx.ctx), name).unwrap();
+        self.believe_value(value)
+    }
+}
+
+impl IntModel<Bool> {
+    #[must_use]
+    pub fn const_false<'ctx>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &'ctx Context,
+    ) -> Int<'ctx, Bool> {
+        self.constant(tyctx, ctx, 0)
+    }
+
+    #[must_use]
+    pub fn const_true<'ctx>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &'ctx Context,
+    ) -> Int<'ctx, Bool> {
+        self.constant(tyctx, ctx, 1)
+    }
+}
+
+impl<'ctx, N: IntKind> Int<'ctx, N> {
+    pub fn s_extend_or_bit_cast<NewN: IntKind, G: CodeGenerator + ?Sized>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+        name: &str,
+    ) -> Int<'ctx, NewN> {
+        IntModel(to_int_kind).s_extend_or_bit_cast(tyctx, ctx, self.value, name)
+    }
+
+    pub fn truncate<NewN: IntKind, G: CodeGenerator + ?Sized>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        to_int_kind: NewN,
+        name: &str,
+    ) -> Int<'ctx, NewN> {
+        IntModel(to_int_kind).truncate(tyctx, ctx, self.value, name)
+    }
+
+    #[must_use]
+    pub fn add<G: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        other: Int<'ctx, N>,
+        name: &str,
+    ) -> Int<'ctx, N> {
+        let value = ctx.builder.build_int_add(self.value, other.value, name).unwrap();
+        self.model.believe_value(value)
+    }
+
+    #[must_use]
+    pub fn sub<G: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        other: Int<'ctx, N>,
+        name: &str,
+    ) -> Int<'ctx, N> {
+        let value = ctx.builder.build_int_sub(self.value, other.value, name).unwrap();
+        self.model.believe_value(value)
+    }
+
+    #[must_use]
+    pub fn mul<G: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        other: Int<'ctx, N>,
+        name: &str,
+    ) -> Int<'ctx, N> {
+        let value = ctx.builder.build_int_mul(self.value, other.value, name).unwrap();
+        self.model.believe_value(value)
+    }
+
+    pub fn compare<G: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        op: IntPredicate,
+        other: Int<'ctx, N>,
+        name: &str,
+    ) -> Int<'ctx, Bool> {
+        let bool_model = IntModel(Bool);
+        let value = ctx.builder.build_int_compare(op, self.value, other.value, name).unwrap();
+        bool_model.believe_value(value)
+    }
+}

nac3core/src/codegen/model/mod.rs

@@ -0,0 +1,12 @@
+mod core;
+mod int;
+mod ptr;
+mod slice;
+mod structure;
+pub mod util;
+
+pub use core::*;
+pub use int::*;
+pub use ptr::*;
+pub use slice::*;
+pub use structure::*;

nac3core/src/codegen/model/ptr.rs

@@ -0,0 +1,142 @@
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum, PointerType},
+    values::{IntValue, PointerValue},
+    AddressSpace,
+};
+
+use crate::codegen::CodeGenContext;
+
+use super::*;
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct PtrModel<Element>(pub Element);
+pub type Ptr<'ctx, Element> = Instance<'ctx, PtrModel<Element>>;
+
+impl<Element: CheckType> CheckType for PtrModel<Element> {
+    fn check_type_impl<'ctx>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &'ctx Context,
+        ty: BasicTypeEnum<'ctx>,
+    ) -> Result<(), super::ModelError> {
+        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_impl(tyctx, ctx, elem_ty)
+            .map_err(|err| err.under_context("a PointerType"))?;
+
+        Ok(())
+    }
+}
+
+impl<Element: Model> Model for PtrModel<Element> {
+    type Value<'ctx> = PointerValue<'ctx>;
+    type Type<'ctx> = PointerType<'ctx>;
+
+    fn get_type<'ctx>(&self, tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> Self::Type<'ctx> {
+        self.0.get_type(tyctx, ctx).ptr_type(AddressSpace::default())
+    }
+}
+
+impl<Element: Model> PtrModel<Element> {
+    /// Return a ***constant*** nullptr.
+    pub fn nullptr<'ctx>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &'ctx Context,
+    ) -> Ptr<'ctx, Element> {
+        let ptr = self.get_type(tyctx, ctx).const_null();
+        self.believe_value(ptr)
+    }
+
+    pub fn transmute<'ctx>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        ptr: PointerValue<'ctx>,
+        name: &str,
+    ) -> Ptr<'ctx, Element> {
+        let ptr = ctx.builder.build_pointer_cast(ptr, self.get_type(tyctx, ctx.ctx), name).unwrap();
+        self.believe_value(ptr)
+    }
+}
+
+impl<'ctx, Element: Model> Ptr<'ctx, Element> {
+    /// Offset the pointer by [`inkwell::builder::Builder::build_in_bounds_gep`].
+    #[must_use]
+    pub fn offset(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        offset: IntValue<'ctx>,
+        name: &str,
+    ) -> Ptr<'ctx, Element> {
+        let new_ptr =
+            unsafe { ctx.builder.build_in_bounds_gep(self.value, &[offset], name).unwrap() };
+        self.model.check_value(tyctx, ctx.ctx, new_ptr).unwrap()
+    }
+
+    // Load the `i`-th element (0-based) on the array with [`inkwell::builder::Builder::build_in_bounds_gep`].
+    pub fn ix(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        i: IntValue<'ctx>,
+        name: &str,
+    ) -> Instance<'ctx, Element> {
+        self.offset(tyctx, ctx, i, name).load(tyctx, ctx, name)
+    }
+
+    /// Load the value with [`inkwell::builder::Builder::build_load`].
+    pub fn load(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        name: &str,
+    ) -> Instance<'ctx, Element> {
+        let value = ctx.builder.build_load(self.value, name).unwrap();
+        self.model.0.check_value(tyctx, 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, Element>) {
+        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 transmute<NewElement: Model>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        new_model: NewElement,
+        name: &str,
+    ) -> Ptr<'ctx, NewElement> {
+        PtrModel(new_model).transmute(tyctx, ctx, self.value, name)
+    }
+
+    /// Check if the pointer is null with [`inkwell::builder::Builder::build_is_null`].
+    pub fn is_null(&self, ctx: &CodeGenContext<'ctx, '_>, name: &str) -> Int<'ctx, Bool> {
+        let bool_model = IntModel(Bool);
+        let value = ctx.builder.build_is_null(self.value, name).unwrap();
+        bool_model.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, '_>, name: &str) -> Int<'ctx, Bool> {
+        let bool_model = IntModel(Bool);
+        let value = ctx.builder.build_is_not_null(self.value, name).unwrap();
+        bool_model.believe_value(value)
+    }
+}

nac3core/src/codegen/model/slice.rs

@@ -0,0 +1,72 @@
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+use super::*;
+
+/// A slice - literally just a pointer and a length value.
+///
+/// NOTE: This is NOT a [`Model`].
+pub struct ArraySlice<'ctx, Len: IntKind, Item: Model> {
+    pub base: Ptr<'ctx, Item>,
+    pub len: Int<'ctx, Len>,
+}
+
+impl<'ctx, Len: IntKind, Item: Model> ArraySlice<'ctx, Len, Item> {
+    /// Get the `idx`-nth element of this [`ArraySlice`], but doesn't do an assertion to see if `idx` is out of bounds or not.
+    ///
+    /// Also see [`ArraySlice::ix`].
+    pub fn ix_unchecked(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        idx: Int<'ctx, Len>,
+        name: &str,
+    ) -> Ptr<'ctx, Item> {
+        let element_ptr = unsafe {
+            ctx.builder.build_in_bounds_gep(self.base.value, &[idx.value], name).unwrap()
+        };
+        self.base.model.check_value(tyctx, ctx.ctx, element_ptr).unwrap()
+    }
+
+    /// Call [`ArraySlice::ix_unchecked`], but checks if `idx` is in bounds, otherwise a runtime `IndexError` will be thrown.
+    pub fn ix<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        idx: Int<'ctx, Len>,
+        name: &str,
+    ) -> Ptr<'ctx, Item> {
+        let tyctx = generator.type_context(ctx.ctx);
+        let len_model = IntModel(Len::default());
+
+        // Assert `0 <= idx < length` and throw an Exception if `idx` is out of bounds
+        let lower_bounded = ctx
+            .builder
+            .build_int_compare(
+                inkwell::IntPredicate::SLE,
+                len_model.constant(tyctx, ctx.ctx, 0).value,
+                idx.value,
+                "lower_bounded",
+            )
+            .unwrap();
+        let upper_bounded = ctx
+            .builder
+            .build_int_compare(
+                inkwell::IntPredicate::SLT,
+                idx.value,
+                self.len.value,
+                "upper_bounded",
+            )
+            .unwrap();
+        let bounded = ctx.builder.build_and(lower_bounded, upper_bounded, "bounded").unwrap();
+        ctx.make_assert(
+            generator,
+            bounded,
+            "0:IndexError",
+            "nac3core LLVM codegen attempting to access out of bounds array index {0}. Must satisfy 0 <= index < {2}",
+            [ Some(idx.value), Some(self.len.value), None],
+            ctx.current_loc
+        );
+
+        self.ix_unchecked(tyctx, ctx, idx, name)
+    }
+}

nac3core/src/codegen/model/structure.rs

@@ -0,0 +1,174 @@
+use std::fmt;
+
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum, StructType},
+    values::StructValue,
+};
+use itertools::izip;
+
+use crate::codegen::CodeGenContext;
+
+use super::*;
+
+#[derive(Debug, Clone, Copy)]
+pub struct GepField<M: Model> {
+    pub gep_index: u64,
+    pub name: &'static str,
+    pub model: M,
+}
+
+pub trait FieldVisitor {
+    type Field<M: Model + 'static>;
+
+    fn add<M: Model + 'static>(&mut self, name: &'static str) -> Self::Field<M>;
+}
+
+pub struct GepFieldVisitor {
+    gep_index_counter: u64,
+}
+
+impl FieldVisitor for GepFieldVisitor {
+    type Field<M: Model + 'static> = GepField<M>;
+
+    fn add<M: Model + 'static>(&mut self, name: &'static str) -> Self::Field<M> {
+        let gep_index = self.gep_index_counter;
+        self.gep_index_counter += 1;
+        Self::Field { gep_index, name, model: M::default() }
+    }
+}
+
+struct TypeFieldVisitor<'ctx> {
+    tyctx: TypeContext<'ctx>,
+    ctx: &'ctx Context,
+    field_types: Vec<BasicTypeEnum<'ctx>>,
+}
+
+impl<'ctx> FieldVisitor for TypeFieldVisitor<'ctx> {
+    type Field<M: Model + 'static> = ();
+
+    fn add<M: Model + 'static>(&mut self, _name: &'static str) -> Self::Field<M> {
+        self.field_types.push(M::default().get_type(self.tyctx, self.ctx).as_basic_type_enum());
+    }
+}
+
+struct CheckTypeEntry {
+    check_type: Box<dyn CheckType + 'static>,
+    name: &'static str,
+}
+
+struct CheckTypeFieldVisitor<'ctx> {
+    tyctx: TypeContext<'ctx>,
+    ctx: &'ctx Context,
+    check_types: Vec<CheckTypeEntry>,
+}
+
+impl<'ctx> FieldVisitor for CheckTypeFieldVisitor<'ctx> {
+    type Field<M: Model + 'static> = ();
+
+    fn add<M: Model + 'static>(&mut self, name: &'static str) -> Self::Field<M> {
+        self.check_types.push(CheckTypeEntry { check_type: Box::<M>::default(), name });
+    }
+}
+
+pub trait StructKind: fmt::Debug + Clone + Copy + Default {
+    type Fields<F: FieldVisitor>;
+
+    fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F>;
+
+    fn fields(&self) -> Self::Fields<GepFieldVisitor> {
+        self.visit_fields(&mut GepFieldVisitor { gep_index_counter: 0 })
+    }
+
+    fn get_struct_type<'ctx>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &'ctx Context,
+    ) -> StructType<'ctx> {
+        let mut visitor = TypeFieldVisitor { tyctx, ctx, field_types: Vec::new() };
+        self.visit_fields(&mut visitor);
+
+        ctx.struct_type(&visitor.field_types, false)
+    }
+}
+
+#[derive(Debug, Clone, Copy, Default)]
+pub struct StructModel<S: StructKind>(pub S);
+pub type Struct<'ctx, S> = Instance<'ctx, StructModel<S>>;
+
+impl<S: StructKind> CheckType for StructModel<S> {
+    fn check_type_impl<'ctx>(
+        &self,
+        tyctx: TypeContext<'ctx>,
+        ctx: &'ctx Context,
+        ty: BasicTypeEnum<'ctx>,
+    ) -> 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 field_types = ty.get_field_types();
+
+        let check_types = {
+            let mut builder = CheckTypeFieldVisitor { tyctx, ctx, check_types: Vec::new() };
+            self.0.visit_fields(&mut builder);
+            builder.check_types
+        };
+
+        if check_types.len() != field_types.len() {
+            return Err(ModelError(format!(
+                "Expecting StructType to have {} field(s), but got {} field(s)",
+                check_types.len(),
+                field_types.len()
+            )));
+        }
+
+        for (field_i, (entry, field_type)) in izip!(check_types, field_types).enumerate() {
+            let field_at = field_i + 1;
+
+            entry.check_type.check_type_impl(tyctx, ctx, field_type).map_err(|err| {
+                err.under_context(format!("struct field #{field_at} '{}'", entry.name).as_str())
+            })?;
+        }
+
+        Ok(())
+    }
+}
+
+impl<S: StructKind> Model for StructModel<S> {
+    type Value<'ctx> = StructValue<'ctx>;
+    type Type<'ctx> = StructType<'ctx>;
+
+    fn get_type<'ctx>(&self, tyctx: TypeContext<'ctx>, ctx: &'ctx Context) -> Self::Type<'ctx> {
+        self.0.get_struct_type(tyctx, ctx)
+    }
+}
+
+impl<'ctx, S: StructKind> Ptr<'ctx, StructModel<S>> {
+    pub fn gep<M, GetField>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        get_field: GetField,
+    ) -> Ptr<'ctx, M>
+    where
+        M: Model,
+        GetField: FnOnce(S::Fields<GepFieldVisitor>) -> GepField<M>,
+    {
+        let field = get_field(self.model.0 .0.fields());
+        let llvm_i32 = ctx.ctx.i32_type(); // must be i32, if its i64 then rust segfaults
+
+        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()
+        };
+
+        let ptr_model = PtrModel(field.model);
+        ptr_model.believe_value(ptr)
+    }
+}

nac3core/src/codegen/model/util.rs

@@ -0,0 +1,23 @@
+use inkwell::{types::BasicType, values::IntValue};
+
+use crate::codegen::{llvm_intrinsics::call_memcpy_generic, CodeGenContext};
+
+use super::*;
+
+pub fn gen_model_memcpy<'ctx, M: Model>(
+    tyctx: TypeContext<'ctx>,
+    ctx: &CodeGenContext<'ctx, '_>,
+    dst: Ptr<'ctx, M>,
+    src: Ptr<'ctx, M>,
+    num_elements: IntValue<'ctx>,
+    volatile: bool,
+) {
+    let bool_model = IntModel(Bool);
+
+    let itemsize = M::default().get_type(tyctx, ctx.ctx).size_of().unwrap();
+    let totalsize =
+        ctx.builder.build_int_mul(itemsize, num_elements, "model_memcpy_totalsize").unwrap();
+    let is_volatile = bool_model.constant(tyctx, ctx.ctx, u64::from(volatile));
+
+    call_memcpy_generic(ctx, dst.value, src.value, totalsize, is_volatile.value);
+}

nac3core/src/codegen/numpy.rs

@@ -1,28 +1,20 @@
-use inkwell::{
-    types::{AnyTypeEnum, BasicType, BasicTypeEnum, PointerType},
-    values::{BasicValue, BasicValueEnum, IntValue, PointerValue},
-    AddressSpace, IntPredicate, OptimizationLevel,
-};
-
-use nac3parser::ast::{Operator, StrRef};
-
-use super::{
-    classes::{
-        ArrayLikeIndexer, ArrayLikeValue, ListType, ListValue, NDArrayType, NDArrayValue,
-        ProxyType, ProxyValue, TypedArrayLikeAccessor, TypedArrayLikeAdapter,
-        TypedArrayLikeMutator, UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
-    },
-    expr::gen_binop_expr_with_values,
-    irrt::{
-        calculate_len_for_slice_range, call_ndarray_calc_broadcast,
-        call_ndarray_calc_broadcast_index, call_ndarray_calc_nd_indices, call_ndarray_calc_size,
-    },
-    llvm_intrinsics::{self, call_memcpy_generic},
-    macros::codegen_unreachable,
-    stmt::{gen_for_callback_incrementing, gen_for_range_callback, gen_if_else_expr_callback},
-    CodeGenContext, CodeGenerator,
-};
 use crate::{
+    codegen::{
+        classes::{
+            ArrayLikeIndexer, ArrayLikeValue, ListType, ListValue, NDArrayType, NDArrayValue,
+            ProxyType, ProxyValue, TypedArrayLikeAccessor, TypedArrayLikeAdapter,
+            TypedArrayLikeMutator, UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
+        },
+        expr::gen_binop_expr_with_values,
+        irrt::{
+            calculate_len_for_slice_range, call_ndarray_calc_broadcast,
+            call_ndarray_calc_broadcast_index, call_ndarray_calc_nd_indices,
+            call_ndarray_calc_size,
+        },
+        llvm_intrinsics::{self, call_memcpy_generic},
+        stmt::{gen_for_callback_incrementing, gen_for_range_callback, gen_if_else_expr_callback},
+        CodeGenContext, CodeGenerator,
+    },
     symbol_resolver::ValueEnum,
     toplevel::{
         helper::PrimDef,
@@ -34,6 +26,13 @@ use crate::{
         typedef::{FunSignature, Type, TypeEnum},
     },
 };
+use inkwell::types::{AnyTypeEnum, BasicTypeEnum, PointerType};
+use inkwell::{
+    types::BasicType,
+    values::{BasicValueEnum, IntValue, PointerValue},
+    AddressSpace, IntPredicate, OptimizationLevel,
+};
+use nac3parser::ast::{Operator, StrRef};
 
 /// Creates an uninitialized `NDArray` instance.
 fn create_ndarray_uninitialized<'ctx, G: CodeGenerator + ?Sized>(
@@ -160,7 +159,7 @@ where
 ///
 /// * `elem_ty` - The element type of the `NDArray`.
 /// * `shape` - The shape of the `NDArray`, represented am array of [`IntValue`]s.
-pub fn create_ndarray_const_shape<'ctx, G: CodeGenerator + ?Sized>(
+fn create_ndarray_const_shape<'ctx, G: CodeGenerator + ?Sized>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
     elem_ty: Type,
@@ -255,9 +254,9 @@ fn ndarray_zero_value<'ctx, G: CodeGenerator + ?Sized>(
     } else if ctx.unifier.unioned(elem_ty, ctx.primitives.bool) {
         ctx.ctx.bool_type().const_zero().into()
     } else if ctx.unifier.unioned(elem_ty, ctx.primitives.str) {
-        ctx.gen_string(generator, "").into()
+        ctx.gen_string(generator, "").value.into()
     } else {
-        codegen_unreachable!(ctx)
+        unreachable!()
     }
 }
 
@@ -283,9 +282,9 @@ fn ndarray_one_value<'ctx, G: CodeGenerator + ?Sized>(
     } else if ctx.unifier.unioned(elem_ty, ctx.primitives.bool) {
         ctx.ctx.bool_type().const_int(1, false).into()
     } else if ctx.unifier.unioned(elem_ty, ctx.primitives.str) {
-        ctx.gen_string(generator, "1").into()
+        ctx.gen_string(generator, "1").value.into()
     } else {
-        codegen_unreachable!(ctx)
+        unreachable!()
     }
 }
 
@@ -353,7 +352,7 @@ fn call_ndarray_empty_impl<'ctx, G: CodeGenerator + ?Sized>(
 
             create_ndarray_const_shape(generator, ctx, elem_ty, &[shape_int])
         }
-        _ => codegen_unreachable!(ctx),
+        _ => unreachable!(),
     }
 }
 
@@ -624,7 +623,7 @@ fn call_ndarray_full_impl<'ctx, G: CodeGenerator + ?Sized>(
         } else if fill_value.is_int_value() || fill_value.is_float_value() {
             fill_value
         } else {
-            codegen_unreachable!(ctx)
+            unreachable!()
         };
 
         Ok(value)
@@ -939,7 +938,7 @@ fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
                         .build_store(
                             lst,
                             ctx.builder
-                                .build_bit_cast(object.as_base_value(), llvm_plist_i8, "")
+                                .build_bitcast(object.as_base_value(), llvm_plist_i8, "")
                                 .unwrap(),
                         )
                         .unwrap();
@@ -961,7 +960,7 @@ fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
                                 .builder
                                 .build_load(lst, "")
                                 .map(BasicValueEnum::into_pointer_value)
-                                .map(|v| ctx.builder.build_bit_cast(v, plist_plist_i8, "").unwrap())
+                                .map(|v| ctx.builder.build_bitcast(v, plist_plist_i8, "").unwrap())
                                 .map(BasicValueEnum::into_pointer_value)
                                 .unwrap();
                             let this_dim = ListValue::from_ptr_val(this_dim, llvm_usize, None);
@@ -980,9 +979,7 @@ fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
                             ctx.builder
                                 .build_store(
                                     lst,
-                                    ctx.builder
+                                    ctx.builder.build_bitcast(next_dim, llvm_plist_i8, "").unwrap(),
-                                        .build_bit_cast(next_dim, llvm_plist_i8, "")
-                                        .unwrap(),
                                 )
                                 .unwrap();
 
@@ -1071,15 +1068,15 @@ fn call_ndarray_eye_impl<'ctx, G: CodeGenerator + ?Sized>(
 /// Copies a slice of an [`NDArrayValue`] to another.
 ///
 /// - `dst_arr`: The [`NDArrayValue`] instance of the destination array. The `ndims` and `dim_sz`
-///   fields should be populated before calling this function.
+/// fields should be populated before calling this function.
 /// - `dst_slice_ptr`: The [`PointerValue`] to the first element of the currently processing
-///   dimensional slice in the destination array.
+/// dimensional slice in the destination array.
 /// - `src_arr`: The [`NDArrayValue`] instance of the source array.
 /// - `src_slice_ptr`: The [`PointerValue`] to the first element of the currently processing
-///   dimensional slice in the source array.
+/// dimensional slice in the source array.
 /// - `dim`: The index of the currently processing dimension.
 /// - `slices`: List of all slices, with the first element corresponding to the slice applicable to
-///   this dimension. The `start`/`stop` values of each slice must be non-negative indices.
+/// this dimension. The `start`/`stop` values of each slice must be non-negative indices.
 fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
@@ -1184,7 +1181,7 @@ fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
 ///
 /// * `elem_ty` - The element type of the `NDArray`.
 /// - `slices`: List of all slices, with the first element corresponding to the slice applicable to
-///   this dimension. The `start`/`stop` values of each slice must be positive indices.
+/// this dimension. The `start`/`stop` values of each slice must be positive indices.
 pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
@@ -1349,7 +1346,7 @@ where
 ///
 /// * `elem_ty` - The element type of the `NDArray`.
 /// * `res` - The `ndarray` instance to write results into, or [`None`] if the result should be
-///   written to a new `ndarray`.
+/// written to a new `ndarray`.
 /// * `value_fn` - Function mapping the two input elements into the result.
 ///
 /// # Panic
@@ -1436,7 +1433,7 @@ where
 ///
 /// * `elem_ty` - The element type of the `NDArray`.
 /// * `res` - The `ndarray` instance to write results into, or [`None`] if the result should be
-///   written to a new `ndarray`.
+/// written to a new `ndarray`.
 pub fn ndarray_matmul_2d<'ctx, G: CodeGenerator>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
@@ -2020,7 +2017,7 @@ pub fn gen_ndarray_fill<'ctx>(
             } else if value_arg.is_int_value() || value_arg.is_float_value() {
                 value_arg
             } else {
-                codegen_unreachable!(ctx)
+                unreachable!()
             };
 
             Ok(value)
@@ -2029,497 +2026,3 @@ pub fn gen_ndarray_fill<'ctx>(
 
     Ok(())
 }
-
-/// Generates LLVM IR for `ndarray.transpose`.
-pub fn ndarray_transpose<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    x1: (Type, BasicValueEnum<'ctx>),
-) -> Result<BasicValueEnum<'ctx>, String> {
-    const FN_NAME: &str = "ndarray_transpose";
-    let (x1_ty, x1) = x1;
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    if let BasicValueEnum::PointerValue(n1) = x1 {
-        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
-        let n_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
-
-        // Dimensions are reversed in the transposed array
-        let out = create_ndarray_dyn_shape(
-            generator,
-            ctx,
-            elem_ty,
-            &n1,
-            |_, ctx, n| Ok(n.load_ndims(ctx)),
-            |generator, ctx, n, idx| {
-                let new_idx = ctx.builder.build_int_sub(n.load_ndims(ctx), idx, "").unwrap();
-                let new_idx = ctx
-                    .builder
-                    .build_int_sub(new_idx, new_idx.get_type().const_int(1, false), "")
-                    .unwrap();
-                unsafe { Ok(n.dim_sizes().get_typed_unchecked(ctx, generator, &new_idx, None)) }
-            },
-        )
-        .unwrap();
-
-        gen_for_callback_incrementing(
-            generator,
-            ctx,
-            None,
-            llvm_usize.const_zero(),
-            (n_sz, false),
-            |generator, ctx, _, idx| {
-                let elem = unsafe { n1.data().get_unchecked(ctx, generator, &idx, None) };
-
-                let new_idx = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
-                let rem_idx = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
-                ctx.builder.build_store(new_idx, llvm_usize.const_zero()).unwrap();
-                ctx.builder.build_store(rem_idx, idx).unwrap();
-
-                // Incrementally calculate the new index in the transposed array
-                // For each index, we first decompose it into the n-dims and use those to reconstruct the new index
-                // The formula used for indexing is:
-                // idx = dim_n * ( ... (dim2 * (dim0 * dim1) + dim1) + dim2 ... ) + dim_n
-                gen_for_callback_incrementing(
-                    generator,
-                    ctx,
-                    None,
-                    llvm_usize.const_zero(),
-                    (n1.load_ndims(ctx), false),
-                    |generator, ctx, _, ndim| {
-                        let ndim_rev =
-                            ctx.builder.build_int_sub(n1.load_ndims(ctx), ndim, "").unwrap();
-                        let ndim_rev = ctx
-                            .builder
-                            .build_int_sub(ndim_rev, llvm_usize.const_int(1, false), "")
-                            .unwrap();
-                        let dim = unsafe {
-                            n1.dim_sizes().get_typed_unchecked(ctx, generator, &ndim_rev, None)
-                        };
-
-                        let rem_idx_val =
-                            ctx.builder.build_load(rem_idx, "").unwrap().into_int_value();
-                        let new_idx_val =
-                            ctx.builder.build_load(new_idx, "").unwrap().into_int_value();
-
-                        let add_component =
-                            ctx.builder.build_int_unsigned_rem(rem_idx_val, dim, "").unwrap();
-                        let rem_idx_val =
-                            ctx.builder.build_int_unsigned_div(rem_idx_val, dim, "").unwrap();
-
-                        let new_idx_val = ctx.builder.build_int_mul(new_idx_val, dim, "").unwrap();
-                        let new_idx_val =
-                            ctx.builder.build_int_add(new_idx_val, add_component, "").unwrap();
-
-                        ctx.builder.build_store(rem_idx, rem_idx_val).unwrap();
-                        ctx.builder.build_store(new_idx, new_idx_val).unwrap();
-
-                        Ok(())
-                    },
-                    llvm_usize.const_int(1, false),
-                )?;
-
-                let new_idx_val = ctx.builder.build_load(new_idx, "").unwrap().into_int_value();
-                unsafe { out.data().set_unchecked(ctx, generator, &new_idx_val, elem) };
-                Ok(())
-            },
-            llvm_usize.const_int(1, false),
-        )?;
-
-        Ok(out.as_base_value().into())
-    } else {
-        codegen_unreachable!(
-            ctx,
-            "{FN_NAME}() not supported for '{}'",
-            format!("'{}'", ctx.unifier.stringify(x1_ty))
-        )
-    }
-}
-
-/// LLVM-typed implementation for generating the implementation for `ndarray.reshape`.
-///
-/// * `x1` - `NDArray` to reshape.
-/// * `shape` - The `shape` parameter used to construct the new `NDArray`.
-///   Just like numpy, the `shape` argument can be:
-///   1. A list of `int32`;   e.g., `np.reshape(arr, [600, -1, 3])`
-///   2. A tuple of `int32`;  e.g., `np.reshape(arr, (-1, 800, 3))`
-///   3. A scalar `int32`;     e.g., `np.reshape(arr, 3)`
-///
-/// Note that unlike other generating functions, one of the dimensions in the shape can be negative.
-pub fn ndarray_reshape<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    x1: (Type, BasicValueEnum<'ctx>),
-    shape: (Type, BasicValueEnum<'ctx>),
-) -> Result<BasicValueEnum<'ctx>, String> {
-    const FN_NAME: &str = "ndarray_reshape";
-    let (x1_ty, x1) = x1;
-    let (_, shape) = shape;
-
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    if let BasicValueEnum::PointerValue(n1) = x1 {
-        let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
-        let n_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
-
-        let acc = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
-        let num_neg = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
-        ctx.builder.build_store(acc, llvm_usize.const_int(1, false)).unwrap();
-        ctx.builder.build_store(num_neg, llvm_usize.const_zero()).unwrap();
-
-        let out = match shape {
-            BasicValueEnum::PointerValue(shape_list_ptr)
-                if ListValue::is_instance(shape_list_ptr, llvm_usize).is_ok() =>
-            {
-                // 1. A list of ints; e.g., `np.reshape(arr, [int64(600), int64(800, -1])`
-
-                let shape_list = ListValue::from_ptr_val(shape_list_ptr, llvm_usize, None);
-                // Check for -1 in dimensions
-                gen_for_callback_incrementing(
-                    generator,
-                    ctx,
-                    None,
-                    llvm_usize.const_zero(),
-                    (shape_list.load_size(ctx, None), false),
-                    |generator, ctx, _, idx| {
-                        let ele =
-                            shape_list.data().get(ctx, generator, &idx, None).into_int_value();
-                        let ele = ctx.builder.build_int_s_extend(ele, llvm_usize, "").unwrap();
-
-                        gen_if_else_expr_callback(
-                            generator,
-                            ctx,
-                            |_, ctx| {
-                                Ok(ctx
-                                    .builder
-                                    .build_int_compare(
-                                        IntPredicate::SLT,
-                                        ele,
-                                        llvm_usize.const_zero(),
-                                        "",
-                                    )
-                                    .unwrap())
-                            },
-                            |_, ctx| -> Result<Option<IntValue>, String> {
-                                let num_neg_value =
-                                    ctx.builder.build_load(num_neg, "").unwrap().into_int_value();
-                                let num_neg_value = ctx
-                                    .builder
-                                    .build_int_add(
-                                        num_neg_value,
-                                        llvm_usize.const_int(1, false),
-                                        "",
-                                    )
-                                    .unwrap();
-                                ctx.builder.build_store(num_neg, num_neg_value).unwrap();
-                                Ok(None)
-                            },
-                            |_, ctx| {
-                                let acc_value =
-                                    ctx.builder.build_load(acc, "").unwrap().into_int_value();
-                                let acc_value =
-                                    ctx.builder.build_int_mul(acc_value, ele, "").unwrap();
-                                ctx.builder.build_store(acc, acc_value).unwrap();
-                                Ok(None)
-                            },
-                        )?;
-                        Ok(())
-                    },
-                    llvm_usize.const_int(1, false),
-                )?;
-                let acc_val = ctx.builder.build_load(acc, "").unwrap().into_int_value();
-                let rem = ctx.builder.build_int_unsigned_div(n_sz, acc_val, "").unwrap();
-                // Generate the output shape by filling -1 with `rem`
-                create_ndarray_dyn_shape(
-                    generator,
-                    ctx,
-                    elem_ty,
-                    &shape_list,
-                    |_, ctx, _| Ok(shape_list.load_size(ctx, None)),
-                    |generator, ctx, shape_list, idx| {
-                        let dim =
-                            shape_list.data().get(ctx, generator, &idx, None).into_int_value();
-                        let dim = ctx.builder.build_int_s_extend(dim, llvm_usize, "").unwrap();
-
-                        Ok(gen_if_else_expr_callback(
-                            generator,
-                            ctx,
-                            |_, ctx| {
-                                Ok(ctx
-                                    .builder
-                                    .build_int_compare(
-                                        IntPredicate::SLT,
-                                        dim,
-                                        llvm_usize.const_zero(),
-                                        "",
-                                    )
-                                    .unwrap())
-                            },
-                            |_, _| Ok(Some(rem)),
-                            |_, _| Ok(Some(dim)),
-                        )?
-                        .unwrap()
-                        .into_int_value())
-                    },
-                )
-            }
-            BasicValueEnum::StructValue(shape_tuple) => {
-                // 2. A tuple of `int32`;  e.g., `np.reshape(arr, (-1, 800, 3))`
-
-                let ndims = shape_tuple.get_type().count_fields();
-                // Check for -1 in dims
-                for dim_i in 0..ndims {
-                    let dim = ctx
-                        .builder
-                        .build_extract_value(shape_tuple, dim_i, "")
-                        .unwrap()
-                        .into_int_value();
-                    let dim = ctx.builder.build_int_s_extend(dim, llvm_usize, "").unwrap();
-
-                    gen_if_else_expr_callback(
-                        generator,
-                        ctx,
-                        |_, ctx| {
-                            Ok(ctx
-                                .builder
-                                .build_int_compare(
-                                    IntPredicate::SLT,
-                                    dim,
-                                    llvm_usize.const_zero(),
-                                    "",
-                                )
-                                .unwrap())
-                        },
-                        |_, ctx| -> Result<Option<IntValue>, String> {
-                            let num_negs =
-                                ctx.builder.build_load(num_neg, "").unwrap().into_int_value();
-                            let num_negs = ctx
-                                .builder
-                                .build_int_add(num_negs, llvm_usize.const_int(1, false), "")
-                                .unwrap();
-                            ctx.builder.build_store(num_neg, num_negs).unwrap();
-                            Ok(None)
-                        },
-                        |_, ctx| {
-                            let acc_val = ctx.builder.build_load(acc, "").unwrap().into_int_value();
-                            let acc_val = ctx.builder.build_int_mul(acc_val, dim, "").unwrap();
-                            ctx.builder.build_store(acc, acc_val).unwrap();
-                            Ok(None)
-                        },
-                    )?;
-                }
-
-                let acc_val = ctx.builder.build_load(acc, "").unwrap().into_int_value();
-                let rem = ctx.builder.build_int_unsigned_div(n_sz, acc_val, "").unwrap();
-                let mut shape = Vec::with_capacity(ndims as usize);
-
-                // Reconstruct shape filling negatives with rem
-                for dim_i in 0..ndims {
-                    let dim = ctx
-                        .builder
-                        .build_extract_value(shape_tuple, dim_i, "")
-                        .unwrap()
-                        .into_int_value();
-                    let dim = ctx.builder.build_int_s_extend(dim, llvm_usize, "").unwrap();
-
-                    let dim = gen_if_else_expr_callback(
-                        generator,
-                        ctx,
-                        |_, ctx| {
-                            Ok(ctx
-                                .builder
-                                .build_int_compare(
-                                    IntPredicate::SLT,
-                                    dim,
-                                    llvm_usize.const_zero(),
-                                    "",
-                                )
-                                .unwrap())
-                        },
-                        |_, _| Ok(Some(rem)),
-                        |_, _| Ok(Some(dim)),
-                    )?
-                    .unwrap()
-                    .into_int_value();
-                    shape.push(dim);
-                }
-                create_ndarray_const_shape(generator, ctx, elem_ty, shape.as_slice())
-            }
-            BasicValueEnum::IntValue(shape_int) => {
-                // 3. A scalar `int32`;     e.g., `np.reshape(arr, 3)`
-                let shape_int = gen_if_else_expr_callback(
-                    generator,
-                    ctx,
-                    |_, ctx| {
-                        Ok(ctx
-                            .builder
-                            .build_int_compare(
-                                IntPredicate::SLT,
-                                shape_int,
-                                llvm_usize.const_zero(),
-                                "",
-                            )
-                            .unwrap())
-                    },
-                    |_, _| Ok(Some(n_sz)),
-                    |_, ctx| {
-                        Ok(Some(ctx.builder.build_int_s_extend(shape_int, llvm_usize, "").unwrap()))
-                    },
-                )?
-                .unwrap()
-                .into_int_value();
-                create_ndarray_const_shape(generator, ctx, elem_ty, &[shape_int])
-            }
-            _ => codegen_unreachable!(ctx),
-        }
-        .unwrap();
-
-        // Only allow one dimension to be negative
-        let num_negs = ctx.builder.build_load(num_neg, "").unwrap().into_int_value();
-        ctx.make_assert(
-            generator,
-            ctx.builder
-                .build_int_compare(IntPredicate::ULT, num_negs, llvm_usize.const_int(2, false), "")
-                .unwrap(),
-            "0:ValueError",
-            "can only specify one unknown dimension",
-            [None, None, None],
-            ctx.current_loc,
-        );
-
-        // The new shape must be compatible with the old shape
-        let out_sz = call_ndarray_calc_size(generator, ctx, &out.dim_sizes(), (None, None));
-        ctx.make_assert(
-            generator,
-            ctx.builder.build_int_compare(IntPredicate::EQ, out_sz, n_sz, "").unwrap(),
-            "0:ValueError",
-            "cannot reshape array of size {0} into provided shape of size {1}",
-            [Some(n_sz), Some(out_sz), None],
-            ctx.current_loc,
-        );
-
-        gen_for_callback_incrementing(
-            generator,
-            ctx,
-            None,
-            llvm_usize.const_zero(),
-            (n_sz, false),
-            |generator, ctx, _, idx| {
-                let elem = unsafe { n1.data().get_unchecked(ctx, generator, &idx, None) };
-                unsafe { out.data().set_unchecked(ctx, generator, &idx, elem) };
-                Ok(())
-            },
-            llvm_usize.const_int(1, false),
-        )?;
-
-        Ok(out.as_base_value().into())
-    } else {
-        codegen_unreachable!(
-            ctx,
-            "{FN_NAME}() not supported for '{}'",
-            format!("'{}'", ctx.unifier.stringify(x1_ty))
-        )
-    }
-}
-
-/// Generates LLVM IR for `ndarray.dot`.
-/// Calculate inner product of two vectors or literals
-/// For matrix multiplication use `np_matmul`
-///
-/// The input `NDArray` are flattened and treated as 1D
-/// The operation is equivalent to `np.dot(arr1.ravel(), arr2.ravel())`
-pub fn ndarray_dot<'ctx, G: CodeGenerator + ?Sized>(
-    generator: &mut G,
-    ctx: &mut CodeGenContext<'ctx, '_>,
-    x1: (Type, BasicValueEnum<'ctx>),
-    x2: (Type, BasicValueEnum<'ctx>),
-) -> Result<BasicValueEnum<'ctx>, String> {
-    const FN_NAME: &str = "ndarray_dot";
-    let (x1_ty, x1) = x1;
-    let (_, x2) = x2;
-
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    match (x1, x2) {
-        (BasicValueEnum::PointerValue(n1), BasicValueEnum::PointerValue(n2)) => {
-            let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
-            let n2 = NDArrayValue::from_ptr_val(n2, llvm_usize, None);
-
-            let n1_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
-            let n2_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
-
-            ctx.make_assert(
-                generator,
-                ctx.builder.build_int_compare(IntPredicate::EQ, n1_sz, n2_sz, "").unwrap(),
-                "0:ValueError",
-                "shapes ({0}), ({1}) not aligned",
-                [Some(n1_sz), Some(n2_sz), None],
-                ctx.current_loc,
-            );
-
-            let identity =
-                unsafe { n1.data().get_unchecked(ctx, generator, &llvm_usize.const_zero(), None) };
-            let acc = ctx.builder.build_alloca(identity.get_type(), "").unwrap();
-            ctx.builder.build_store(acc, identity.get_type().const_zero()).unwrap();
-
-            gen_for_callback_incrementing(
-                generator,
-                ctx,
-                None,
-                llvm_usize.const_zero(),
-                (n1_sz, false),
-                |generator, ctx, _, idx| {
-                    let elem1 = unsafe { n1.data().get_unchecked(ctx, generator, &idx, None) };
-                    let elem2 = unsafe { n2.data().get_unchecked(ctx, generator, &idx, None) };
-
-                    let product = match elem1 {
-                        BasicValueEnum::IntValue(e1) => ctx
-                            .builder
-                            .build_int_mul(e1, elem2.into_int_value(), "")
-                            .unwrap()
-                            .as_basic_value_enum(),
-                        BasicValueEnum::FloatValue(e1) => ctx
-                            .builder
-                            .build_float_mul(e1, elem2.into_float_value(), "")
-                            .unwrap()
-                            .as_basic_value_enum(),
-                        _ => codegen_unreachable!(ctx),
-                    };
-                    let acc_val = ctx.builder.build_load(acc, "").unwrap();
-                    let acc_val = match acc_val {
-                        BasicValueEnum::IntValue(e1) => ctx
-                            .builder
-                            .build_int_add(e1, product.into_int_value(), "")
-                            .unwrap()
-                            .as_basic_value_enum(),
-                        BasicValueEnum::FloatValue(e1) => ctx
-                            .builder
-                            .build_float_add(e1, product.into_float_value(), "")
-                            .unwrap()
-                            .as_basic_value_enum(),
-                        _ => codegen_unreachable!(ctx),
-                    };
-                    ctx.builder.build_store(acc, acc_val).unwrap();
-
-                    Ok(())
-                },
-                llvm_usize.const_int(1, false),
-            )?;
-            let acc_val = ctx.builder.build_load(acc, "").unwrap();
-            Ok(acc_val)
-        }
-        (BasicValueEnum::IntValue(e1), BasicValueEnum::IntValue(e2)) => {
-            Ok(ctx.builder.build_int_mul(e1, e2, "").unwrap().as_basic_value_enum())
-        }
-        (BasicValueEnum::FloatValue(e1), BasicValueEnum::FloatValue(e2)) => {
-            Ok(ctx.builder.build_float_mul(e1, e2, "").unwrap().as_basic_value_enum())
-        }
-        _ => codegen_unreachable!(
-            ctx,
-            "{FN_NAME}() not supported for '{}'",
-            format!("'{}'", ctx.unifier.stringify(x1_ty))
-        ),
-    }
-}

nac3core/src/codegen/numpy_new/broadcast.rs

@@ -0,0 +1,113 @@
+use itertools::Itertools;
+
+use crate::{
+    codegen::{
+        irrt::ndarray::broadcast::{
+            call_nac3_ndarray_broadcast_shapes, call_nac3_ndarray_broadcast_to, ShapeEntry,
+        },
+        model::*,
+        numpy_new::util::{create_ndims, extract_ndims},
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::Type,
+};
+
+use super::object::NDArrayObject;
+
+#[derive(Debug, Clone)]
+pub struct BroadcastAllResult<'ctx> {
+    /// The statically known `ndims` of the broadcast result.
+    pub ndims: u64,
+    /// The broadcasting shape.
+    pub shape: Ptr<'ctx, IntModel<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>>,
+}
+
+// TODO: DOCUMENT: Behaves like `np.broadcast()`, except returns results differently.
+pub fn broadcast_all_ndarrays<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndarrays: Vec<NDArrayObject<'ctx>>,
+) -> BroadcastAllResult<'ctx> {
+    assert!(!ndarrays.is_empty());
+
+    let tyctx = generator.type_context(ctx.ctx);
+    let sizet_model = IntModel(SizeT);
+    let shape_model = StructModel(ShapeEntry);
+
+    // We can deduce the final ndims statically and immediately.
+    // It should be `max([ ndarray.ndims for ndarray in ndarrays ])`.
+    let broadcast_ndims =
+        ndarrays.iter().map(|ndarray| extract_ndims(&ctx.unifier, ndarray.ndims)).max().unwrap();
+    let broadcast_ndims_ty = create_ndims(&mut ctx.unifier, broadcast_ndims);
+
+    // NOTE: Now prepare before calling `call_nac3_ndarray_broadcast_shapes`
+
+    // Prepare input shape entries
+    let num_shape_entries =
+        sizet_model.constant(tyctx, ctx.ctx, u64::try_from(ndarrays.len()).unwrap());
+    let shape_entries =
+        shape_model.array_alloca(tyctx, ctx, num_shape_entries.value, "shape_entries");
+    for (i, ndarray) in ndarrays.iter().enumerate() {
+        let i = sizet_model.constant(tyctx, ctx.ctx, i as u64).value;
+
+        let this_shape = ndarray.instance.gep(ctx, |f| f.shape).load(tyctx, ctx, "this_shape");
+        let this_ndims = ndarray.instance.gep(ctx, |f| f.ndims).load(tyctx, ctx, "this_ndims");
+
+        let shape_entry = shape_entries.offset(tyctx, ctx, i, "shape_entry");
+        shape_entry.gep(ctx, |f| f.shape).store(ctx, this_shape);
+        shape_entry.gep(ctx, |f| f.ndims).store(ctx, this_ndims);
+    }
+
+    // Prepare destination
+    let dst_ndims = sizet_model.constant(tyctx, ctx.ctx, broadcast_ndims);
+    let dst_shape = sizet_model.array_alloca(tyctx, ctx, dst_ndims.value, "dst_shape");
+
+    call_nac3_ndarray_broadcast_shapes(
+        generator,
+        ctx,
+        num_shape_entries,
+        shape_entries,
+        dst_ndims,
+        dst_shape,
+    );
+
+    // Now that we know about the broadcasting shape, broadcast all the inputs.
+
+    // Broadcast all the inputs to shape `dst_shape`
+    let broadcasted_ndarrays = ndarrays
+        .into_iter()
+        .map(|ndarray| ndarray.broadcast_to(generator, ctx, broadcast_ndims_ty, dst_shape))
+        .collect_vec();
+
+    BroadcastAllResult { ndims: broadcast_ndims, shape: dst_shape, ndarrays: broadcasted_ndarrays }
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    /// Broadcast an ndarray to a target shape.
+    #[must_use]
+    pub fn broadcast_to<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        target_ndims_ty: Type,
+        target_shape: Ptr<'ctx, IntModel<SizeT>>,
+    ) -> Self {
+        // Please see comment in IRRT on how the caller should prepare `dst_ndarray`
+        let dst_ndarray = NDArrayObject::alloca(
+            generator,
+            ctx,
+            target_ndims_ty,
+            self.dtype,
+            "broadcast_ndarray_to_dst",
+        );
+        dst_ndarray.copy_shape(generator, ctx, target_shape);
+        call_nac3_ndarray_broadcast_to(generator, ctx, self.instance, dst_ndarray.instance);
+        dst_ndarray
+    }
+}

nac3core/src/codegen/numpy_new/factory.rs

@@ -0,0 +1,217 @@
+use inkwell::{
+    types::BasicType,
+    values::{BasicValue, BasicValueEnum, PointerValue},
+    AddressSpace,
+};
+use nac3parser::ast::StrRef;
+
+use crate::{
+    codegen::{
+        model::*,
+        numpy_new::util::{alloca_ndarray, init_ndarray_data_by_alloca, init_ndarray_shape},
+        structure::ndarray::NpArray,
+        util::shape::make_shape_writer,
+        CodeGenContext, CodeGenerator,
+    },
+    symbol_resolver::ValueEnum,
+    toplevel::DefinitionId,
+    typecheck::typedef::{FunSignature, Type},
+};
+
+use super::util::gen_foreach_ndarray_elements;
+
+/// Helper function to create an ndarray with uninitialized values
+///
+/// * `elem_ty` - The [`Type`] of the ndarray elements
+/// * `shape` - The user input shape argument
+/// * `shape_ty` - The [`Type`] of the shape argument
+/// * `name` - LLVM IR name of the returned ndarray
+fn create_empty_ndarray<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    elem_ty: Type,
+    shape: BasicValueEnum<'ctx>,
+    shape_ty: Type,
+    name: &str,
+) -> Result<Ptr<'ctx, StructModel<NpArray>>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let tyctx = generator.type_context(ctx.ctx);
+    let sizet_model = IntModel(SizeT);
+
+    let shape_writer = make_shape_writer(generator, ctx, shape, shape_ty);
+    let ndims = shape_writer.len;
+
+    let ndarray = alloca_ndarray(generator, ctx, ndims, name);
+    init_ndarray_shape(generator, ctx, ndarray, &shape_writer)?;
+
+    let itemsize = ctx.get_llvm_type(generator, elem_ty).size_of().unwrap();
+    let itemsize = sizet_model.check_value(tyctx, ctx.ctx, itemsize).unwrap();
+    ndarray.gep(ctx, |f| f.itemsize).store(ctx, itemsize);
+
+    // Needs `itemsize` and `shape` initialized
+    init_ndarray_data_by_alloca(generator, ctx, ndarray);
+
+    Ok(ndarray)
+}
+
+/// Helper function to create an ndarray full of a value.
+///
+/// * `elem_ty` - The [`Type`] of the ndarray elements and the fill value
+/// * `shape` - The user input shape argument
+/// * `shape_ty` - The [`Type`] of the shape argument
+/// * `fill_value` - The user specified fill value
+/// * `name` - LLVM IR name of the returned ndarray
+fn create_full_ndarray<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    elem_ty: Type,
+    shape: BasicValueEnum<'ctx>,
+    shape_ty: Type,
+    fill_value: BasicValueEnum<'ctx>,
+    name: &str,
+) -> Result<Ptr<'ctx, StructModel<NpArray>>, String>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let pndarray = create_empty_ndarray(generator, ctx, elem_ty, shape, shape_ty, name)?;
+    gen_foreach_ndarray_elements(
+        generator,
+        ctx,
+        pndarray,
+        |_generator, ctx, _hooks, _i, pelement| {
+            // Cannot use Model here, fill_value's type is not statically known.
+            let pfill_value_ty = fill_value.get_type().ptr_type(AddressSpace::default());
+            let pelement =
+                ctx.builder.build_pointer_cast(pelement.value, pfill_value_ty, "pelement").unwrap();
+            ctx.builder.build_store(pelement, fill_value).unwrap();
+            Ok(())
+        },
+    )?;
+    Ok(pndarray)
+}
+
+/// Generates LLVM IR for `np.empty`.
+pub fn gen_ndarray_empty<'ctx>(
+    context: &mut CodeGenContext<'ctx, '_>,
+    obj: &Option<(Type, ValueEnum<'ctx>)>,
+    fun: (&FunSignature, DefinitionId),
+    args: &[(Option<StrRef>, ValueEnum<'ctx>)],
+    generator: &mut dyn CodeGenerator,
+) -> Result<PointerValue<'ctx>, String> {
+    assert!(obj.is_none());
+    assert_eq!(args.len(), 1);
+
+    // Parse arguments
+    let shape_ty = fun.0.args[0].ty;
+    let shape = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
+
+    // Implementation
+    let ndarray_ptr = create_empty_ndarray(
+        generator,
+        context,
+        context.primitives.float,
+        shape,
+        shape_ty,
+        "ndarray",
+    )?;
+    Ok(ndarray_ptr.value)
+}
+
+/// Generates LLVM IR for `np.zeros`.
+pub fn gen_ndarray_zeros<'ctx>(
+    context: &mut CodeGenContext<'ctx, '_>,
+    obj: &Option<(Type, ValueEnum<'ctx>)>,
+    fun: (&FunSignature, DefinitionId),
+    args: &[(Option<StrRef>, ValueEnum<'ctx>)],
+    generator: &mut dyn CodeGenerator,
+) -> Result<PointerValue<'ctx>, String> {
+    assert!(obj.is_none());
+    assert_eq!(args.len(), 1);
+
+    // Parse arguments
+    let shape_ty = fun.0.args[0].ty;
+    let shape = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
+
+    // Implementation
+    // NOTE: Currently nac3's `np.zeros` is always `float64`.
+    let float64_ty = context.primitives.float;
+    let float64_llvm_type = context.get_llvm_type(generator, float64_ty).into_float_type();
+
+    let ndarray_ptr = create_full_ndarray(
+        generator,
+        context,
+        float64_ty, // `elem_ty` is always `float64`
+        shape,
+        shape_ty,
+        float64_llvm_type.const_zero().as_basic_value_enum(),
+        "ndarray",
+    )?;
+    Ok(ndarray_ptr.value)
+}
+
+/// Generates LLVM IR for `np.ones`.
+pub fn gen_ndarray_ones<'ctx>(
+    context: &mut CodeGenContext<'ctx, '_>,
+    obj: &Option<(Type, ValueEnum<'ctx>)>,
+    fun: (&FunSignature, DefinitionId),
+    args: &[(Option<StrRef>, ValueEnum<'ctx>)],
+    generator: &mut dyn CodeGenerator,
+) -> Result<PointerValue<'ctx>, String> {
+    assert!(obj.is_none());
+    assert_eq!(args.len(), 1);
+
+    // Parse arguments
+    let shape_ty = fun.0.args[0].ty;
+    let shape = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
+
+    // Implementation
+    // NOTE: Currently nac3's `np.ones` is always `float64`.
+    let float64_ty = context.primitives.float;
+    let float64_llvm_type = context.get_llvm_type(generator, float64_ty).into_float_type();
+
+    let ndarray_ptr = create_full_ndarray(
+        generator,
+        context,
+        float64_ty, // `elem_ty` is always `float64`
+        shape,
+        shape_ty,
+        float64_llvm_type.const_float(1.0).as_basic_value_enum(),
+        "ndarray",
+    )?;
+    Ok(ndarray_ptr.value)
+}
+
+/// Generates LLVM IR for `np.full`.
+pub fn gen_ndarray_full<'ctx>(
+    context: &mut CodeGenContext<'ctx, '_>,
+    obj: &Option<(Type, ValueEnum<'ctx>)>,
+    fun: (&FunSignature, DefinitionId),
+    args: &[(Option<StrRef>, ValueEnum<'ctx>)],
+    generator: &mut dyn CodeGenerator,
+) -> Result<PointerValue<'ctx>, String> {
+    assert!(obj.is_none());
+    assert_eq!(args.len(), 2);
+
+    // Parse argument #1 shape
+    let shape_ty = fun.0.args[0].ty;
+    let shape_arg = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
+
+    // Parse argument #2 fill_value
+    let fill_value_ty = fun.0.args[1].ty;
+    let fill_value_arg =
+        args[1].1.clone().to_basic_value_enum(context, generator, fill_value_ty)?;
+
+    // Implementation
+    let ndarray_ptr = create_full_ndarray(
+        generator,
+        context,
+        fill_value_ty,
+        shape_arg,
+        shape_ty,
+        fill_value_arg,
+        "ndarray",
+    )?;
+    Ok(ndarray_ptr.value)
+}

nac3core/src/codegen/numpy_new/indexing.rs

@@ -0,0 +1,76 @@
+use crate::{
+    codegen::{
+        irrt::ndarray::indexing::{call_nac3_ndarray_index, RustNDIndex},
+        model::*,
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::{Type, Unifier},
+};
+
+use super::{
+    object::{NDArrayObject, ScalarObject, ScalarOrNDArray},
+    util::{create_ndims, extract_ndims},
+};
+
+impl<'ctx> NDArrayObject<'ctx> {
+    pub fn deduce_ndims_after_indexing_with(
+        &self,
+        unifier: &mut Unifier,
+        indexes: &[RustNDIndex<'ctx>],
+    ) -> Type {
+        let ndims = extract_ndims(unifier, self.ndims);
+        let new_ndims = RustNDIndex::deduce_ndims_after_indexing(indexes, ndims);
+        create_ndims(unifier, new_ndims)
+    }
+
+    #[must_use]
+    pub fn index_always_ndarray<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        indexes: &[RustNDIndex<'ctx>],
+        name: &str,
+    ) -> Self {
+        let tyctx = generator.type_context(ctx.ctx);
+
+        let dst_ndims = self.deduce_ndims_after_indexing_with(&mut ctx.unifier, indexes);
+        let dst_ndarray = NDArrayObject::alloca(generator, ctx, dst_ndims, self.dtype, name);
+
+        let (num_indexes, indexes) = RustNDIndex::alloca_ndindexes(tyctx, ctx, indexes);
+        call_nac3_ndarray_index(
+            generator,
+            ctx,
+            num_indexes,
+            indexes,
+            self.instance,
+            dst_ndarray.instance,
+        );
+
+        dst_ndarray
+    }
+
+    pub fn index<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        indexes: &[RustNDIndex<'ctx>],
+        name: &str,
+    ) -> ScalarOrNDArray<'ctx> {
+        let tyctx = generator.type_context(ctx.ctx);
+        let sizet_model = IntModel(SizeT);
+
+        let subndarray = self.index_always_ndarray(generator, ctx, indexes, name);
+        if subndarray.is_unsized(&ctx.unifier) {
+            // TODO: This actually never fails, don't use the `checked_` version.
+            let value = subndarray.checked_get_nth_element(
+                generator,
+                ctx,
+                sizet_model.const_0(tyctx, ctx.ctx),
+                name,
+            );
+            ScalarOrNDArray::Scalar(ScalarObject { dtype: self.dtype, value })
+        } else {
+            ScalarOrNDArray::NDArray(subndarray)
+        }
+    }
+}

nac3core/src/codegen/numpy_new/mod.rs

@@ -0,0 +1,6 @@
+pub mod broadcast;
+pub mod factory;
+pub mod indexing;
+pub mod object;
+pub mod util;
+pub mod view;

nac3core/src/codegen/numpy_new/object.rs

@@ -0,0 +1,69 @@
+use inkwell::values::{BasicValue, BasicValueEnum};
+
+use crate::{
+    codegen::{model::*, structure::ndarray::NpArray, CodeGenContext},
+    toplevel::numpy::unpack_ndarray_var_tys,
+    typecheck::typedef::{Type, TypeEnum},
+};
+
+/// An LLVM ndarray instance with its typechecker [`Type`]s.
+#[derive(Debug, Clone, Copy)]
+pub struct NDArrayObject<'ctx> {
+    pub dtype: Type,
+    pub ndims: Type,
+    pub instance: Ptr<'ctx, StructModel<NpArray>>,
+}
+
+/// An LLVM numpy scalar with its [`Type`].
+#[derive(Debug, Clone, Copy)]
+pub struct ScalarObject<'ctx> {
+    pub dtype: Type,
+    pub value: BasicValueEnum<'ctx>,
+}
+
+#[derive(Debug, Clone, Copy)]
+pub enum ScalarOrNDArray<'ctx> {
+    Scalar(ScalarObject<'ctx>),
+    NDArray(NDArrayObject<'ctx>),
+}
+
+impl<'ctx> ScalarOrNDArray<'ctx> {
+    /// 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(),
+        }
+    }
+}
+
+impl<'ctx> From<ScalarOrNDArray<'ctx>> for BasicValueEnum<'ctx> {
+    fn from(input: ScalarOrNDArray<'ctx>) -> BasicValueEnum<'ctx> {
+        input.to_basic_value_enum()
+    }
+}
+
+/// Split an [`BasicValueEnum<'ctx>`] into a [`ScalarOrNDArray`] depending
+/// on its [`Type`].
+pub fn split_scalar_or_ndarray<'ctx>(
+    tyctx: TypeContext<'ctx>,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    input: BasicValueEnum<'ctx>,
+    input_ty: Type,
+) -> ScalarOrNDArray<'ctx> {
+    let pndarray_model = PtrModel(StructModel(NpArray));
+
+    let input_ty_enum = ctx.unifier.get_ty(input_ty);
+    match &*input_ty_enum {
+        TypeEnum::TObj { obj_id, .. }
+            if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
+        {
+            let value = pndarray_model.check_value(tyctx, ctx.ctx, input).unwrap();
+            let (dtype, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, input_ty);
+
+            ScalarOrNDArray::NDArray(NDArrayObject { dtype, ndims, instance: value })
+        }
+        _ => ScalarOrNDArray::Scalar(ScalarObject { dtype: input_ty, value: input }),
+    }
+}

nac3core/src/codegen/numpy_new/util.rs

@@ -0,0 +1,328 @@
+use inkwell::{
+    types::BasicType,
+    values::{BasicValueEnum, PointerValue},
+    AddressSpace,
+};
+use util::gen_model_memcpy;
+
+use crate::{
+    codegen::{
+        irrt::ndarray::basic::{
+            call_nac3_ndarray_copy_data, call_nac3_ndarray_get_nth_pelement,
+            call_nac3_ndarray_is_c_contiguous, call_nac3_ndarray_nbytes,
+            call_nac3_ndarray_set_strides_by_shape, call_nac3_ndarray_size,
+            call_nac3_ndarray_util_assert_shape_no_negative,
+        },
+        model::*,
+        stmt::BreakContinueHooks,
+        structure::ndarray::NpArray,
+        util::{array_writer::ArrayWriter, control::gen_model_for},
+        CodeGenContext, CodeGenerator,
+    },
+    symbol_resolver::SymbolValue,
+    typecheck::typedef::{Type, TypeEnum, Unifier},
+};
+
+use super::object::{NDArrayObject, ScalarOrNDArray};
+
+/// Extract an ndarray's `ndims` [type][`Type`] in `u64`. Panic if not possible.
+#[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)
+}
+
+/// Allocate an ndarray on the stack given its `ndims`.
+///
+/// `shape` and `strides` will be automatically allocated on the stack.
+///
+/// The returned ndarray's content will be:
+/// - `data`: `nullptr`
+/// - `itemsize`: **uninitialized** value
+/// - `ndims`: initialized value, set to the input `ndims`
+/// - `shape`: initialized pointer to an allocated stack with **uninitialized** values
+/// - `strides`: initialized pointer to an allocated stack with **uninitialized** values
+pub fn alloca_ndarray<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    ndims: Int<'ctx, SizeT>,
+    name: &str,
+) -> Ptr<'ctx, StructModel<NpArray>>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let tyctx = generator.type_context(ctx.ctx);
+
+    let sizet_model = IntModel(SizeT);
+    let ndarray_model = StructModel(NpArray);
+    let ndarray_data_model = PtrModel(IntModel(Byte));
+
+    // Setup ndarray
+    let ndarray_ptr = ndarray_model.alloca(tyctx, ctx, name);
+    let shape = sizet_model.array_alloca(tyctx, ctx, ndims.value, "shape");
+    let strides = sizet_model.array_alloca(tyctx, ctx, ndims.value, "strides");
+
+    ndarray_ptr.gep(ctx, |f| f.data).store(ctx, ndarray_data_model.nullptr(tyctx, ctx.ctx));
+    ndarray_ptr.gep(ctx, |f| f.ndims).store(ctx, ndims);
+    ndarray_ptr.gep(ctx, |f| f.shape).store(ctx, shape);
+    ndarray_ptr.gep(ctx, |f| f.strides).store(ctx, strides);
+
+    ndarray_ptr
+}
+
+/// Initialize an ndarray's `shape` and asserts on.
+/// `shape`'s values and prohibit illegal inputs like negative dimensions.
+pub fn init_ndarray_shape<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    pndarray: Ptr<'ctx, StructModel<NpArray>>,
+    shape_writer: &ArrayWriter<'ctx, G, SizeT, IntModel<SizeT>>,
+) -> Result<(), String> {
+    let tyctx = generator.type_context(ctx.ctx);
+    let shape = pndarray.gep(ctx, |f| f.shape).load(tyctx, ctx, "shape");
+    (shape_writer.write)(generator, ctx, shape)?;
+    call_nac3_ndarray_util_assert_shape_no_negative(generator, ctx, shape_writer.len, shape);
+    Ok(())
+}
+
+/// 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 init_ndarray_data_by_alloca<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    pndarray: Ptr<'ctx, StructModel<NpArray>>,
+) {
+    let tyctx = generator.type_context(ctx.ctx);
+    let ndarray_data_model = IntModel(Byte);
+
+    let nbytes = call_nac3_ndarray_nbytes(generator, ctx, pndarray);
+    let data = ndarray_data_model.array_alloca(tyctx, ctx, nbytes.value, "data");
+    pndarray.gep(ctx, |f| f.data).store(ctx, data);
+    call_nac3_ndarray_set_strides_by_shape(generator, ctx, pndarray);
+}
+
+/// Iterate through all elements in an ndarray.
+///
+/// `body` is given the index of an element and an opaque pointer (as an `uint8_t*`, you might want to cast it) to the element.
+///
+/// Short-circuiting is possible with the given [`BreakContinueHooks`].
+pub fn gen_foreach_ndarray_elements<'ctx, G, F>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    pndarray: Ptr<'ctx, StructModel<NpArray>>,
+    body: F,
+) -> Result<(), String>
+where
+    G: CodeGenerator + ?Sized,
+    F: Fn(
+        &mut G,
+        &mut CodeGenContext<'ctx, '_>,
+        BreakContinueHooks<'ctx>,
+        Int<'ctx, SizeT>,
+        Ptr<'ctx, IntModel<Byte>>,
+    ) -> Result<(), String>,
+{
+    // TODO: Make this more efficient - use a special NDArray iterator?
+
+    let tyctx = generator.type_context(ctx.ctx);
+
+    let sizet_model = IntModel(SizeT);
+    let size = call_nac3_ndarray_size(generator, ctx, pndarray);
+
+    gen_model_for(
+        generator,
+        ctx,
+        sizet_model.const_0(tyctx, ctx.ctx),
+        size,
+        sizet_model.const_1(tyctx, ctx.ctx),
+        |generator, ctx, hooks, index| {
+            let pelement = call_nac3_ndarray_get_nth_pelement(generator, ctx, pndarray, index);
+            body(generator, ctx, hooks, index, pelement)
+        },
+    )
+}
+
+impl<'ctx> ScalarOrNDArray<'ctx> {
+    /// Convert `input` to an ndarray - behaves like `np.asarray`.
+    pub fn as_ndarray<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> NDArrayObject<'ctx> {
+        match self {
+            ScalarOrNDArray::NDArray(ndarray) => *ndarray,
+            ScalarOrNDArray::Scalar(scalar) => {
+                let tyctx = generator.type_context(ctx.ctx);
+                let pbyte_model = PtrModel(IntModel(Byte));
+
+                // We have to put the value on the stack to get a data pointer.
+                let data =
+                    ctx.builder.build_alloca(scalar.value.get_type(), "as_ndarray_scalar").unwrap();
+                ctx.builder.build_store(data, scalar.value).unwrap();
+                let data = pbyte_model.transmute(tyctx, ctx, data, "data");
+
+                let ndims_ty = create_ndims(&mut ctx.unifier, 0);
+                let ndarray = NDArrayObject::alloca(
+                    generator,
+                    ctx,
+                    ndims_ty,
+                    scalar.dtype,
+                    "scalar_as_ndarray",
+                );
+                ndarray.instance.gep(ctx, |f| f.data).store(ctx, data);
+
+                // No need to initialize/setup strides or shapes - because `ndims` is 0.
+                // So we only have to set `data`, `itemsize`, and `ndims = 0`.
+
+                ndarray
+            }
+        }
+    }
+}
+
+impl<'ctx> NDArrayObject<'ctx> {
+    pub fn alloca<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndims: Type,
+        dtype: Type,
+        name: &str,
+    ) -> Self {
+        let tyctx = generator.type_context(ctx.ctx);
+        let sizet_model = IntModel(SizeT);
+
+        let ndims_int = sizet_model.constant(tyctx, ctx.ctx, extract_ndims(&ctx.unifier, ndims));
+        let instance = alloca_ndarray(generator, ctx, ndims_int, name);
+
+        // Set itemsize
+        let dtype_ty = ctx.get_llvm_type(generator, dtype);
+        let itemsize = dtype_ty.size_of().unwrap();
+        let itemsize = sizet_model.s_extend_or_bit_cast(tyctx, ctx, itemsize, "itemsize");
+        instance.gep(ctx, |f| f.itemsize).store(ctx, itemsize);
+
+        NDArrayObject { dtype, ndims, instance }
+    }
+
+    pub fn copy_shape<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        src_shape: Ptr<'ctx, IntModel<SizeT>>,
+    ) {
+        let tyctx = generator.type_context(ctx.ctx);
+        let sizet_model = IntModel(SizeT);
+
+        let self_shape = self.instance.gep(ctx, |f| f.shape).load(tyctx, ctx, "self_shape");
+        let ndims_int =
+            sizet_model.constant(tyctx, ctx.ctx, extract_ndims(&ctx.unifier, self.ndims));
+        gen_model_memcpy(tyctx, ctx, self_shape, src_shape, ndims_int.value, false);
+    }
+
+    pub fn copy_shape_from<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        src_ndarray: NDArrayObject<'ctx>,
+    ) {
+        let tyctx = generator.type_context(ctx.ctx);
+        let src_shape = src_ndarray.instance.gep(ctx, |f| f.shape).load(tyctx, ctx, "src_shape");
+        self.copy_shape(generator, ctx, src_shape);
+    }
+
+    pub fn update_strides_by_shape<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) {
+        call_nac3_ndarray_set_strides_by_shape(generator, ctx, self.instance);
+    }
+
+    pub fn checked_get_nth_pelement<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        i: Int<'ctx, SizeT>,
+        name: &str,
+    ) -> PointerValue<'ctx> {
+        let elem_ty = ctx.get_llvm_type(generator, self.dtype);
+
+        let p = call_nac3_ndarray_get_nth_pelement(generator, ctx, self.instance, i);
+        ctx.builder
+            .build_pointer_cast(p.value, elem_ty.ptr_type(AddressSpace::default()), name)
+            .unwrap()
+    }
+
+    pub fn checked_get_nth_element<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        i: Int<'ctx, SizeT>,
+        name: &str,
+    ) -> BasicValueEnum<'ctx> {
+        let pelement = self.checked_get_nth_pelement(generator, ctx, i, "pelement");
+        ctx.builder.build_load(pelement, name).unwrap()
+    }
+
+    #[must_use]
+    pub fn is_unsized(&self, unifier: &Unifier) -> bool {
+        extract_ndims(unifier, self.ndims) == 0
+    }
+
+    pub fn size<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Int<'ctx, SizeT> {
+        call_nac3_ndarray_size(generator, ctx, self.instance)
+    }
+
+    pub fn nbytes<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Int<'ctx, SizeT> {
+        call_nac3_ndarray_nbytes(generator, ctx, self.instance)
+    }
+
+    pub fn is_c_contiguous<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> Int<'ctx, Bool> {
+        call_nac3_ndarray_is_c_contiguous(generator, ctx, self.instance)
+    }
+
+    pub fn alloca_owned_data<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) {
+        init_ndarray_data_by_alloca(generator, ctx, self.instance);
+    }
+
+    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);
+    }
+}

nac3core/src/codegen/numpy_new/view.rs

@@ -0,0 +1,114 @@
+use inkwell::values::PointerValue;
+use nac3parser::ast::StrRef;
+
+use crate::{
+    codegen::{
+        irrt::ndarray::reshape::call_nac3_ndarray_resolve_and_check_new_shape,
+        model::*,
+        numpy_new::{object::split_scalar_or_ndarray, util::extract_ndims},
+        util::shape::make_shape_writer,
+        CodeGenContext, CodeGenerator,
+    },
+    symbol_resolver::ValueEnum,
+    toplevel::{numpy::unpack_ndarray_var_tys, DefinitionId},
+    typecheck::typedef::{FunSignature, Type},
+};
+
+use super::object::NDArrayObject;
+
+impl<'ctx> NDArrayObject<'ctx> {
+    #[must_use]
+    pub fn reshape_or_copy<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        new_ndims: Type,
+        new_shape: Ptr<'ctx, IntModel<SizeT>>,
+    ) -> Self {
+        let tyctx = generator.type_context(ctx.ctx);
+
+        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, new_ndims, self.dtype, "reshaped_ndarray");
+        dst_ndarray.copy_shape(generator, ctx, new_shape);
+        dst_ndarray.update_strides_by_shape(generator, ctx);
+
+        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
+            .instance
+            .gep(ctx, |f| f.data)
+            .store(ctx, dst_ndarray.instance.gep(ctx, |f| f.data).load(tyctx, ctx, "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.alloca_owned_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
+    }
+}
+
+/// Generates LLVM IR for `np.reshape`.
+pub fn gen_ndarray_reshape<'ctx>(
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    obj: &Option<(Type, ValueEnum<'ctx>)>,
+    fun: (&FunSignature, DefinitionId),
+    args: &[(Option<StrRef>, ValueEnum<'ctx>)],
+    generator: &mut dyn CodeGenerator,
+) -> Result<PointerValue<'ctx>, String> {
+    assert!(obj.is_none());
+    assert_eq!(args.len(), 2);
+
+    // Parse argument #1 input
+    let input_ty = fun.0.args[0].ty;
+    let input_arg = args[0].1.clone().to_basic_value_enum(ctx, generator, input_ty)?;
+
+    // Parse argument #2 shape
+    let shape_ty = fun.0.args[1].ty;
+    let shape_arg = args[1].1.clone().to_basic_value_enum(ctx, generator, shape_ty)?;
+
+    // Define models
+    let tyctx = generator.type_context(ctx.ctx);
+    let sizet_model = IntModel(SizeT);
+
+    // Extract reshaped_ndims
+    let (_, reshaped_ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, fun.0.ret);
+    let reshaped_ndims_int = extract_ndims(&ctx.unifier, reshaped_ndims);
+
+    // Process `input`
+    let ndarray =
+        split_scalar_or_ndarray(tyctx, ctx, input_arg, input_ty).as_ndarray(generator, ctx);
+
+    // Process the shape input from user and resolve negative indices
+    let new_shape = make_shape_writer(generator, ctx, shape_arg, shape_ty).alloca_array_and_write(
+        generator,
+        ctx,
+        "new_shape",
+    )?;
+    let size = ndarray.size(generator, ctx);
+    call_nac3_ndarray_resolve_and_check_new_shape(
+        generator,
+        ctx,
+        size,
+        sizet_model.constant(tyctx, ctx.ctx, reshaped_ndims_int),
+        new_shape,
+    );
+
+    // Reshape
+    let reshaped_ndarray = ndarray.reshape_or_copy(generator, ctx, reshaped_ndims, new_shape);
+
+    Ok(reshaped_ndarray.instance.value)
+}

nac3core/src/codegen/structure/cslice.rs

@@ -0,0 +1,43 @@
+use crate::codegen::{model::*, CodeGenContext};
+
+/// Fields of [`CSlice<'ctx>`].
+pub struct CSliceFields<F: FieldVisitor> {
+    /// Pointer to the data.
+    pub base: F::Field<PtrModel<IntModel<Byte>>>,
+    /// Number of bytes of the data.
+    pub len: F::Field<IntModel<SizeT>>,
+}
+
+/// See <https://crates.io/crates/cslice>.
+///
+/// Additionally, see <https://github.com/m-labs/artiq/blob/b0d2705c385f64b6e6711c1726cd9178f40b598e/artiq/firmware/libeh/eh_artiq.rs>)
+/// for ARTIQ-specific notes.
+#[derive(Debug, Clone, Copy, Default)]
+pub struct CSlice;
+
+impl StructKind for CSlice {
+    type Fields<F: FieldVisitor> = CSliceFields<F>;
+
+    fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
+        Self::Fields { base: visitor.add("base"), len: visitor.add("len") }
+    }
+}
+
+impl StructModel<CSlice> {
+    /// Create a [`CSlice`].
+    ///
+    /// `base` and `len` must be LLVM global constants.
+    pub fn create_const<'ctx>(
+        &self,
+        type_context: TypeContext<'ctx>,
+        ctx: &CodeGenContext<'ctx, '_>,
+        base: Ptr<'ctx, IntModel<Byte>>,
+        len: Int<'ctx, SizeT>,
+    ) -> Struct<'ctx, CSlice> {
+        let value = self
+            .0
+            .get_struct_type(type_context, ctx.ctx)
+            .const_named_struct(&[base.value.into(), len.value.into()]);
+        self.believe_value(value)
+    }
+}

nac3core/src/codegen/structure/exception.rs

@@ -0,0 +1,57 @@
+use crate::codegen::model::*;
+
+use super::cslice::CSlice;
+
+/// The LLVM int type of an Exception ID.
+pub type ExceptionId = Int32;
+
+/// Fields of [`Exception<'ctx>`]
+///
+/// The definition came from `pub struct Exception<'a>` in
+/// <https://github.com/m-labs/artiq/blob/master/artiq/firmware/libeh/eh_artiq.rs>.
+pub struct ExceptionFields<F: FieldVisitor> {
+    /// nac3core's ID of the exception
+    pub id: F::Field<IntModel<ExceptionId>>,
+    /// The name of the file this `Exception` was raised in.
+    pub filename: F::Field<StructModel<CSlice>>,
+    /// The line number in the file this `Exception` was raised in.
+    pub line: F::Field<IntModel<Int32>>,
+    /// The column number in the file this `Exception` was raised in.
+    pub column: F::Field<IntModel<Int32>>,
+    /// The name of the Python function this `Exception` was raised in.
+    pub function: F::Field<StructModel<CSlice>>,
+    /// The message of this Exception.
+    ///
+    /// The message can optionally contain integer parameters `{0}`, `{1}`, and `{2}` in its string,
+    /// where they will be substituted by `params[0]`, `params[1]`, and `params[2]` respectively (as `int64_t`s).
+    /// Here is an example:
+    ///
+    /// ```ignore
+    /// "Index {0} is out of bounds! List only has {1} element(s)."
+    /// ```
+    ///
+    /// In this case, `params[0]` and `params[1]` must be specified, and `params[2]` is ***unused***.
+    /// Having only 3 parameters is a constraint in ARTIQ.
+    pub msg: F::Field<StructModel<CSlice>>,
+    pub params: [F::Field<IntModel<Int64>>; 3],
+}
+
+/// nac3core & ARTIQ's Exception
+#[derive(Debug, Clone, Copy, Default)]
+pub struct Exception;
+
+impl StructKind for Exception {
+    type Fields<F: FieldVisitor> = ExceptionFields<F>;
+
+    fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            id: visitor.add("id"),
+            filename: visitor.add("filename"),
+            line: visitor.add("line"),
+            column: visitor.add("column"),
+            function: visitor.add("function"),
+            msg: visitor.add("msg"),
+            params: [visitor.add("params[0]"), visitor.add("params[1]"), visitor.add("params[2]")],
+        }
+    }
+}

nac3core/src/codegen/structure/mod.rs

@@ -0,0 +1,3 @@
+pub mod cslice;
+pub mod exception;
+pub mod ndarray;

nac3core/src/codegen/structure/ndarray.rs

@@ -0,0 +1,27 @@
+use crate::codegen::*;
+
+pub struct NpArrayFields<F: FieldVisitor> {
+    pub data: F::Field<PtrModel<IntModel<Byte>>>,
+    pub itemsize: F::Field<IntModel<SizeT>>,
+    pub ndims: F::Field<IntModel<SizeT>>,
+    pub shape: F::Field<PtrModel<IntModel<SizeT>>>,
+    pub strides: F::Field<PtrModel<IntModel<SizeT>>>,
+}
+
+// TODO: Rename to `NDArray` when the old NDArray is removed.
+#[derive(Debug, Clone, Copy, Default)]
+pub struct NpArray;
+
+impl StructKind for NpArray {
+    type Fields<F: FieldVisitor> = NpArrayFields<F>;
+
+    fn visit_fields<F: FieldVisitor>(&self, visitor: &mut F) -> Self::Fields<F> {
+        Self::Fields {
+            data: visitor.add("data"),
+            itemsize: visitor.add("itemsize"),
+            ndims: visitor.add("ndims"),
+            shape: visitor.add("shape"),
+            strides: visitor.add("strides"),
+        }
+    }
+}

nac3core/src/codegen/test.rs

@@ -1,37 +1,34 @@
-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::{
+        classes::{ListType, NDArrayType, ProxyType, RangeType},
+        concrete_type::ConcreteTypeStore,
+        CodeGenContext, CodeGenLLVMOptions, CodeGenTargetMachineOptions, CodeGenTask,
+        CodeGenerator, 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 +64,6 @@ impl SymbolResolver for Resolver {
         &self,
         _: StrRef,
         _: &mut CodeGenContext<'ctx, '_>,
-        _: &mut dyn CodeGenerator,
     ) -> Option<ValueEnum<'ctx>> {
         unimplemented!()
     }
@@ -98,7 +94,7 @@ fn test_primitives() {
         "};
     let statements = parse_program(source, FileName::default()).unwrap();
 
-    let composer = TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 32).0;
+    let composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 32).0;
     let mut unifier = composer.unifier.clone();
     let primitives = composer.primitives_ty;
     let top_level = Arc::new(composer.make_top_level_context());
@@ -113,18 +109,8 @@ fn test_primitives() {
     let threads = vec![DefaultCodeGenerator::new("test".into(), 32).into()];
     let signature = FunSignature {
         args: vec![
-            FuncArg {
+            FuncArg { name: "a".into(), ty: primitives.int32, default_value: None },
-                name: "a".into(),
+            FuncArg { name: "b".into(), ty: primitives.int32, default_value: None },
-                ty: primitives.int32,
-                default_value: None,
-                is_vararg: false,
-            },
-            FuncArg {
-                name: "b".into(),
-                ty: primitives.int32,
-                default_value: None,
-                is_vararg: false,
-            },
         ],
         ret: primitives.int32,
         vars: VarMap::new(),
@@ -142,8 +128,7 @@ fn test_primitives() {
     };
     let mut virtual_checks = Vec::new();
     let mut calls = HashMap::new();
-    let mut identifiers: HashMap<_, _> =
+    let mut identifiers: HashSet<_> = ["a".into(), "b".into()].into();
-        ["a".into(), "b".into()].map(|id| (id, IdentifierInfo::default())).into();
     let mut inferencer = Inferencer {
         top_level: &top_level,
         function_data: &mut function_data,
@@ -263,19 +248,14 @@ fn test_simple_call() {
         "};
     let statements_2 = parse_program(source_2, FileName::default()).unwrap();
 
-    let composer = TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 32).0;
+    let composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 32).0;
     let mut unifier = composer.unifier.clone();
     let primitives = composer.primitives_ty;
     let top_level = Arc::new(composer.make_top_level_context());
     unifier.top_level = Some(top_level.clone());
 
     let signature = FunSignature {
-        args: vec![FuncArg {
+        args: vec![FuncArg { name: "a".into(), ty: primitives.int32, default_value: None }],
-            name: "a".into(),
-            ty: primitives.int32,
-            default_value: None,
-            is_vararg: false,
-        }],
         ret: primitives.int32,
         vars: VarMap::new(),
     };
@@ -322,8 +302,7 @@ fn test_simple_call() {
     };
     let mut virtual_checks = Vec::new();
     let mut calls = HashMap::new();
-    let mut identifiers: HashMap<_, _> =
+    let mut identifiers: HashSet<_> = ["a".into(), "foo".into()].into();
-        ["a".into(), "foo".into()].map(|id| (id, IdentifierInfo::default())).into();
     let mut inferencer = Inferencer {
         top_level: &top_level,
         function_data: &mut function_data,

nac3core/src/codegen/util/array_writer.rs

@@ -0,0 +1,34 @@
+use crate::codegen::{model::*, CodeGenContext, CodeGenerator};
+
+/// A closure containing details on how to write to/initialize an array.
+#[allow(clippy::type_complexity)]
+pub struct ArrayWriter<'ctx, G: CodeGenerator + ?Sized, Len: IntKind, Item: Model> {
+    /// Number of items to write
+    pub len: Int<'ctx, Len>,
+    /// Implementation to write to an array given its base pointer.
+    pub write: Box<
+        dyn Fn(
+                &mut G,
+                &mut CodeGenContext<'ctx, '_>,
+                Ptr<'ctx, Item>, // Base pointer
+            ) -> Result<(), String>
+            + 'ctx,
+    >,
+}
+
+impl<'ctx, G: CodeGenerator + ?Sized, Len: IntKind, Item: Model> ArrayWriter<'ctx, G, Len, Item> {
+    pub fn alloca_array_and_write(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: &str,
+    ) -> Result<Ptr<'ctx, Item>, String> {
+        let tyctx = generator.type_context(ctx.ctx);
+
+        let item_model = Item::default();
+
+        let item_array = item_model.array_alloca(tyctx, ctx, self.len.value, name);
+        (self.write)(generator, ctx, item_array)?;
+        Ok(item_array)
+    }
+}

nac3core/src/codegen/util/control.rs

@@ -0,0 +1,42 @@
+use crate::codegen::{
+    model::*,
+    stmt::{gen_for_callback_incrementing, BreakContinueHooks},
+    CodeGenContext, CodeGenerator,
+};
+
+// TODO: Document
+// TODO: Rename function
+/// Only allows positive steps
+pub fn gen_model_for<'ctx, 'a, G, F, I>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, 'a>,
+    start: Int<'ctx, I>,
+    stop: Int<'ctx, I>,
+    step: Int<'ctx, I>,
+    body: F,
+) -> Result<(), String>
+where
+    G: CodeGenerator + ?Sized,
+    F: FnOnce(
+        &mut G,
+        &mut CodeGenContext<'ctx, 'a>,
+        BreakContinueHooks<'ctx>,
+        Int<'ctx, I>,
+    ) -> Result<(), String>,
+    I: IntKind,
+{
+    let int_model = IntModel(I::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,
+    )
+}

nac3core/src/codegen/util/mod.rs

@@ -0,0 +1,3 @@
+pub mod array_writer;
+pub mod control;
+pub mod shape;

nac3core/src/codegen/util/shape.rs

@@ -0,0 +1,127 @@
+use inkwell::values::BasicValueEnum;
+
+use crate::{
+    codegen::{
+        classes::{ListValue, UntypedArrayLikeAccessor},
+        model::*,
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::{Type, TypeEnum},
+};
+
+use super::{array_writer::ArrayWriter, control::gen_model_for};
+
+// TODO: Generalize to complex iterables under a common interface
+/// Create an [`ArrayWriter`] from a NumPy-like `shape` argument input.
+/// * `shape` - The `shape` parameter.
+/// * `shape_ty` - The element type of the `NDArray`.
+///
+/// The `shape` 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])`
+///
+/// The `int32` values will be sign-extended to `SizeT`
+pub fn make_shape_writer<'ctx, G>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    shape: BasicValueEnum<'ctx>,
+    shape_ty: Type,
+) -> ArrayWriter<'ctx, G, SizeT, IntModel<SizeT>>
+where
+    G: CodeGenerator + ?Sized,
+{
+    let tyctx = generator.type_context(ctx.ctx);
+    let sizet_model = IntModel(SizeT);
+
+    match &*ctx.unifier.get_ty(shape_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])`
+
+            // TODO: Remove ListValue with Model
+
+            let shape = ListValue::from_ptr_val(shape.into_pointer_value(), tyctx.size_type, None);
+            let len =
+                sizet_model.check_value(tyctx, ctx.ctx, shape.load_size(ctx, Some("len"))).unwrap();
+
+            ArrayWriter {
+                len,
+                write: Box::new(move |generator, ctx, dst_array| {
+                    gen_model_for(
+                        generator,
+                        ctx,
+                        sizet_model.constant(tyctx, ctx.ctx, 0),
+                        len,
+                        sizet_model.constant(tyctx, ctx.ctx, 1),
+                        |generator, ctx, _hooks, i| {
+                            let dim =
+                                shape.data().get(ctx, generator, &i.value, None).into_int_value();
+                            let dim = sizet_model.s_extend_or_bit_cast(tyctx, ctx, dim, "");
+
+                            dst_array.offset(tyctx, ctx, i.value, "pdim").store(ctx, dim);
+                            Ok(())
+                        },
+                    )
+                }),
+            }
+        }
+        TypeEnum::TTuple { ty: tuple_types } => {
+            // 2. A tuple of ints; e.g., `np.empty((600, 800, 3))`
+
+            let ndims = tuple_types.len();
+
+            // A tuple has to be a StructValue
+            // Read [`codegen::expr::gen_expr`] to see how `nac3core` translates a Python tuple into LLVM.
+            let shape = shape.into_struct_value();
+
+            ArrayWriter {
+                len: sizet_model.constant(tyctx, ctx.ctx, ndims as u64),
+                write: Box::new(move |_generator, ctx, dst_array| {
+                    for axis in 0..ndims {
+                        let dim = ctx
+                            .builder
+                            .build_extract_value(shape, axis as u32, format!("dim{axis}").as_str())
+                            .unwrap()
+                            .into_int_value();
+                        let dim = sizet_model.s_extend_or_bit_cast(tyctx, ctx, dim, "");
+
+                        dst_array
+                            .offset(
+                                tyctx,
+                                ctx,
+                                sizet_model.constant(tyctx, ctx.ctx, axis as u64).value,
+                                "pdim",
+                            )
+                            .store(ctx, dim);
+                    }
+                    Ok(())
+                }),
+            }
+        }
+        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])`
+
+            // The value has to be an integer
+            let shape_int = shape.into_int_value();
+
+            ArrayWriter {
+                len: sizet_model.constant(tyctx, ctx.ctx, 1),
+                write: Box::new(move |_generator, ctx, dst_array| {
+                    let dim = sizet_model.s_extend_or_bit_cast(tyctx, ctx, shape_int, "");
+
+                    // Set shape[0] = shape_int
+                    dst_array
+                        .offset(tyctx, ctx, sizet_model.constant(tyctx, ctx.ctx, 0).value, "pdim")
+                        .store(ctx, dim);
+
+                    Ok(())
+                }),
+            }
+        }
+        _ => panic!("encountered shape type"),
+    }
+}

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;

nac3core/src/symbol_resolver.rs

@@ -1,15 +1,7 @@
-use std::{
+use std::fmt::Debug;
-    collections::{HashMap, HashSet},
+use std::rc::Rc;
-    fmt::{Debug, Display},
+use std::sync::Arc;
-    rc::Rc,
+use std::{collections::HashMap, collections::HashSet, fmt::Display};
-    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 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 {
@@ -82,14 +78,14 @@ impl SymbolValue {
             }
             Constant::Tuple(t) => {
                 let expected_ty = unifier.get_ty(expected_ty);
-                let TypeEnum::TTuple { ty, is_vararg_ctx } = expected_ty.as_ref() else {
+                let TypeEnum::TTuple { ty } = expected_ty.as_ref() else {
                     return Err(format!(
                         "Expected {:?}, but got Tuple",
                         expected_ty.get_type_name()
                     ));
                 };
 
-                assert!(*is_vararg_ctx || ty.len() == t.len());
+                assert_eq!(ty.len(), t.len());
 
                 let elems = t
                     .iter()
@@ -159,7 +155,7 @@ impl SymbolValue {
             SymbolValue::Bool(_) => primitives.bool,
             SymbolValue::Tuple(vs) => {
                 let vs_tys = vs.iter().map(|v| v.get_type(primitives, unifier)).collect::<Vec<_>>();
-                unifier.add_ty(TypeEnum::TTuple { ty: vs_tys, is_vararg_ctx: false })
+                unifier.add_ty(TypeEnum::TTuple { ty: vs_tys })
             }
             SymbolValue::OptionSome(_) | SymbolValue::OptionNone => primitives.option,
         }
@@ -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>;
@@ -487,7 +482,7 @@ pub fn parse_type_annotation<T>(
                         parse_type_annotation(resolver, top_level_defs, unifier, primitives, elt)
                     })
                     .collect::<Result<Vec<_>, _>>()?;
-                Ok(unifier.add_ty(TypeEnum::TTuple { ty, is_vararg_ctx: false }))
+                Ok(unifier.add_ty(TypeEnum::TTuple { ty }))
             } else {
                 Err(HashSet::from(["Expected multiple elements for tuple".into()]))
             }

nac3core/src/toplevel/builtins.rs

@@ -1,5 +1,6 @@
 use std::iter::once;
 
+use helper::{debug_assert_prim_is_allowed, make_exception_fields, PrimDefDetails};
 use indexmap::IndexMap;
 use inkwell::{
     attributes::{Attribute, AttributeLoc},
@@ -8,24 +9,28 @@ use inkwell::{
     IntPredicate,
 };
 use itertools::Either;
+use ndarray::basic::call_nac3_ndarray_len;
 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},
+        expr::destructure_range,
+        irrt::*,
+        model::*,
         numpy::*,
+        numpy_new,
         stmt::exn_constructor,
+        structure::ndarray::NpArray,
     },
     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(
@@ -44,26 +49,10 @@ pub fn get_exn_constructor(
             name: "msg".into(),
             ty: string,
             default_value: Some(SymbolValue::Str(String::new())),
-            is_vararg: false,
-        },
-        FuncArg {
-            name: "param0".into(),
-            ty: int64,
-            default_value: Some(SymbolValue::I64(0)),
-            is_vararg: false,
-        },
-        FuncArg {
-            name: "param1".into(),
-            ty: int64,
-            default_value: Some(SymbolValue::I64(0)),
-            is_vararg: false,
-        },
-        FuncArg {
-            name: "param2".into(),
-            ty: int64,
-            default_value: Some(SymbolValue::I64(0)),
-            is_vararg: false,
         },
+        FuncArg { name: "param0".into(), ty: int64, default_value: Some(SymbolValue::I64(0)) },
+        FuncArg { name: "param1".into(), ty: int64, default_value: Some(SymbolValue::I64(0)) },
+        FuncArg { name: "param2".into(), ty: int64, default_value: Some(SymbolValue::I64(0)) },
     ];
     let exn_type = unifier.add_ty(TypeEnum::TObj {
         obj_id: DefinitionId(class_id),
@@ -113,7 +102,7 @@ pub fn get_exn_constructor(
 /// * `name`: The name of the implemented NumPy function.
 /// * `ret_ty`: The return type of this function.
 /// * `param_ty`: The parameters accepted by this function, represented by a tuple of the
-///   [parameter type][Type] and the parameter symbol name.
+/// [parameter type][Type] and the parameter symbol name.
 /// * `codegen_callback`: A lambda generating LLVM IR for the implementation of this function.
 fn create_fn_by_codegen(
     unifier: &mut Unifier,
@@ -129,12 +118,7 @@ fn create_fn_by_codegen(
         signature: unifier.add_ty(TypeEnum::TFunc(FunSignature {
             args: param_ty
                 .iter()
-                .map(|p| FuncArg {
+                .map(|p| FuncArg { name: p.1.into(), ty: p.0, default_value: None })
-                    name: p.1.into(),
-                    ty: p.0,
-                    default_value: None,
-                    is_vararg: false,
-                })
                 .collect(),
             ret: ret_ty,
             vars: var_map.clone(),
@@ -153,7 +137,7 @@ fn create_fn_by_codegen(
 /// * `name`: The name of the implemented NumPy function.
 /// * `ret_ty`: The return type of this function.
 /// * `param_ty`: The parameters accepted by this function, represented by a tuple of the
-///   [parameter type][Type] and the parameter symbol name.
+/// [parameter type][Type] and the parameter symbol name.
 /// * `intrinsic_fn`: The fully-qualified name of the LLVM intrinsic function.
 fn create_fn_by_intrinsic(
     unifier: &mut Unifier,
@@ -215,10 +199,10 @@ fn create_fn_by_intrinsic(
 /// * `name`: The name of the implemented NumPy function.
 /// * `ret_ty`: The return type of this function.
 /// * `param_ty`: The parameters accepted by this function, represented by a tuple of the
-///   [parameter type][Type] and the parameter symbol name.
+/// [parameter type][Type] and the parameter symbol name.
 /// * `extern_fn`: The fully-qualified name of the extern function used as the implementation.
 /// * `attrs`: The list of attributes to apply to this function declaration. Note that `nounwind` is
-///   already implied by the C ABI.
+/// already implied by the C ABI.
 fn create_fn_by_extern(
     unifier: &mut Unifier,
     var_map: &VarMap,
@@ -512,6 +496,8 @@ impl<'a> BuiltinBuilder<'a> {
             | PrimDef::FunNpEye
             | PrimDef::FunNpIdentity => self.build_ndarray_other_factory_function(prim),
 
+            PrimDef::FunNpReshape => self.build_ndarray_view_functions(prim),
+
             PrimDef::FunStr => self.build_str_function(),
 
             PrimDef::FunFloor | PrimDef::FunFloor64 | PrimDef::FunCeil | PrimDef::FunCeil64 => {
@@ -576,22 +562,6 @@ impl<'a> BuiltinBuilder<'a> {
             | PrimDef::FunNpLdExp
             | 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
-            | PrimDef::FunNpLinalgSvd
-            | PrimDef::FunNpLinalgInv
-            | PrimDef::FunNpLinalgPinv
-            | PrimDef::FunNpLinalgMatrixPower
-            | PrimDef::FunNpLinalgDet
-            | PrimDef::FunSpLinalgLu
-            | PrimDef::FunSpLinalgSchur
-            | PrimDef::FunSpLinalgHessenberg => self.build_linalg_methods(prim),
         };
 
         if cfg!(debug_assertions) {
@@ -649,24 +619,17 @@ impl<'a> BuiltinBuilder<'a> {
         let make_ctor_signature = |unifier: &mut Unifier| {
             unifier.add_ty(TypeEnum::TFunc(FunSignature {
                 args: vec![
-                    FuncArg {
+                    FuncArg { name: "start".into(), ty: int32, default_value: None },
-                        name: "start".into(),
-                        ty: int32,
-                        default_value: None,
-                        is_vararg: false,
-                    },
                     FuncArg {
                         name: "stop".into(),
                         ty: int32,
                         // placeholder
                         default_value: Some(SymbolValue::I32(0)),
-                        is_vararg: false,
                     },
                     FuncArg {
                         name: "step".into(),
                         ty: int32,
                         default_value: Some(SymbolValue::I32(1)),
-                        is_vararg: false,
                     },
                 ],
                 ret: range,
@@ -922,7 +885,6 @@ impl<'a> BuiltinBuilder<'a> {
                         name: "n".into(),
                         ty: self.option_tvar.ty,
                         default_value: None,
-                        is_vararg: false,
                     }],
                     ret: self.primitives.option,
                     vars: into_var_map([self.option_tvar]),
@@ -1057,7 +1019,6 @@ impl<'a> BuiltinBuilder<'a> {
                     name: "n".into(),
                     ty: self.num_or_ndarray_ty.ty,
                     default_value: None,
-                    is_vararg: false,
                 }],
                 ret: self.num_or_ndarray_ty.ty,
                 vars: self.num_or_ndarray_var_map.clone(),
@@ -1247,9 +1208,11 @@ impl<'a> BuiltinBuilder<'a> {
             &[(self.ndarray_factory_fn_shape_arg_tvar.ty, "shape")],
             Box::new(move |ctx, obj, fun, args, generator| {
                 let func = match prim {
-                    PrimDef::FunNpNDArray | PrimDef::FunNpEmpty => gen_ndarray_empty,
+                    PrimDef::FunNpNDArray | PrimDef::FunNpEmpty => {
-                    PrimDef::FunNpZeros => gen_ndarray_zeros,
+                        numpy_new::factory::gen_ndarray_empty
-                    PrimDef::FunNpOnes => gen_ndarray_ones,
+                    }
+                    PrimDef::FunNpZeros => numpy_new::factory::gen_ndarray_zeros,
+                    PrimDef::FunNpOnes => numpy_new::factory::gen_ndarray_ones,
                     _ => unreachable!(),
                 };
                 func(ctx, &obj, fun, &args, generator).map(|val| Some(val.as_basic_value_enum()))
@@ -1277,23 +1240,16 @@ impl<'a> BuiltinBuilder<'a> {
                     simple_name: prim.simple_name().into(),
                     signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
                         args: vec![
-                            FuncArg {
+                            FuncArg { name: "object".into(), ty: tv.ty, default_value: None },
-                                name: "object".into(),
-                                ty: tv.ty,
-                                default_value: None,
-                                is_vararg: false,
-                            },
                             FuncArg {
                                 name: "copy".into(),
                                 ty: bool,
                                 default_value: Some(SymbolValue::Bool(true)),
-                                is_vararg: false,
                             },
                             FuncArg {
                                 name: "ndmin".into(),
                                 ty: int32,
                                 default_value: Some(SymbolValue::U32(0)),
-                                is_vararg: false,
                             },
                         ],
                         ret: ndarray,
@@ -1324,7 +1280,7 @@ impl<'a> BuiltinBuilder<'a> {
                     // type variable
                     &[(self.list_int32, "shape"), (tv.ty, "fill_value")],
                     Box::new(move |ctx, obj, fun, args, generator| {
-                        gen_ndarray_full(ctx, &obj, fun, &args, generator)
+                        numpy_new::factory::gen_ndarray_full(ctx, &obj, fun, &args, generator)
                             .map(|val| Some(val.as_basic_value_enum()))
                     }),
                 )
@@ -1335,24 +1291,17 @@ impl<'a> BuiltinBuilder<'a> {
                     simple_name: prim.simple_name().into(),
                     signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
                         args: vec![
-                            FuncArg {
+                            FuncArg { name: "N".into(), ty: int32, default_value: None },
-                                name: "N".into(),
-                                ty: int32,
-                                default_value: None,
-                                is_vararg: false,
-                            },
                             // TODO(Derppening): Default values current do not work?
                             FuncArg {
                                 name: "M".into(),
                                 ty: int32,
                                 default_value: Some(SymbolValue::OptionNone),
-                                is_vararg: false,
                             },
                             FuncArg {
                                 name: "k".into(),
                                 ty: int32,
                                 default_value: Some(SymbolValue::I32(0)),
-                                is_vararg: false,
                             },
                         ],
                         ret: self.ndarray_float_2d,
@@ -1386,6 +1335,41 @@ impl<'a> BuiltinBuilder<'a> {
         }
     }
 
+    // Build functions related to NDArray views
+    fn build_ndarray_view_functions(&mut self, prim: PrimDef) -> TopLevelDef {
+        debug_assert_prim_is_allowed(prim, &[PrimDef::FunNpReshape]);
+
+        match prim {
+            PrimDef::FunNpReshape => {
+                // TODO: Support scalar inputs, e.g., `np.reshape(99, (1, 1, 1, 1))`
+
+                let new_ndim_ty = self.unifier.get_fresh_var(Some("NewNDim".into()), None);
+                let returned_ndarray_ty = make_ndarray_ty(
+                    self.unifier,
+                    self.primitives,
+                    Some(self.ndarray_dtype_tvar.ty),
+                    Some(new_ndim_ty.ty),
+                );
+
+                create_fn_by_codegen(
+                    self.unifier,
+                    &into_var_map([self.ndarray_dtype_tvar, self.ndarray_ndims_tvar, new_ndim_ty]),
+                    prim.name(),
+                    returned_ndarray_ty,
+                    &[
+                        (self.primitives.ndarray, "array"),
+                        (self.ndarray_factory_fn_shape_arg_tvar.ty, "shape"),
+                    ],
+                    Box::new(|ctx, obj, fun, args, generator| {
+                        numpy_new::view::gen_ndarray_reshape(ctx, &obj, fun, &args, generator)
+                            .map(|val| Some(val.as_basic_value_enum()))
+                    }),
+                )
+            }
+            _ => unreachable!(),
+        }
+    }
+
     /// Build the `str()` function.
     fn build_str_function(&mut self) -> TopLevelDef {
         let prim = PrimDef::FunStr;
@@ -1396,12 +1380,7 @@ impl<'a> BuiltinBuilder<'a> {
             name: prim.name().into(),
             simple_name: prim.simple_name().into(),
             signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
-                args: vec![FuncArg {
+                args: vec![FuncArg { name: "s".into(), ty: str, default_value: None }],
-                    name: "s".into(),
-                    ty: str,
-                    default_value: None,
-                    is_vararg: false,
-                }],
                 ret: str,
                 vars: VarMap::default(),
             })),
@@ -1465,21 +1444,31 @@ impl<'a> BuiltinBuilder<'a> {
     fn build_len_function(&mut self) -> TopLevelDef {
         let prim = PrimDef::FunLen;
 
-        // Type handled in [`Inferencer::try_fold_special_call`]
+        let PrimitiveStore { uint64, int32, .. } = *self.primitives;
-        let arg_tvar = self.unifier.get_dummy_var();
 
+        let tvar = self.unifier.get_fresh_var(Some("L".into()), None);
+        let list = self
+            .unifier
+            .subst(
+                self.primitives.list,
+                &into_var_map([TypeVar { id: self.list_tvar.id, ty: tvar.ty }]),
+            )
+            .unwrap();
+        let ndims = self.unifier.get_fresh_const_generic_var(uint64, Some("N".into()), None);
+        let ndarray = make_ndarray_ty(self.unifier, self.primitives, Some(tvar.ty), Some(ndims.ty));
+
+        let arg_ty = self.unifier.get_fresh_var_with_range(
+            &[list, ndarray, self.primitives.range],
+            Some("I".into()),
+            None,
+        );
         TopLevelDef::Function {
             name: prim.name().into(),
             simple_name: prim.simple_name().into(),
             signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
-                args: vec![FuncArg {
+                args: vec![FuncArg { name: "ls".into(), ty: arg_ty.ty, default_value: None }],
-                    name: "obj".into(),
+                ret: int32,
-                    ty: arg_tvar.ty,
+                vars: into_var_map([tvar, arg_ty]),
-                    default_value: None,
-                    is_vararg: false,
-                }],
-                ret: self.primitives.int32,
-                vars: into_var_map([arg_tvar]),
             })),
             var_id: Vec::default(),
             instance_to_symbol: HashMap::default(),
@@ -1487,10 +1476,48 @@ impl<'a> BuiltinBuilder<'a> {
             resolver: None,
             codegen_callback: Some(Arc::new(GenCall::new(Box::new(
                 move |ctx, _, fun, args, generator| {
+                    let range_ty = ctx.primitives.range;
                     let arg_ty = fun.0.args[0].ty;
                     let arg = args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
+                    Ok(if ctx.unifier.unioned(arg_ty, range_ty) {
+                        let arg = RangeValue::from_ptr_val(arg.into_pointer_value(), Some("range"));
+                        let (start, end, step) = destructure_range(ctx, arg);
+                        Some(calculate_len_for_slice_range(generator, ctx, start, end, step).into())
+                    } else {
+                        match &*ctx.unifier.get_ty_immutable(arg_ty) {
+                            TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::List.id() => {
+                                let int32 = ctx.ctx.i32_type();
+                                let zero = int32.const_zero();
+                                let len = ctx
+                                    .build_gep_and_load(
+                                        arg.into_pointer_value(),
+                                        &[zero, int32.const_int(1, false)],
+                                        None,
+                                    )
+                                    .into_int_value();
+                                if len.get_type().get_bit_width() == 32 {
+                                    Some(len.into())
+                                } else {
+                                    Some(
+                                        ctx.builder
+                                            .build_int_truncate(len, int32, "len2i32")
+                                            .map(Into::into)
+                                            .unwrap(),
+                                    )
+                                }
+                            }
+                            TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
+                                let tyctx = generator.type_context(ctx.ctx);
+                                let pndarray_model = PtrModel(StructModel(NpArray));
 
-                    builtin_fns::call_len(generator, ctx, (arg_ty, arg)).map(|ret| Some(ret.into()))
+                                let ndarray =
+                                    pndarray_model.check_value(tyctx, ctx.ctx, arg).unwrap();
+                                let len = call_nac3_ndarray_len(generator, ctx, ndarray);
+                                Some(len.value.as_basic_value_enum())
+                            }
+                            _ => unreachable!(),
+                        }
+                    })
                 },
             )))),
             loc: None,
@@ -1506,18 +1533,8 @@ impl<'a> BuiltinBuilder<'a> {
             simple_name: prim.simple_name().into(),
             signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
                 args: vec![
-                    FuncArg {
+                    FuncArg { name: "m".into(), ty: self.num_ty.ty, default_value: None },
-                        name: "m".into(),
+                    FuncArg { name: "n".into(), ty: self.num_ty.ty, default_value: None },
-                        ty: self.num_ty.ty,
-                        default_value: None,
-                        is_vararg: false,
-                    },
-                    FuncArg {
-                        name: "n".into(),
-                        ty: self.num_ty.ty,
-                        default_value: None,
-                        is_vararg: false,
-                    },
                 ],
                 ret: self.num_ty.ty,
                 vars: self.num_var_map.clone(),
@@ -1599,12 +1616,7 @@ impl<'a> BuiltinBuilder<'a> {
             signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
                 args: param_ty
                     .iter()
-                    .map(|p| FuncArg {
+                    .map(|p| FuncArg { name: p.1.into(), ty: p.0, default_value: None })
-                        name: p.1.into(),
-                        ty: p.0,
-                        default_value: None,
-                        is_vararg: false,
-                    })
                     .collect(),
                 ret: ret_ty.ty,
                 vars: into_var_map([x1_ty, x2_ty, ret_ty]),
@@ -1645,7 +1657,6 @@ impl<'a> BuiltinBuilder<'a> {
                     name: "n".into(),
                     ty: self.num_or_ndarray_ty.ty,
                     default_value: None,
-                    is_vararg: false,
                 }],
                 ret: self.num_or_ndarray_ty.ty,
                 vars: self.num_or_ndarray_var_map.clone(),
@@ -1834,12 +1845,7 @@ impl<'a> BuiltinBuilder<'a> {
             signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
                 args: param_ty
                     .iter()
-                    .map(|p| FuncArg {
+                    .map(|p| FuncArg { name: p.1.into(), ty: p.0, default_value: None })
-                        name: p.1.into(),
-                        ty: p.0,
-                        default_value: None,
-                        is_vararg: false,
-                    })
                     .collect(),
                 ret: ret_ty.ty,
                 vars: into_var_map([x1_ty, x2_ty, ret_ty]),
@@ -1873,207 +1879,6 @@ 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`
-    fn build_linalg_methods(&mut self, prim: PrimDef) -> TopLevelDef {
-        debug_assert_prim_is_allowed(
-            prim,
-            &[
-                PrimDef::FunNpDot,
-                PrimDef::FunNpLinalgCholesky,
-                PrimDef::FunNpLinalgQr,
-                PrimDef::FunNpLinalgSvd,
-                PrimDef::FunNpLinalgInv,
-                PrimDef::FunNpLinalgPinv,
-                PrimDef::FunNpLinalgMatrixPower,
-                PrimDef::FunNpLinalgDet,
-                PrimDef::FunSpLinalgLu,
-                PrimDef::FunSpLinalgSchur,
-                PrimDef::FunSpLinalgHessenberg,
-            ],
-        );
-
-        match prim {
-            PrimDef::FunNpDot => create_fn_by_codegen(
-                self.unifier,
-                &self.num_or_ndarray_var_map,
-                prim.name(),
-                self.num_ty.ty,
-                &[(self.num_or_ndarray_ty.ty, "x1"), (self.num_or_ndarray_ty.ty, "x2")],
-                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))?))
-                }),
-            ),
-
-            PrimDef::FunNpLinalgCholesky | PrimDef::FunNpLinalgInv | PrimDef::FunNpLinalgPinv => {
-                create_fn_by_codegen(
-                    self.unifier,
-                    &VarMap::new(),
-                    prim.name(),
-                    self.ndarray_float_2d,
-                    &[(self.ndarray_float_2d, "x1")],
-                    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 func = match prim {
-                            PrimDef::FunNpLinalgCholesky => builtin_fns::call_np_linalg_cholesky,
-                            PrimDef::FunNpLinalgInv => builtin_fns::call_np_linalg_inv,
-                            PrimDef::FunNpLinalgPinv => builtin_fns::call_np_linalg_pinv,
-                            _ => unreachable!(),
-                        };
-                        Ok(Some(func(generator, ctx, (x1_ty, x1_val))?))
-                    }),
-                )
-            }
-
-            PrimDef::FunNpLinalgQr
-            | PrimDef::FunSpLinalgLu
-            | PrimDef::FunSpLinalgSchur
-            | PrimDef::FunSpLinalgHessenberg => {
-                let ret_ty = self.unifier.add_ty(TypeEnum::TTuple {
-                    ty: vec![self.ndarray_float_2d, self.ndarray_float_2d],
-                    is_vararg_ctx: false,
-                });
-                create_fn_by_codegen(
-                    self.unifier,
-                    &VarMap::new(),
-                    prim.name(),
-                    ret_ty,
-                    &[(self.ndarray_float_2d, "x1")],
-                    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 func = match prim {
-                            PrimDef::FunNpLinalgQr => builtin_fns::call_np_linalg_qr,
-                            PrimDef::FunSpLinalgLu => builtin_fns::call_sp_linalg_lu,
-                            PrimDef::FunSpLinalgSchur => builtin_fns::call_sp_linalg_schur,
-                            PrimDef::FunSpLinalgHessenberg => {
-                                builtin_fns::call_sp_linalg_hessenberg
-                            }
-                            _ => unreachable!(),
-                        };
-                        Ok(Some(func(generator, ctx, (x1_ty, x1_val))?))
-                    }),
-                )
-            }
-
-            PrimDef::FunNpLinalgSvd => {
-                let ret_ty = self.unifier.add_ty(TypeEnum::TTuple {
-                    ty: vec![self.ndarray_float_2d, self.ndarray_float, self.ndarray_float_2d],
-                    is_vararg_ctx: false,
-                });
-                create_fn_by_codegen(
-                    self.unifier,
-                    &VarMap::new(),
-                    prim.name(),
-                    ret_ty,
-                    &[(self.ndarray_float_2d, "x1")],
-                    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)?;
-
-                        Ok(Some(builtin_fns::call_np_linalg_svd(generator, ctx, (x1_ty, x1_val))?))
-                    }),
-                )
-            }
-            PrimDef::FunNpLinalgMatrixPower => create_fn_by_codegen(
-                self.unifier,
-                &VarMap::new(),
-                prim.name(),
-                self.ndarray_float_2d,
-                &[(self.ndarray_float_2d, "x1"), (self.primitives.int32, "power")],
-                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(builtin_fns::call_np_linalg_matrix_power(
-                        generator,
-                        ctx,
-                        (x1_ty, x1_val),
-                        (x2_ty, x2_val),
-                    )?))
-                }),
-            ),
-            PrimDef::FunNpLinalgDet => create_fn_by_codegen(
-                self.unifier,
-                &VarMap::new(),
-                prim.name(),
-                self.primitives.float,
-                &[(self.ndarray_float_2d, "x1")],
-                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)?;
-                    Ok(Some(builtin_fns::call_np_linalg_det(generator, ctx, (x1_ty, x1_val))?))
-                }),
-            ),
-            _ => unreachable!(),
-        }
-    }
-
     fn create_method(prim: PrimDef, method_ty: Type) -> (StrRef, Type, DefinitionId) {
         (prim.simple_name().into(), method_ty, prim.id())
     }

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::*;
-
-use super::{numpy::unpack_ndarray_var_tys, *};
-use crate::{
-    symbol_resolver::SymbolValue,
-    typecheck::typedef::{into_var_map, iter_type_vars, Mapping, TypeVarId, VarMap},
-};
 
 /// All primitive types and functions in nac3core.
 #[derive(Clone, Copy, Debug, EnumIter, PartialEq, Eq)]
@@ -54,6 +52,9 @@ pub enum PrimDef {
     FunNpEye,
     FunNpIdentity,
 
+    // NumPy view functions
+    FunNpReshape,
+
     // Miscellaneous NumPy & SciPy functions
     FunNpRound,
     FunNpFloor,
@@ -101,21 +102,6 @@ pub enum PrimDef {
     FunNpLdExp,
     FunNpHypot,
     FunNpNextAfter,
-    FunNpTranspose,
-    FunNpReshape,
-
-    // Linalg functions
-    FunNpDot,
-    FunNpLinalgCholesky,
-    FunNpLinalgQr,
-    FunNpLinalgSvd,
-    FunNpLinalgInv,
-    FunNpLinalgPinv,
-    FunNpLinalgMatrixPower,
-    FunNpLinalgDet,
-    FunSpLinalgLu,
-    FunSpLinalgSchur,
-    FunSpLinalgHessenberg,
 
     // Miscellaneous Python & NAC3 functions
     FunInt32,
@@ -240,6 +226,9 @@ impl PrimDef {
             PrimDef::FunNpEye => fun("np_eye", None),
             PrimDef::FunNpIdentity => fun("np_identity", None),
 
+            // NumPy view functions
+            PrimDef::FunNpReshape => fun("np_reshape", None),
+
             // Miscellaneous NumPy & SciPy functions
             PrimDef::FunNpRound => fun("np_round", None),
             PrimDef::FunNpFloor => fun("np_floor", None),
@@ -287,21 +276,6 @@ 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),
-            PrimDef::FunNpLinalgCholesky => fun("np_linalg_cholesky", None),
-            PrimDef::FunNpLinalgQr => fun("np_linalg_qr", None),
-            PrimDef::FunNpLinalgSvd => fun("np_linalg_svd", None),
-            PrimDef::FunNpLinalgInv => fun("np_linalg_inv", None),
-            PrimDef::FunNpLinalgPinv => fun("np_linalg_pinv", None),
-            PrimDef::FunNpLinalgMatrixPower => fun("np_linalg_matrix_power", None),
-            PrimDef::FunNpLinalgDet => fun("np_linalg_det", None),
-            PrimDef::FunSpLinalgLu => fun("sp_linalg_lu", None),
-            PrimDef::FunSpLinalgSchur => fun("sp_linalg_schur", None),
-            PrimDef::FunSpLinalgHessenberg => fun("sp_linalg_hessenberg", None),
 
             // Miscellaneous Python & NAC3 functions
             PrimDef::FunInt32 => fun("int32", None),
@@ -389,9 +363,6 @@ impl TopLevelDef {
                     r
                 }
             ),
-            TopLevelDef::Variable { name, ty, .. } => {
-                format!("Variable {{ name: {name:?}, ty: {:?} }}", unifier.stringify(*ty),)
-            }
         }
     }
 }
@@ -510,7 +481,6 @@ impl TopLevelComposer {
                 name: "value".into(),
                 ty: ndarray_dtype_tvar.ty,
                 default_value: None,
-                is_vararg: false,
             }],
             ret: none,
             vars: into_var_map([ndarray_dtype_tvar, ndarray_ndims_tvar]),
@@ -593,18 +563,6 @@ 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 +708,7 @@ impl TopLevelComposer {
         )
     }
 
-    /// This function returns the fields that have been initialized in the `__init__` function of a class
+    pub fn get_all_assigned_field(stmts: &[Stmt<()>]) -> Result<HashSet<StrRef>, HashSet<String>> {
-    /// 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>> {
         let mut result = HashSet::new();
         for s in stmts {
             match &s.node {
@@ -795,138 +744,30 @@ 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(
+                    result.extend(Self::get_all_assigned_field(body.as_slice())?);
-                        class_id,
+                    result.extend(Self::get_all_assigned_field(orelse.as_slice())?);
-                        definition_ast_list,
-                        body.as_slice(),
-                    )?);
-                    result.extend(Self::get_all_assigned_field(
-                        class_id,
-                        definition_ast_list,
-                        orelse.as_slice(),
-                    )?);
                 }
                 ast::StmtKind::If { body, orelse, .. } => {
-                    let inited_for_sure = Self::get_all_assigned_field(
+                    let inited_for_sure = Self::get_all_assigned_field(body.as_slice())?
-                        class_id,
+                        .intersection(&Self::get_all_assigned_field(orelse.as_slice())?)
-                        definition_ast_list,
+                        .copied()
-                        body.as_slice(),
+                        .collect::<HashSet<_>>();
-                    )?
-                    .intersection(&Self::get_all_assigned_field(
-                        class_id,
-                        definition_ast_list,
-                        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(
+                    let inited_for_sure = Self::get_all_assigned_field(body.as_slice())?
-                        class_id,
+                        .intersection(&Self::get_all_assigned_field(orelse.as_slice())?)
-                        definition_ast_list,
+                        .copied()
-                        body.as_slice(),
+                        .collect::<HashSet<_>>();
-                    )?
-                    .intersection(&Self::get_all_assigned_field(
-                        class_id,
-                        definition_ast_list,
-                        orelse.as_slice(),
-                    )?)
-                    .copied()
-                    .collect::<HashSet<_>>();
                     result.extend(inited_for_sure);
-                    result.extend(Self::get_all_assigned_field(
+                    result.extend(Self::get_all_assigned_field(finalbody.as_slice())?);
-                        class_id,
-                        definition_ast_list,
-                        finalbody.as_slice(),
-                    )?);
                 }
                 ast::StmtKind::With { body, .. } => {
-                    result.extend(Self::get_all_assigned_field(
+                    result.extend(Self::get_all_assigned_field(body.as_slice())?);
-                        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
-                        )]));
-                    }
                 }
                 ast::StmtKind::Pass { .. }
                 | ast::StmtKind::Assert { .. }
-                | ast::StmtKind::AnnAssign { .. } => {}
+                | ast::StmtKind::Expr { .. } => {}
 
                 _ => {
                     unimplemented!()

nac3core/src/toplevel/mod.rs

@@ -6,36 +6,36 @@ use std::{
     sync::Arc,
 };
 
-use inkwell::values::BasicValueEnum;
+use super::codegen::CodeGenContext;
-use itertools::Itertools;
+use super::typecheck::type_inferencer::PrimitiveStore;
-use parking_lot::RwLock;
+use super::typecheck::typedef::{
-
+    FunSignature, FuncArg, SharedUnifier, Type, TypeEnum, Unifier, VarMap,
-use nac3parser::ast::{self, Expr, Location, Stmt, StrRef};
+};
-
 use crate::{
-    codegen::{CodeGenContext, CodeGenerator},
+    codegen::CodeGenerator,
     symbol_resolver::{SymbolResolver, ValueEnum},
     typecheck::{
-        type_inferencer::{CodeLocation, PrimitiveStore},
+        type_inferencer::CodeLocation,
-        typedef::{
+        typedef::{CallId, TypeVarId},
-            CallId, FunSignature, FuncArg, SharedUnifier, Type, TypeEnum, TypeVarId, Unifier,
-            VarMap,
-        },
     },
 };
-use composer::*;
+use inkwell::values::BasicValueEnum;
-use type_annotation::*;
+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>,
@@ -130,14 +130,14 @@ pub enum TopLevelDef {
         /// Function instance to symbol mapping
         ///
         /// * Key: String representation of type variable values, sorted by variable ID in ascending
-        ///   order, including type variables associated with the class.
+        /// order, including type variables associated with the class.
         /// * Value: Function symbol name.
         instance_to_symbol: HashMap<String, String>,
         /// Function instances to annotated AST mapping
         ///
         /// * Key: String representation of type variable values, sorted by variable ID in ascending
-        ///   order, including type variables associated with the class. Excluding rigid type
+        /// order, including type variables associated with the class. Excluding rigid type
-        ///   variables.
+        /// variables.
         ///
         /// Rigid type variables that would be substituted when the function is instantiated.
         instance_to_stmt: HashMap<String, FunInstance>,
@@ -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 {

nac3core/src/toplevel/numpy.rs

@@ -1,17 +1,18 @@
-use itertools::Itertools;
+use crate::{
-
+    toplevel::helper::PrimDef,
-use super::helper::PrimDef;
+    typecheck::{
-use crate::typecheck::{
+        type_inferencer::PrimitiveStore,
-    type_inferencer::PrimitiveStore,
+        typedef::{Type, TypeEnum, TypeVarId, Unifier, VarMap},
-    typedef::{Type, TypeEnum, TypeVarId, Unifier, VarMap},
+    },
 };
+use itertools::Itertools;
 
 /// Creates a `ndarray` [`Type`] with the given type arguments.
 ///
 /// * `dtype` - The element type of the `ndarray`, or [`None`] if the type variable is not
-///   specialized.
+/// specialized.
 /// * `ndims` - The number of dimensions of the `ndarray`, or [`None`] if the type variable is not
-///   specialized.
+/// specialized.
 pub fn make_ndarray_ty(
     unifier: &mut Unifier,
     primitives: &PrimitiveStore,
@@ -24,9 +25,9 @@ pub fn make_ndarray_ty(
 /// Substitutes type variables in `ndarray`.
 ///
 /// * `dtype` - The element type of the `ndarray`, or [`None`] if the type variable is not
-///   specialized.
+/// specialized.
 /// * `ndims` - The number of dimensions of the `ndarray`, or [`None`] if the type variable is not
-///   specialized.
+/// specialized.
 pub fn subst_ndarray_tvars(
     unifier: &mut Unifier,
     ndarray: Type,

nac3core/src/toplevel/snapshots/nac3core__toplevel__test__test_analyze__generic_class.snap

@@ -5,7 +5,7 @@ expression: res_vec
 [
     "Class {\nname: \"Generic_A\",\nancestors: [\"Generic_A[V]\", \"B\"],\nfields: [\"aa\", \"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"foo\", \"fn[[b:T], none]\"), (\"fun\", \"fn[[a:int32], V]\")],\ntype_vars: [\"V\"]\n}\n",
     "Function {\nname: \"Generic_A.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
-    "Function {\nname: \"Generic_A.fun\",\nsig: \"fn[[a:int32], V]\",\nvar_id: [TypeVarId(241)]\n}\n",
+    "Function {\nname: \"Generic_A.fun\",\nsig: \"fn[[a:int32], V]\",\nvar_id: [TypeVarId(248)]\n}\n",
     "Class {\nname: \"B\",\nancestors: [\"B\"],\nfields: [\"aa\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"foo\", \"fn[[b:T], none]\")],\ntype_vars: []\n}\n",
     "Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
     "Function {\nname: \"B.foo\",\nsig: \"fn[[b:T], none]\",\nvar_id: []\n}\n",

nac3core/src/toplevel/snapshots/nac3core__toplevel__test__test_analyze__inheritance_override.snap

@@ -7,7 +7,7 @@ expression: res_vec
     "Function {\nname: \"A.__init__\",\nsig: \"fn[[t:T], none]\",\nvar_id: []\n}\n",
     "Function {\nname: \"A.fun\",\nsig: \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\",\nvar_id: []\n}\n",
     "Function {\nname: \"A.foo\",\nsig: \"fn[[c:C], none]\",\nvar_id: []\n}\n",
-    "Class {\nname: \"B\",\nancestors: [\"B[typevar230]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: [\"typevar230\"]\n}\n",
+    "Class {\nname: \"B\",\nancestors: [\"B[typevar237]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: [\"typevar237\"]\n}\n",
     "Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
     "Function {\nname: \"B.fun\",\nsig: \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\",\nvar_id: []\n}\n",
     "Class {\nname: \"C\",\nancestors: [\"C\", \"B[bool]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\", \"e\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: []\n}\n",

nac3core/src/toplevel/snapshots/nac3core__toplevel__test__test_analyze__list_tuple_generic.snap

@@ -5,8 +5,8 @@ expression: res_vec
 [
     "Function {\nname: \"foo\",\nsig: \"fn[[a:list[int32], b:tuple[T, float]], A[B, bool]]\",\nvar_id: []\n}\n",
     "Class {\nname: \"A\",\nancestors: [\"A[T, V]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[v:V], none]\"), (\"fun\", \"fn[[a:T], V]\")],\ntype_vars: [\"T\", \"V\"]\n}\n",
-    "Function {\nname: \"A.__init__\",\nsig: \"fn[[v:V], none]\",\nvar_id: [TypeVarId(243)]\n}\n",
+    "Function {\nname: \"A.__init__\",\nsig: \"fn[[v:V], none]\",\nvar_id: [TypeVarId(250)]\n}\n",
-    "Function {\nname: \"A.fun\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(248)]\n}\n",
+    "Function {\nname: \"A.fun\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(255)]\n}\n",
     "Function {\nname: \"gfun\",\nsig: \"fn[[a:A[list[float], int32]], none]\",\nvar_id: []\n}\n",
     "Class {\nname: \"B\",\nancestors: [\"B\"],\nfields: [],\nmethods: [(\"__init__\", \"fn[[], none]\")],\ntype_vars: []\n}\n",
     "Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",