[meta] Apply rustfmt changes

copy constructor -> clone
ld/dwarf: remove reader resets
2024-11-29 15:43:34 +08:00 · 2024-11-28 18:52:53 +08:00 · 2024-11-28 18:52:53 +08:00 · 2024-11-28 18:52:53 +08:00 · 2024-11-27 14:31:57 +08:00 · 2024-11-27 14:31:57 +08:00
132 changed files with 7457 additions and 10673 deletions
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@ -1,24 +1,24 @@
 # See https://pre-commit.com for more information
 # See https://pre-commit.com/hooks.html for more hooks
-default_stages: [commit]
+default_stages: [pre-commit]
 repos:
  - repo: local
    hooks:
      - id: nac3-cargo-fmt
        name: nac3 cargo format
-        entry: cargo
+        entry: nix
        language: system
        types: [file, rust]
        pass_filenames: false
        description: Runs cargo fmt on the codebase.
-        args: [fmt]
+        args: [develop, -c, cargo, fmt, --all]
      - id: nac3-cargo-clippy
        name: nac3 cargo clippy
-        entry: cargo
+        entry: nix
        language: system
        types: [file, rust]
        pass_filenames: false
        description: Runs cargo clippy on the codebase.
-        args: [clippy, --tests]
+        args: [develop, -c, cargo, clippy, --tests]
--- a/Cargo.lock
+++ b/Cargo.lock
@ -26,9 +26,9 @@ dependencies = [
 [[package]]
 name = "anstream"
-version = "0.6.15"
+version = "0.6.18"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "64e15c1ab1f89faffbf04a634d5e1962e9074f2741eef6d97f3c4e322426d526"
+checksum = "8acc5369981196006228e28809f761875c0327210a891e941f4c683b3a99529b"
 dependencies = [
 "anstyle",
 "anstyle-parse",
@ -41,67 +41,67 @@ dependencies = [
 [[package]]
 name = "anstyle"
-version = "1.0.8"
+version = "1.0.10"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1bec1de6f59aedf83baf9ff929c98f2ad654b97c9510f4e70cf6f661d49fd5b1"
+checksum = "55cc3b69f167a1ef2e161439aa98aed94e6028e5f9a59be9a6ffb47aef1651f9"
 [[package]]
 name = "anstyle-parse"
-version = "0.2.5"
+version = "0.2.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "eb47de1e80c2b463c735db5b217a0ddc39d612e7ac9e2e96a5aed1f57616c1cb"
+checksum = "3b2d16507662817a6a20a9ea92df6652ee4f94f914589377d69f3b21bc5798a9"
 dependencies = [
 "utf8parse",
 ]
 [[package]]
 name = "anstyle-query"
-version = "1.1.1"
+version = "1.1.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "6d36fc52c7f6c869915e99412912f22093507da8d9e942ceaf66fe4b7c14422a"
+checksum = "79947af37f4177cfead1110013d678905c37501914fba0efea834c3fe9a8d60c"
 dependencies = [
- "windows-sys 0.52.0",
+ "windows-sys 0.59.0",
 ]
 [[package]]
 name = "anstyle-wincon"
-version = "3.0.4"
+version = "3.0.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5bf74e1b6e971609db8ca7a9ce79fd5768ab6ae46441c572e46cf596f59e57f8"
+checksum = "2109dbce0e72be3ec00bed26e6a7479ca384ad226efdd66db8fa2e3a38c83125"
 dependencies = [
 "anstyle",
- "windows-sys 0.52.0",
+ "windows-sys 0.59.0",
 ]
 [[package]]
 name = "ascii-canvas"
-version = "3.0.0"
+version = "4.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8824ecca2e851cec16968d54a01dd372ef8f95b244fb84b84e70128be347c3c6"
+checksum = "ef1e3e699d84ab1b0911a1010c5c106aa34ae89aeac103be5ce0c3859db1e891"
 dependencies = [
 "term",
 ]
 [[package]]
 name = "autocfg"
-version = "1.3.0"
+version = "1.4.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0c4b4d0bd25bd0b74681c0ad21497610ce1b7c91b1022cd21c80c6fbdd9476b0"
+checksum = "ace50bade8e6234aa140d9a2f552bbee1db4d353f69b8217bc503490fc1a9f26"
 [[package]]
 name = "bit-set"
-version = "0.5.3"
+version = "0.8.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0700ddab506f33b20a03b13996eccd309a48e5ff77d0d95926aa0210fb4e95f1"
+checksum = "08807e080ed7f9d5433fa9b275196cfc35414f66a0c79d864dc51a0d825231a3"
 dependencies = [
 "bit-vec",
 ]
 [[package]]
 name = "bit-vec"
-version = "0.6.3"
+version = "0.8.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "349f9b6a179ed607305526ca489b34ad0a41aed5f7980fa90eb03160b69598fb"
+checksum = "5e764a1d40d510daf35e07be9eb06e75770908c27d411ee6c92109c9840eaaf7"
 [[package]]
 name = "bitflags"
@ -109,6 +109,15 @@ 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"
@ -117,9 +126,9 @@ checksum = "1fd0f2584146f6f2ef48085050886acf353beff7305ebd1ae69500e27c67f64b"
 [[package]]
 name = "cc"
-version = "1.1.15"
+version = "1.2.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "57b6a275aa2903740dc87da01c62040406b8812552e97129a63ea8850a17c6e6"
+checksum = "fd9de9f2205d5ef3fd67e685b0df337994ddd4495e2a28d185500d0e1edfea47"
 dependencies = [
 "shlex",
 ]
@ -132,9 +141,9 @@ checksum = "baf1de4339761588bc0619e3cbc0120ee582ebb74b53b4efbf79117bd2da40fd"
 [[package]]
 name = "clap"
-version = "4.5.16"
+version = "4.5.21"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ed6719fffa43d0d87e5fd8caeab59be1554fb028cd30edc88fc4369b17971019"
+checksum = "fb3b4b9e5a7c7514dfa52869339ee98b3156b0bfb4e8a77c4ff4babb64b1604f"
 dependencies = [
 "clap_builder",
 "clap_derive",
@ -142,9 +151,9 @@ dependencies = [
 [[package]]
 name = "clap_builder"
-version = "4.5.15"
+version = "4.5.21"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "216aec2b177652e3846684cbfe25c9964d18ec45234f0f5da5157b207ed1aab6"
+checksum = "b17a95aa67cc7b5ebd32aa5370189aa0d79069ef1c64ce893bd30fb24bff20ec"
 dependencies = [
 "anstream",
 "anstyle",
@ -154,27 +163,27 @@ dependencies = [
 [[package]]
 name = "clap_derive"
-version = "4.5.13"
+version = "4.5.18"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "501d359d5f3dcaf6ecdeee48833ae73ec6e42723a1e52419c79abf9507eec0a0"
+checksum = "4ac6a0c7b1a9e9a5186361f67dfa1b88213572f427fb9ab038efb2bd8c582dab"
 dependencies = [
 "heck 0.5.0",
 "proc-macro2",
 "quote",
- "syn 2.0.76",
+ "syn 2.0.87",
 ]
 [[package]]
 name = "clap_lex"
-version = "0.7.2"
+version = "0.7.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "1462739cb27611015575c0c11df5df7601141071f07518d56fcc1be504cbec97"
+checksum = "afb84c814227b90d6895e01398aee0d8033c00e7466aca416fb6a8e0eb19d8a7"
 [[package]]
 name = "colorchoice"
-version = "1.0.2"
+version = "1.0.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d3fd119d74b830634cea2a0f58bbd0d54540518a14397557951e79340abc28c0"
+checksum = "5b63caa9aa9397e2d9480a9b13673856c78d8ac123288526c37d7839f2a86990"
 [[package]]
 name = "console"
@ -188,6 +197,15 @@ dependencies = [
 "windows-sys 0.52.0",
 ]
 [[package]]
 name = "cpufeatures"
 version = "0.2.15"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "0ca741a962e1b0bff6d724a1a0958b686406e853bb14061f218562e1896f95e6"
 dependencies = [
 "libc",
 ]
 [[package]]
 name = "crossbeam"
 version = "0.8.4"
@ -245,32 +263,31 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "22ec99545bb0ed0ea7bb9b8e1e9122ea386ff8a48c0922e43f36d45ab09e0e80"
 [[package]]
-name = "crunchy"
+name = "crypto-common"
-version = "0.2.2"
+version = "0.1.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7a81dae078cea95a014a339291cec439d2f232ebe854a9d672b796c6afafa9b7"
+checksum = "1bfb12502f3fc46cca1bb51ac28df9d618d813cdc3d2f25b9fe775a34af26bb3"
 [[package]]
 name = "dirs-next"
 version = "2.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b98cf8ebf19c3d1b223e151f99a4f9f0690dca41414773390fc824184ac833e1"
 dependencies = [
- "cfg-if",
+ "generic-array",
- "dirs-sys-next",
+ "typenum",
 ]
 [[package]]
-name = "dirs-sys-next"
+name = "digest"
-version = "0.1.2"
+version = "0.10.7"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4ebda144c4fe02d1f7ea1a7d9641b6fc6b580adcfa024ae48797ecdeb6825b4d"
+checksum = "9ed9a281f7bc9b7576e61468ba615a66a5c8cfdff42420a70aa82701a3b1e292"
 dependencies = [
- "libc",
+ "block-buffer",
- "redox_users",
+ "crypto-common",
 "winapi",
 ]
 [[package]]
 name = "dissimilar"
 version = "1.0.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "59f8e79d1fbf76bdfbde321e902714bf6c49df88a7dda6fc682fc2979226962d"
 [[package]]
 name = "either"
 version = "1.13.0"
@ -310,9 +327,9 @@ dependencies = [
 [[package]]
 name = "fastrand"
-version = "2.1.1"
+version = "2.2.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e8c02a5121d4ea3eb16a80748c74f5549a5665e4c21333c6098f283870fbdea6"
+checksum = "486f806e73c5707928240ddc295403b1b93c96a02038563881c4a2fd84b81ac4"
 [[package]]
 name = "fixedbitset"
@ -329,6 +346,16 @@ 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"
@ -349,6 +376,12 @@ dependencies = [
 "wasi",
 ]
 [[package]]
 name = "glob"
 version = "0.3.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "d2fabcfbdc87f4758337ca535fb41a6d701b65693ce38287d856d1674551ec9b"
 [[package]]
 name = "hashbrown"
 version = "0.12.3"
@ -364,6 +397,12 @@ dependencies = [
 "ahash",
 ]
 [[package]]
 name = "hashbrown"
 version = "0.15.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "3a9bfc1af68b1726ea47d3d5109de126281def866b33970e10fbab11b5dafab3"
 [[package]]
 name = "heck"
 version = "0.4.1"
@ -376,6 +415,15 @@ version = "0.5.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "2304e00983f87ffb38b55b444b5e3b60a884b5d30c0fca7d82fe33449bbe55ea"
 [[package]]
 name = "home"
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 checksum = "e3d1354bf6b7235cb4a0576c2619fd4ed18183f689b12b006a0ee7329eeff9a5"
 dependencies = [
 "windows-sys 0.52.0",
 ]
 [[package]]
 name = "indexmap"
 version = "1.9.3"
@ -388,12 +436,12 @@ dependencies = [
 [[package]]
 name = "indexmap"
-version = "2.4.0"
+version = "2.6.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "93ead53efc7ea8ed3cfb0c79fc8023fbb782a5432b52830b6518941cebe6505c"
+checksum = "707907fe3c25f5424cce2cb7e1cbcafee6bdbe735ca90ef77c29e84591e5b9da"
 dependencies = [
 "equivalent",
- "hashbrown 0.14.5",
+ "hashbrown 0.15.1",
 ]
 [[package]]
@ -404,9 +452,9 @@ checksum = "b248f5224d1d606005e02c97f5aa4e88eeb230488bcc03bc9ca4d7991399f2b5"
 [[package]]
 name = "inkwell"
-version = "0.4.0"
+version = "0.5.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "b597a7b2cdf279aeef6d7149071e35e4bc87c2cf05a5b7f2d731300bffe587ea"
+checksum = "40fb405537710d51f6bdbc8471365ddd4cd6d3a3c3ad6e0c8291691031ba94b2"
 dependencies = [
 "either",
 "inkwell_internals",
@ -418,13 +466,13 @@ dependencies = [
 [[package]]
 name = "inkwell_internals"
-version = "0.9.0"
+version = "0.10.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4fa4d8d74483041a882adaa9a29f633253a66dde85055f0495c121620ac484b2"
+checksum = "9dd28cfd4cfba665d47d31c08a6ba637eed16770abca2eccbbc3ca831fef1e44"
 dependencies = [
 "proc-macro2",
 "quote",
- "syn 2.0.76",
+ "syn 2.0.87",
 ]
 [[package]]
@ -447,15 +495,6 @@ version = "1.70.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "7943c866cc5cd64cbc25b2e01621d07fa8eb2a1a23160ee81ce38704e97b8ecf"
 [[package]]
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 checksum = "b1c173a5686ce8bfa551b3563d0c2170bf24ca44da99c7ca4bfdab5418c3fe57"
 dependencies = [
 "either",
 ]
 [[package]]
 name = "itertools"
 version = "0.13.0"
@ -472,34 +511,44 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "49f1f14873335454500d59611f1cf4a4b0f786f9ac11f4312a78e4cf2566695b"
 [[package]]
-name = "lalrpop"
+name = "keccak"
-version = "0.20.2"
+version = "0.1.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "55cb077ad656299f160924eb2912aa147d7339ea7d69e1b5517326fdcec3c1ca"
+checksum = "ecc2af9a1119c51f12a14607e783cb977bde58bc069ff0c3da1095e635d70654"
 dependencies = [
 "cpufeatures",
 ]
 [[package]]
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 checksum = "06093b57658c723a21da679530e061a8c25340fa5a6f98e313b542268c7e2a1f"
 dependencies = [
 "ascii-canvas",
 "bit-set",
 "ena",
- "itertools 0.11.0",
+ "itertools",
 "lalrpop-util",
 "petgraph",
 "pico-args",
 "regex",
 "regex-syntax",
 "sha3",
 "string_cache",
 "term",
 "tiny-keccak",
 "unicode-xid",
 "walkdir",
 ]
 [[package]]
 name = "lalrpop-util"
-version = "0.20.2"
+version = "0.22.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "507460a910eb7b32ee961886ff48539633b788a36b65692b95f225b844c82553"
+checksum = "feee752d43abd0f4807a921958ab4131f692a44d4d599733d4419c5d586176ce"
 dependencies = [
 "regex-automata",
 "rustversion",
 ]
 [[package]]
@ -510,9 +559,9 @@ checksum = "bbd2bcb4c963f2ddae06a2efc7e9f3591312473c50c6685e1f298068316e66fe"
 [[package]]
 name = "libc"
-version = "0.2.158"
+version = "0.2.164"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d8adc4bb1803a324070e64a98ae98f38934d91957a99cfb3a43dcbc01bc56439"
+checksum = "433bfe06b8c75da9b2e3fbea6e5329ff87748f0b144ef75306e674c3f6f7c13f"
 [[package]]
 name = "libloading"
@ -524,16 +573,6 @@ 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"
@ -594,11 +633,9 @@ dependencies = [
 name = "nac3artiq"
 version = "0.1.0"
 dependencies = [
- "inkwell",
+ "itertools",
 "itertools 0.13.0",
 "nac3core",
 "nac3ld",
 "nac3parser",
 "parking_lot",
 "pyo3",
 "tempfile",
@ -609,7 +646,6 @@ name = "nac3ast"
 version = "0.1.0"
 dependencies = [
 "fxhash",
 "lazy_static",
 "parking_lot",
 "string-interner",
 ]
@ -619,11 +655,12 @@ name = "nac3core"
 version = "0.1.0"
 dependencies = [
 "crossbeam",
- "indexmap 2.4.0",
+ "indexmap 2.6.0",
 "indoc",
 "inkwell",
 "insta",
- "itertools 0.13.0",
+ "itertools",
 "nac3core_derive",
 "nac3parser",
 "parking_lot",
 "rayon",
@ -633,6 +670,18 @@ dependencies = [
 "test-case",
 ]
 [[package]]
 name = "nac3core_derive"
 version = "0.1.0"
 dependencies = [
 "nac3core",
 "proc-macro-error",
 "proc-macro2",
 "quote",
 "syn 2.0.87",
 "trybuild",
 ]
 [[package]]
 name = "nac3ld"
 version = "0.1.0"
@ -661,9 +710,7 @@ name = "nac3standalone"
 version = "0.1.0"
 dependencies = [
 "clap",
 "inkwell",
 "nac3core",
 "nac3parser",
 "parking_lot",
 ]
@ -675,9 +722,9 @@ checksum = "650eef8c711430f1a879fdd01d4745a7deea475becfb90269c06775983bbf086"
 [[package]]
 name = "once_cell"
-version = "1.19.0"
+version = "1.20.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3fdb12b2476b595f9358c5161aa467c2438859caa136dec86c26fdd2efe17b92"
+checksum = "1261fe7e33c73b354eab43b1273a57c8f967d0391e80353e51f764ac02cf6775"
 [[package]]
 name = "parking_lot"
@ -709,7 +756,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b4c5cc86750666a3ed20bdaf5ca2a0344f9c67674cae0515bec2da16fbaa47db"
 dependencies = [
 "fixedbitset",
- "indexmap 2.4.0",
+ "indexmap 2.6.0",
 ]
 [[package]]
@ -752,7 +799,7 @@ dependencies = [
 "phf_shared 0.11.2",
 "proc-macro2",
 "quote",
- "syn 2.0.76",
+ "syn 2.0.87",
 ]
 [[package]]
@ -781,9 +828,9 @@ checksum = "5be167a7af36ee22fe3115051bc51f6e6c7054c9348e28deb4f49bd6f705a315"
 [[package]]
 name = "portable-atomic"
-version = "1.7.0"
+version = "1.9.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "da544ee218f0d287a911e9c99a39a8c9bc8fcad3cb8db5959940044ecfc67265"
+checksum = "cc9c68a3f6da06753e9335d63e27f6b9754dd1920d941135b7ea8224f141adb2"
 [[package]]
 name = "ppv-lite86"
@ -801,10 +848,34 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "925383efa346730478fb4838dbe9137d2a47675ad789c546d150a6e1dd4ab31c"
 [[package]]
-name = "proc-macro2"
+name = "proc-macro-error"
-version = "1.0.86"
+version = "1.0.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "5e719e8df665df0d1c8fbfd238015744736151d4445ec0836b8e628aae103b77"
+checksum = "da25490ff9892aab3fcf7c36f08cfb902dd3e71ca0f9f9517bea02a73a5ce38c"
 dependencies = [
 "proc-macro-error-attr",
 "proc-macro2",
 "quote",
 "syn 1.0.109",
 "version_check",
 ]
 [[package]]
 name = "proc-macro-error-attr"
 version = "1.0.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "a1be40180e52ecc98ad80b184934baf3d0d29f979574e439af5a55274b35f869"
 dependencies = [
 "proc-macro2",
 "quote",
 "version_check",
 ]
 [[package]]
 name = "proc-macro2"
 version = "1.0.89"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "f139b0662de085916d1fb67d2b4169d1addddda1919e696f3252b740b629986e"
 dependencies = [
 "unicode-ident",
 ]
@ -856,7 +927,7 @@ dependencies = [
 "proc-macro2",
 "pyo3-macros-backend",
 "quote",
- "syn 2.0.76",
+ "syn 2.0.87",
 ]
 [[package]]
@ -869,7 +940,7 @@ dependencies = [
 "proc-macro2",
 "pyo3-build-config",
 "quote",
- "syn 2.0.76",
+ "syn 2.0.87",
 ]
 [[package]]
@ -933,29 +1004,18 @@ dependencies = [
 [[package]]
 name = "redox_syscall"
-version = "0.5.3"
+version = "0.5.7"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2a908a6e00f1fdd0dfd9c0eb08ce85126f6d8bbda50017e74bc4a4b7d4a926a4"
+checksum = "9b6dfecf2c74bce2466cabf93f6664d6998a69eb21e39f4207930065b27b771f"
 dependencies = [
 "bitflags",
 ]
 [[package]]
 name = "redox_users"
 version = "0.4.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "ba009ff324d1fc1b900bd1fdb31564febe58a8ccc8a6fdbb93b543d33b13ca43"
 dependencies = [
 "getrandom",
 "libredox",
 "thiserror",
 ]
 [[package]]
 name = "regex"
-version = "1.10.6"
+version = "1.11.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4219d74c6b67a3654a9fbebc4b419e22126d13d2f3c4a07ee0cb61ff79a79619"
+checksum = "b544ef1b4eac5dc2db33ea63606ae9ffcfac26c1416a2806ae0bf5f56b201191"
 dependencies = [
 "aho-corasick",
 "memchr",
@ -965,9 +1025,9 @@ dependencies = [
 [[package]]
 name = "regex-automata"
-version = "0.4.7"
+version = "0.4.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "38caf58cc5ef2fed281f89292ef23f6365465ed9a41b7a7754eb4e26496c92df"
+checksum = "809e8dc61f6de73b46c85f4c96486310fe304c434cfa43669d7b40f711150908"
 dependencies = [
 "aho-corasick",
 "memchr",
@ -976,9 +1036,9 @@ dependencies = [
 [[package]]
 name = "regex-syntax"
-version = "0.8.4"
+version = "0.8.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "7a66a03ae7c801facd77a29370b4faec201768915ac14a721ba36f20bc9c209b"
+checksum = "2b15c43186be67a4fd63bee50d0303afffcef381492ebe2c5d87f324e1b8815c"
 [[package]]
 name = "runkernel"
@ -989,9 +1049,9 @@ dependencies = [
 [[package]]
 name = "rustix"
-version = "0.38.35"
+version = "0.38.41"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a85d50532239da68e9addb745ba38ff4612a242c1c7ceea689c4bc7c2f43c36f"
+checksum = "d7f649912bc1495e167a6edee79151c84b1bad49748cb4f1f1167f459f6224f6"
 dependencies = [
 "bitflags",
 "errno",
@ -1002,9 +1062,9 @@ dependencies = [
 [[package]]
 name = "rustversion"
-version = "1.0.17"
+version = "1.0.18"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "955d28af4278de8121b7ebeb796b6a45735dc01436d898801014aced2773a3d6"
+checksum = "0e819f2bc632f285be6d7cd36e25940d45b2391dd6d9b939e79de557f7014248"
 [[package]]
 name = "ryu"
@ -1035,29 +1095,29 @@ checksum = "61697e0a1c7e512e84a621326239844a24d8207b4669b41bc18b32ea5cbf988b"
 [[package]]
 name = "serde"
-version = "1.0.209"
+version = "1.0.215"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "99fce0ffe7310761ca6bf9faf5115afbc19688edd00171d81b1bb1b116c63e09"
+checksum = "6513c1ad0b11a9376da888e3e0baa0077f1aed55c17f50e7b2397136129fb88f"
 dependencies = [
 "serde_derive",
 ]
 [[package]]
 name = "serde_derive"
-version = "1.0.209"
+version = "1.0.215"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a5831b979fd7b5439637af1752d535ff49f4860c0f341d1baeb6faf0f4242170"
+checksum = "ad1e866f866923f252f05c889987993144fb74e722403468a4ebd70c3cd756c0"
 dependencies = [
 "proc-macro2",
 "quote",
- "syn 2.0.76",
+ "syn 2.0.87",
 ]
 [[package]]
 name = "serde_json"
-version = "1.0.127"
+version = "1.0.133"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "8043c06d9f82bd7271361ed64f415fe5e12a77fdb52e573e7f06a516dea329ad"
+checksum = "c7fceb2473b9166b2294ef05efcb65a3db80803f0b03ef86a5fc88a2b85ee377"
 dependencies = [
 "itoa",
 "memchr",
@ -1065,6 +1125,15 @@ dependencies = [
 "serde",
 ]
 [[package]]
 name = "serde_spanned"
 version = "0.6.8"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "87607cb1398ed59d48732e575a4c28a7a8ebf2454b964fe3f224f2afc07909e1"
 dependencies = [
 "serde",
 ]
 [[package]]
 name = "serde_yaml"
 version = "0.8.26"
@ -1077,6 +1146,16 @@ 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"
@ -1147,7 +1226,7 @@ dependencies = [
 "proc-macro2",
 "quote",
 "rustversion",
- "syn 2.0.76",
+ "syn 2.0.87",
 ]
 [[package]]
@ -1163,9 +1242,9 @@ dependencies = [
 [[package]]
 name = "syn"
-version = "2.0.76"
+version = "2.0.87"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "578e081a14e0cefc3279b0472138c513f37b41a08d5a3cca9b6e4e8ceb6cd525"
+checksum = "25aa4ce346d03a6dcd68dd8b4010bcb74e54e62c90c573f394c46eae99aba32d"
 dependencies = [
 "proc-macro2",
 "quote",
@ -1179,10 +1258,16 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "61c41af27dd6d1e27b1b16b489db798443478cef1f06a660c96db617ba5de3b1"
 [[package]]
-name = "tempfile"
+name = "target-triple"
-version = "3.12.0"
+version = "0.1.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "04cbcdd0c794ebb0d4cf35e88edd2f7d2c4c3e9a5a6dab322839b321c6a87a64"
+checksum = "42a4d50cdb458045afc8131fd91b64904da29548bcb63c7236e0844936c13078"
 [[package]]
 name = "tempfile"
 version = "3.14.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "28cce251fcbc87fac86a866eeb0d6c2d536fc16d06f184bb61aeae11aa4cee0c"
 dependencies = [
 "cfg-if",
 "fastrand",
@ -1193,13 +1278,21 @@ dependencies = [
 [[package]]
 name = "term"
-version = "0.7.0"
+version = "1.0.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c59df8ac95d96ff9bede18eb7300b0fda5e5d8d90960e76f8e14ae765eedbf1f"
+checksum = "4df4175de05129f31b80458c6df371a15e7fc3fd367272e6bf938e5c351c7ea0"
 dependencies = [
- "dirs-next",
+ "home",
- "rustversion",
+ "windows-sys 0.52.0",
- "winapi",
+]
 [[package]]
 name = "termcolor"
 version = "1.4.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "06794f8f6c5c898b3275aebefa6b8a1cb24cd2c6c79397ab15774837a0bc5755"
 dependencies = [
 "winapi-util",
 ]
 [[package]]
@ -1217,33 +1310,80 @@ dependencies = [
 [[package]]
 name = "thiserror"
-version = "1.0.63"
+version = "1.0.69"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c0342370b38b6a11b6cc11d6a805569958d54cfa061a29969c3b5ce2ea405724"
+checksum = "b6aaf5339b578ea85b50e080feb250a3e8ae8cfcdff9a461c9ec2904bc923f52"
 dependencies = [
 "thiserror-impl",
 ]
 [[package]]
 name = "thiserror-impl"
-version = "1.0.63"
+version = "1.0.69"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a4558b58466b9ad7ca0f102865eccc95938dca1a74a856f2b57b6629050da261"
+checksum = "4fee6c4efc90059e10f81e6d42c60a18f76588c3d74cb83a0b242a2b6c7504c1"
 dependencies = [
 "proc-macro2",
 "quote",
- "syn 2.0.76",
+ "syn 2.0.87",
 ]
 [[package]]
-name = "tiny-keccak"
+name = "toml"
-version = "2.0.2"
+version = "0.8.19"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "2c9d3793400a45f954c52e73d068316d76b6f4e36977e3fcebb13a2721e80237"
+checksum = "a1ed1f98e3fdc28d6d910e6737ae6ab1a93bf1985935a1193e68f93eeb68d24e"
 dependencies = [
- "crunchy",
+ "serde",
 "serde_spanned",
 "toml_datetime",
 "toml_edit",
 ]
 [[package]]
 name = "toml_datetime"
 version = "0.6.8"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "0dd7358ecb8fc2f8d014bf86f6f638ce72ba252a2c3a2572f2a795f1d23efb41"
 dependencies = [
 "serde",
 ]
 [[package]]
 name = "toml_edit"
 version = "0.22.22"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "4ae48d6208a266e853d946088ed816055e556cc6028c5e8e2b84d9fa5dd7c7f5"
 dependencies = [
 "indexmap 2.6.0",
 "serde",
 "serde_spanned",
 "toml_datetime",
 "winnow",
 ]
 [[package]]
 name = "trybuild"
 version = "1.0.101"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "8dcd332a5496c026f1e14b7f3d2b7bd98e509660c04239c58b0ba38a12daded4"
 dependencies = [
 "dissimilar",
 "glob",
 "serde",
 "serde_derive",
 "serde_json",
 "target-triple",
 "termcolor",
 "toml",
 ]
 [[package]]
 name = "typenum"
 version = "1.17.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "42ff0bf0c66b8238c6f3b578df37d0b7848e55df8577b3f74f92a69acceeb825"
 [[package]]
 name = "unic-char-property"
 version = "0.9.0"
@ -1298,27 +1438,27 @@ dependencies = [
 [[package]]
 name = "unicode-ident"
-version = "1.0.12"
+version = "1.0.13"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "3354b9ac3fae1ff6755cb6db53683adb661634f67557942dea4facebec0fee4b"
+checksum = "e91b56cd4cadaeb79bbf1a5645f6b4f8dc5bde8834ad5894a8db35fda9efa1fe"
 [[package]]
 name = "unicode-width"
-version = "0.1.13"
+version = "0.1.14"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "0336d538f7abc86d282a4189614dfaa90810dfc2c6f6427eaf88e16311dd225d"
+checksum = "7dd6e30e90baa6f72411720665d41d89b9a3d039dc45b8faea1ddd07f617f6af"
 [[package]]
 name = "unicode-xid"
-version = "0.2.5"
+version = "0.2.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "229730647fbc343e3a80e463c1db7f78f3855d3f3739bee0dda773c9a037c90a"
+checksum = "ebc1c04c71510c7f702b52b7c350734c9ff1295c464a03335b00bb84fc54f853"
 [[package]]
 name = "unicode_names2"
-version = "1.2.2"
+version = "1.3.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "addeebf294df7922a1164f729fb27ebbbcea99cc32b3bf08afab62757f707677"
+checksum = "d1673eca9782c84de5f81b82e4109dcfb3611c8ba0d52930ec4a9478f547b2dd"
 dependencies = [
 "phf",
 "unicode_names2_generator",
@ -1326,9 +1466,9 @@ dependencies = [
 [[package]]
 name = "unicode_names2_generator"
-version = "1.2.2"
+version = "1.3.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f444b8bba042fe3c1251ffaca35c603f2dc2ccc08d595c65a8c4f76f3e8426c0"
+checksum = "b91e5b84611016120197efd7dc93ef76774f4e084cd73c9fb3ea4a86c570c56e"
 dependencies = [
 "getopts",
 "log",
@ -1370,22 +1510,6 @@ version = "0.11.0+wasi-snapshot-preview1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "9c8d87e72b64a3b4db28d11ce29237c246188f4f51057d65a7eab63b7987e423"
 [[package]]
 name = "winapi"
 version = "0.3.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "5c839a674fcd7a98952e593242ea400abe93992746761e38641405d28b00f419"
 dependencies = [
 "winapi-i686-pc-windows-gnu",
 "winapi-x86_64-pc-windows-gnu",
 ]
 [[package]]
 name = "winapi-i686-pc-windows-gnu"
 version = "0.4.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "ac3b87c63620426dd9b991e5ce0329eff545bccbbb34f3be09ff6fb6ab51b7b6"
 [[package]]
 name = "winapi-util"
 version = "0.1.9"
@ -1395,12 +1519,6 @@ dependencies = [
 "windows-sys 0.59.0",
 ]
 [[package]]
 name = "winapi-x86_64-pc-windows-gnu"
 version = "0.4.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "712e227841d057c1ee1cd2fb22fa7e5a5461ae8e48fa2ca79ec42cfc1931183f"
 [[package]]
 name = "windows-sys"
 version = "0.52.0"
@ -1483,6 +1601,15 @@ version = "0.52.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "589f6da84c646204747d1270a2a5661ea66ed1cced2631d546fdfb155959f9ec"
 [[package]]
 name = "winnow"
 version = "0.6.20"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "36c1fec1a2bb5866f07c25f68c26e565c4c200aebb96d7e55710c19d3e8ac49b"
 dependencies = [
 "memchr",
 ]
 [[package]]
 name = "yaml-rust"
 version = "0.4.5"
@ -1510,5 +1637,5 @@ checksum = "fa4f8080344d4671fb4e831a13ad1e68092748387dfc4f55e356242fae12ce3e"
 dependencies = [
 "proc-macro2",
 "quote",
- "syn 2.0.76",
+ "syn 2.0.87",
 ]
--- a/Cargo.toml
+++ b/Cargo.toml
@ -4,6 +4,7 @@ members = [
  "nac3ast",
  "nac3parser",
  "nac3core",
  "nac3core/nac3core_derive",
  "nac3standalone",
  "nac3artiq",
  "runkernel",
--- a/flake.lock
+++ b/flake.lock
@ -2,11 +2,11 @@
  "nodes": {
    "nixpkgs": {
      "locked": {
-        "lastModified": 1723637854,
+        "lastModified": 1731319897,
-        "narHash": "sha256-med8+5DSWa2UnOqtdICndjDAEjxr5D7zaIiK4pn0Q7c=",
+        "narHash": "sha256-PbABj4tnbWFMfBp6OcUK5iGy1QY+/Z96ZcLpooIbuEI=",
        "owner": "NixOS",
        "repo": "nixpkgs",
-        "rev": "c3aa7b8938b17aebd2deecf7be0636000d62a2b9",
+        "rev": "dc460ec76cbff0e66e269457d7b728432263166c",
        "type": "github"
      },
      "original": {
--- a/flake.nix
+++ b/flake.nix
@ -107,18 +107,18 @@
            (pkgs.fetchFromGitHub {
              owner = "m-labs";
              repo = "sipyco";
-              rev = "939f84f9b5eef7efbf7423c735d1834783b6140e";
+              rev = "094a6cd63ffa980ef63698920170e50dc9ba77fd";
-              sha256 = "sha256-15Nun4EY35j+6SPZkjzZtyH/ncxLS60KuGJjFh5kSTc=";
+              sha256 = "sha256-PPnAyDedUQ7Og/Cby9x5OT9wMkNGTP8GS53V6N/dk4w=";
            })
            (pkgs.fetchFromGitHub {
              owner = "m-labs";
              repo = "artiq";
-              rev = "923ca3377d42c815f979983134ec549dc39d3ca0";
+              rev = "28c9de3e251daa89a8c9fd79d5ab64a3ec03bac6";
-              sha256 = "sha256-oJoEeNEeNFSUyh6jXG8Tzp6qHVikeHS0CzfE+mODPgw=";
+              sha256 = "sha256-vAvpbHc5B+1wtG8zqN7j9dQE1ON+i22v+uqA+tw6Gak=";
            })
          ];
          buildInputs = [
-            (python3-mimalloc.withPackages(ps: [ ps.numpy ps.scipy ps.jsonschema ps.lmdb nac3artiq-instrumented ]))
+            (python3-mimalloc.withPackages(ps: [ ps.numpy ps.scipy ps.jsonschema ps.lmdb ps.platformdirs nac3artiq-instrumented ]))
            pkgs.llvmPackages_14.llvm.out
          ];
          phases = [ "buildPhase" "installPhase" ];
--- a/nac3artiq/Cargo.toml
+++ b/nac3artiq/Cargo.toml
@ -12,16 +12,10 @@ crate-type = ["cdylib"]
 itertools = "0.13"
 pyo3 = { version = "0.21", features = ["extension-module", "gil-refs"] }
 parking_lot = "0.12"
-tempfile = "3.10"
+tempfile = "3.13"
 nac3parser = { path = "../nac3parser" }
 nac3core = { path = "../nac3core" }
 nac3ld = { path = "../nac3ld" }
 [dependencies.inkwell]
 version = "0.4"
 default-features = false
 features = ["llvm14-0", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]
 [features]
 init-llvm-profile = []
 no-escape-analysis = ["nac3core/no-escape-analysis"]
--- a/nac3artiq/demo/min_artiq.py
+++ b/nac3artiq/demo/min_artiq.py
@ -112,10 +112,15 @@ def extern(function):
    register_function(function)
    return function
-def rpc(function):
+
-    """Decorates a function declaration defined by the core device runtime."""
+def rpc(arg=None, flags={}):
-    register_function(function)
+    """Decorates a function or method to be executed on the host interpreter."""
-    return function
+    if arg is None:
        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."""
@ -201,7 +206,7 @@ class Core:
        embedding = EmbeddingMap()
        if allow_registration:
-            compiler.analyze(registered_functions, registered_classes)
+            compiler.analyze(registered_functions, registered_classes, set())
            allow_registration = False
        if hasattr(method, "__self__"):
--- a/nac3artiq/src/codegen.rs
+++ b/nac3artiq/src/codegen.rs
@ -1,39 +1,3 @@
 use nac3core::{
    codegen::{
        classes::{
            ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayType,
            NDArrayValue, ProxyType, ProxyValue, RangeValue, UntypedArrayLikeAccessor,
        },
        expr::{destructure_range, gen_call},
        irrt::call_ndarray_calc_size,
        llvm_intrinsics::{call_int_smax, call_memcpy_generic, call_stackrestore, call_stacksave},
        stmt::{gen_block, gen_for_callback_incrementing, gen_if_callback, gen_with},
        CodeGenContext, CodeGenerator,
    },
    symbol_resolver::ValueEnum,
    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId, GenCall},
    typecheck::typedef::{iter_type_vars, FunSignature, FuncArg, Type, TypeEnum, VarMap},
 };
 use nac3parser::ast::{Expr, ExprKind, Located, Stmt, StmtKind, StrRef};
 use inkwell::{
    context::Context,
    module::Linkage,
    types::{BasicType, IntType},
    values::{BasicValueEnum, PointerValue, StructValue},
    AddressSpace, IntPredicate, OptimizationLevel,
 };
 use pyo3::{
    types::{PyDict, PyList},
    PyObject, PyResult, Python,
 };
 use crate::{symbol_resolver::InnerResolver, timeline::TimeFns};
 use inkwell::values::IntValue;
 use itertools::Itertools;
 use std::{
    collections::{hash_map::DefaultHasher, HashMap},
    hash::{Hash, Hasher},
@ -42,6 +6,40 @@ use std::{
    sync::Arc,
 };
 use itertools::Itertools;
 use pyo3::{
    types::{PyDict, PyList},
    PyObject, PyResult, Python,
 };
 use nac3core::{
    codegen::{
        expr::{destructure_range, gen_call},
        irrt::call_ndarray_calc_size,
        llvm_intrinsics::{call_int_smax, call_memcpy_generic, call_stackrestore, call_stacksave},
        stmt::{gen_block, gen_for_callback_incrementing, gen_if_callback, gen_with},
        types::{NDArrayType, ProxyType},
        values::{
            ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue, ProxyValue,
            RangeValue, UntypedArrayLikeAccessor,
        },
        CodeGenContext, CodeGenerator,
    },
    inkwell::{
        context::Context,
        module::Linkage,
        types::{BasicType, IntType},
        values::{BasicValueEnum, IntValue, PointerValue, StructValue},
        AddressSpace, IntPredicate, OptimizationLevel,
    },
    nac3parser::ast::{Expr, ExprKind, Located, Stmt, StmtKind, StrRef},
    symbol_resolver::ValueEnum,
    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId, GenCall},
    typecheck::typedef::{iter_type_vars, FunSignature, FuncArg, Type, TypeEnum, VarMap},
 };
 use super::{symbol_resolver::InnerResolver, timeline::TimeFns};
 /// The parallelism mode within a block.
 #[derive(Copy, Clone, Eq, PartialEq)]
 enum ParallelMode {
@ -461,9 +459,9 @@ fn format_rpc_arg<'ctx>(
            let llvm_usize = generator.get_size_type(ctx.ctx);
            let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, arg_ty);
-            let llvm_arg_ty =
+            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-                NDArrayType::new(generator, ctx.ctx, ctx.get_llvm_type(generator, elem_ty));
+            let llvm_arg_ty = NDArrayType::new(generator, ctx.ctx, llvm_elem_ty);
-            let llvm_arg = NDArrayValue::from_ptr_val(arg.into_pointer_value(), llvm_usize, None);
+            let llvm_arg = llvm_arg_ty.map_value(arg.into_pointer_value(), None);
            let llvm_usize_sizeof = ctx
                .builder
@ -472,7 +470,7 @@ fn format_rpc_arg<'ctx>(
            let llvm_pdata_sizeof = ctx
                .builder
                .build_int_truncate_or_bit_cast(
-                    llvm_arg_ty.element_type().ptr_type(AddressSpace::default()).size_of(),
+                    llvm_elem_ty.ptr_type(AddressSpace::default()).size_of(),
                    llvm_usize,
                    "",
                )
@ -500,7 +498,7 @@ fn format_rpc_arg<'ctx>(
            call_memcpy_generic(
                ctx,
                pbuffer_dims_begin,
-                llvm_arg.dim_sizes().base_ptr(ctx, generator),
+                llvm_arg.shape().base_ptr(ctx, generator),
                dims_buf_sz,
                llvm_i1.const_zero(),
            );
@ -515,7 +513,7 @@ fn format_rpc_arg<'ctx>(
            ctx.builder.build_store(arg_slot, arg).unwrap();
            ctx.builder
-                .build_bitcast(arg_slot, llvm_pi8, "rpc.arg")
+                .build_bit_cast(arg_slot, llvm_pi8, "rpc.arg")
                .map(BasicValueEnum::into_pointer_value)
                .unwrap()
        }
@ -614,7 +612,7 @@ fn format_rpc_ret<'ctx>(
            // Set `ndarray.ndims`
            ndarray.store_ndims(ctx, generator, llvm_usize.const_int(ndims, false));
            // Allocate `ndarray.shape` [size_t; ndims]
-            ndarray.create_dim_sizes(ctx, llvm_usize, ndarray.load_ndims(ctx));
+            ndarray.create_shape(ctx, llvm_usize, ndarray.load_ndims(ctx));
            /*
                ndarray now:
@ -630,7 +628,7 @@ fn format_rpc_ret<'ctx>(
            let llvm_pdata_sizeof = ctx
                .builder
                .build_int_truncate_or_bit_cast(
-                    llvm_ret_ty.element_type().size_of().unwrap(),
+                    llvm_elem_ty.ptr_type(AddressSpace::default()).size_of(),
                    llvm_usize,
                    "",
                )
@ -662,7 +660,7 @@ fn format_rpc_ret<'ctx>(
                .unwrap();
            let buffer = ctx
                .builder
-                .build_bitcast(buffer, llvm_pi8, "")
+                .build_bit_cast(buffer, llvm_pi8, "")
                .map(BasicValueEnum::into_pointer_value)
                .unwrap();
            let buffer = ArraySliceValue::from_ptr_val(buffer, buffer_size, None);
@ -704,7 +702,7 @@ fn format_rpc_ret<'ctx>(
            call_memcpy_generic(
                ctx,
-                ndarray.dim_sizes().base_ptr(ctx, generator),
+                ndarray.shape().base_ptr(ctx, generator),
                pbuffer_dims,
                sizeof_dims,
                llvm_i1.const_zero(),
@ -716,7 +714,7 @@ fn format_rpc_ret<'ctx>(
            // `ndarray.shape` must be initialized beforehand in this implementation
            //   (for ndarray.create_data() to know how many elements to allocate)
            let num_elements =
-                call_ndarray_calc_size(generator, ctx, &ndarray.dim_sizes(), (None, None));
+                call_ndarray_calc_size(generator, ctx, &ndarray.shape(), (None, None));
            // debug_assert(nelems * sizeof(T) >= ndarray_nbytes)
            if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
@ -785,7 +783,7 @@ fn format_rpc_ret<'ctx>(
        _ => {
            let slot = ctx.builder.build_alloca(llvm_ret_ty, "rpc.ret.slot").unwrap();
-            let slotgen = ctx.builder.build_bitcast(slot, llvm_pi8, "rpc.ret.ptr").unwrap();
+            let slotgen = ctx.builder.build_bit_cast(slot, llvm_pi8, "rpc.ret.ptr").unwrap();
            ctx.builder.build_unconditional_branch(head_bb).unwrap();
            ctx.builder.position_at_end(head_bb);
@ -806,7 +804,7 @@ fn format_rpc_ret<'ctx>(
            let alloc_ptr =
                ctx.builder.build_array_alloca(llvm_pi8, alloc_size, "rpc.alloc").unwrap();
            let alloc_ptr =
-                ctx.builder.build_bitcast(alloc_ptr, llvm_pi8, "rpc.alloc.ptr").unwrap();
+                ctx.builder.build_bit_cast(alloc_ptr, llvm_pi8, "rpc.alloc.ptr").unwrap();
            phi.add_incoming(&[(&alloc_ptr, alloc_bb)]);
            ctx.builder.build_unconditional_branch(head_bb).unwrap();
@ -824,6 +822,7 @@ fn rpc_codegen_callback_fn<'ctx>(
    fun: (&FunSignature, DefinitionId),
    args: Vec<(Option<StrRef>, ValueEnum<'ctx>)>,
    generator: &mut dyn CodeGenerator,
    is_async: bool,
 ) -> Result<Option<BasicValueEnum<'ctx>>, String> {
    let int8 = ctx.ctx.i8_type();
    let int32 = ctx.ctx.i32_type();
@ -932,6 +931,29 @@ fn rpc_codegen_callback_fn<'ctx>(
    }
    // call
    if is_async {
        let rpc_send_async = ctx.module.get_function("rpc_send_async").unwrap_or_else(|| {
            ctx.module.add_function(
                "rpc_send_async",
                ctx.ctx.void_type().fn_type(
                    &[
                        int32.into(),
                        tag_ptr_type.ptr_type(AddressSpace::default()).into(),
                        ptr_type.ptr_type(AddressSpace::default()).into(),
                    ],
                    false,
                ),
                None,
            )
        });
        ctx.builder
            .build_call(
                rpc_send_async,
                &[service_id.into(), tag_ptr.into(), args_ptr.into()],
                "rpc.send",
            )
            .unwrap();
    } else {
        let rpc_send = ctx.module.get_function("rpc_send").unwrap_or_else(|| {
            ctx.module.add_function(
                "rpc_send",
@ -949,10 +971,15 @@ fn rpc_codegen_callback_fn<'ctx>(
        ctx.builder
            .build_call(rpc_send, &[service_id.into(), tag_ptr.into(), args_ptr.into()], "rpc.send")
            .unwrap();
    }
    // reclaim stack space used by arguments
    call_stackrestore(ctx, stackptr);
    if is_async {
        // async RPCs do not return any values
        Ok(None)
    } else {
        let result = format_rpc_ret(generator, ctx, fun.0.ret);
        if !result.is_some_and(|res| res.get_type().is_pointer_type()) {
@ -962,12 +989,14 @@ fn rpc_codegen_callback_fn<'ctx>(
        Ok(result)
    }
 }
-pub fn attributes_writeback(
+pub fn attributes_writeback<'ctx>(
-    ctx: &mut CodeGenContext<'_, '_>,
+    ctx: &mut CodeGenContext<'ctx, '_>,
    generator: &mut dyn CodeGenerator,
    inner_resolver: &InnerResolver,
    host_attributes: &PyObject,
    return_obj: Option<(Type, ValueEnum<'ctx>)>,
 ) -> Result<(), String> {
    Python::with_gil(|py| -> PyResult<Result<(), String>> {
        let host_attributes: &PyList = host_attributes.downcast(py)?;
@ -977,6 +1006,11 @@ pub fn attributes_writeback(
        let zero = int32.const_zero();
        let mut values = Vec::new();
        let mut scratch_buffer = Vec::new();
        if let Some((ty, obj)) = return_obj {
            values.push((ty, obj.to_basic_value_enum(ctx, generator, ty).unwrap()));
        }
        for val in (*globals).values() {
            let val = val.as_ref(py);
            let ty = inner_resolver.get_obj_type(
@ -1055,7 +1089,7 @@ pub fn attributes_writeback(
        let args: Vec<_> =
            values.into_iter().map(|(_, val)| (None, ValueEnum::Dynamic(val))).collect();
        if let Err(e) =
-            rpc_codegen_callback_fn(ctx, None, (&fun, PrimDef::Int32.id()), args, generator)
+            rpc_codegen_callback_fn(ctx, None, (&fun, PrimDef::Int32.id()), args, generator, true)
        {
            return Ok(Err(e));
        }
@ -1065,9 +1099,9 @@ pub fn attributes_writeback(
    Ok(())
 }
-pub fn rpc_codegen_callback() -> Arc<GenCall> {
+pub fn rpc_codegen_callback(is_async: bool) -> Arc<GenCall> {
-    Arc::new(GenCall::new(Box::new(|ctx, obj, fun, args, generator| {
+    Arc::new(GenCall::new(Box::new(move |ctx, obj, fun, args, generator| {
-        rpc_codegen_callback_fn(ctx, obj, fun, args, generator)
+        rpc_codegen_callback_fn(ctx, obj, fun, args, generator, is_async)
    })))
 }
@ -1281,7 +1315,8 @@ fn polymorphic_print<'ctx>(
                fmt.push('[');
                flush(ctx, generator, &mut fmt, &mut args);
-                let val = ListValue::from_ptr_val(value.into_pointer_value(), llvm_usize, None);
+                let val =
                    ListValue::from_pointer_value(value.into_pointer_value(), llvm_usize, None);
                let len = val.load_size(ctx, None);
                let last =
                    ctx.builder.build_int_sub(len, llvm_usize.const_int(1, false), "").unwrap();
@ -1333,12 +1368,18 @@ fn polymorphic_print<'ctx>(
            TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
                let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
                let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
                fmt.push_str("array([");
                flush(ctx, generator, &mut fmt, &mut args);
-                let val = NDArrayValue::from_ptr_val(value.into_pointer_value(), llvm_usize, None);
+                let val = NDArrayValue::from_pointer_value(
-                let len = call_ndarray_calc_size(generator, ctx, &val.dim_sizes(), (None, None));
+                    value.into_pointer_value(),
                    llvm_elem_ty,
                    llvm_usize,
                    None,
                );
                let len = call_ndarray_calc_size(generator, ctx, &val.shape(), (None, None));
                let last =
                    ctx.builder.build_int_sub(len, llvm_usize.const_int(1, false), "").unwrap();
@ -1391,7 +1432,7 @@ fn polymorphic_print<'ctx>(
                fmt.push_str("range(");
                flush(ctx, generator, &mut fmt, &mut args);
-                let val = RangeValue::from_ptr_val(value.into_pointer_value(), None);
+                let val = RangeValue::from_pointer_value(value.into_pointer_value(), None);
                let (start, stop, step) = destructure_range(ctx, val);
--- a/nac3artiq/src/lib.rs
+++ b/nac3artiq/src/lib.rs
@ -1,10 +1,4 @@
-#![deny(
+#![deny(future_incompatible, let_underscore, nonstandard_style, clippy::all)]
    future_incompatible,
    let_underscore,
    nonstandard_style,
    rust_2024_compatibility,
    clippy::all
 )]
 #![warn(clippy::pedantic)]
 #![allow(
    unsafe_op_in_unsafe_fn,
@ -16,64 +10,65 @@
    clippy::wildcard_imports
 )]
-use std::collections::{HashMap, HashSet};
+use std::{
-use std::fs;
+    collections::{HashMap, HashSet},
-use std::io::Write;
+    fs,
-use std::process::Command;
+    io::Write,
-use std::rc::Rc;
+    process::Command,
-use std::sync::Arc;
+    rc::Rc,
    sync::Arc,
 };
-use inkwell::{
+use itertools::Itertools;
 use parking_lot::{Mutex, RwLock};
 use pyo3::{
    create_exception, exceptions,
    prelude::*,
    types::{PyBytes, PyDict, PyNone, PySet},
 };
 use tempfile::{self, TempDir};
 use nac3core::{
    codegen::{
        concrete_type::ConcreteTypeStore, gen_func_impl, irrt::load_irrt, CodeGenLLVMOptions,
        CodeGenTargetMachineOptions, CodeGenTask, CodeGenerator, WithCall, WorkerRegistry,
    },
    inkwell::{
        context::Context,
        memory_buffer::MemoryBuffer,
-    module::{Linkage, Module},
+        module::{FlagBehavior, Linkage, Module},
        passes::PassBuilderOptions,
        support::is_multithreaded,
        targets::*,
        OptimizationLevel,
-};
+    },
-use itertools::Itertools;
+    nac3parser::{
-use nac3core::codegen::{gen_func_impl, CodeGenLLVMOptions, CodeGenTargetMachineOptions};
+        ast::{Constant, ExprKind, Located, Stmt, StmtKind, StrRef},
 use nac3core::toplevel::builtins::get_exn_constructor;
 use nac3core::typecheck::typedef::{into_var_map, TypeEnum, Unifier, VarMap};
 use nac3parser::{
    ast::{ExprKind, Stmt, StmtKind, StrRef},
        parser::parse_program,
-};
+    },
 use pyo3::create_exception;
 use pyo3::prelude::*;
 use pyo3::{exceptions, types::PyBytes, types::PyDict, types::PySet};
 use parking_lot::{Mutex, RwLock};
 use nac3core::{
    codegen::irrt::load_irrt,
    codegen::{concrete_type::ConcreteTypeStore, CodeGenTask, WithCall, WorkerRegistry},
    symbol_resolver::SymbolResolver,
    toplevel::{
        builtins::get_exn_constructor,
        composer::{BuiltinFuncCreator, BuiltinFuncSpec, ComposerConfig, TopLevelComposer},
        DefinitionId, GenCall, TopLevelDef,
    },
-    typecheck::typedef::{FunSignature, FuncArg},
+    typecheck::{
-    typecheck::{type_inferencer::PrimitiveStore, typedef::Type},
+        type_inferencer::PrimitiveStore,
        typedef::{into_var_map, FunSignature, FuncArg, Type, TypeEnum, Unifier, VarMap},
    },
 };
 use nac3ld::Linker;
-use crate::{
+use codegen::{
    codegen::{
    attributes_writeback, gen_core_log, gen_rtio_log, rpc_codegen_callback, ArtiqCodeGenerator,
    },
    symbol_resolver::{DeferredEvaluationStore, InnerResolver, PythonHelper, Resolver},
 };
-use tempfile::{self, TempDir};
+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,
@ -147,14 +142,32 @@ impl Nac3 {
        module: &PyObject,
        registered_class_ids: &HashSet<u64>,
    ) -> PyResult<()> {
-        let (module_name, source_file) = Python::with_gil(|py| -> PyResult<(String, String)> {
+        let (module_name, source_file, source) =
            Python::with_gil(|py| -> PyResult<(String, String, String)> {
                let module: &PyAny = module.extract(py)?;
-            Ok((module.getattr("__name__")?.extract()?, module.getattr("__file__")?.extract()?))
+                let source_file = module.getattr("__file__");
                let (source_file, source) = if let Ok(source_file) = source_file {
                    let source_file = source_file.extract()?;
                    (
                        source_file,
                        fs::read_to_string(source_file).map_err(|e| {
                            exceptions::PyIOError::new_err(format!(
                                "failed to read input file: {e}"
                            ))
                        })?,
                    )
                } else {
                    // kernels submitted by content have no file
                    // but still can provide source by StringLoader
                    let get_src_fn = module
                        .getattr("__loader__")?
                        .extract::<PyObject>()?
                        .getattr(py, "get_source")?;
                    ("<expcontent>", get_src_fn.call1(py, (PyNone::get(py),))?.extract(py)?)
                };
                Ok((module.getattr("__name__")?.extract()?, source_file.to_string(), source))
            })?;
        let source = fs::read_to_string(&source_file).map_err(|e| {
            exceptions::PyIOError::new_err(format!("failed to read input file: {e}"))
        })?;
        let parser_result = parse_program(&source, source_file.into())
            .map_err(|e| exceptions::PySyntaxError::new_err(format!("parse error: {e}")))?;
@ -194,10 +207,8 @@ impl Nac3 {
                    body.retain(|stmt| {
                        if let StmtKind::FunctionDef { ref decorator_list, .. } = stmt.node {
                            decorator_list.iter().any(|decorator| {
-                                if let ExprKind::Name { id, .. } = decorator.node {
+                                if let Some(id) = decorator_id_string(decorator) {
-                                    id.to_string() == "kernel"
+                                    id == "kernel" || id == "portable" || id == "rpc"
                                        || id.to_string() == "portable"
                                        || id.to_string() == "rpc"
                                } else {
                                    false
                                }
@ -210,9 +221,8 @@ impl Nac3 {
                }
                StmtKind::FunctionDef { ref decorator_list, .. } => {
                    decorator_list.iter().any(|decorator| {
-                        if let ExprKind::Name { id, .. } = decorator.node {
+                        if let Some(id) = decorator_id_string(decorator) {
-                            let id = id.to_string();
+                            id == "extern" || id == "kernel" || id == "portable" || id == "rpc"
                            id == "extern" || id == "portable" || id == "kernel" || id == "rpc"
                        } else {
                            false
                        }
@ -478,9 +488,25 @@ impl Nac3 {
            match &stmt.node {
                StmtKind::FunctionDef { decorator_list, .. } => {
-                    if decorator_list.iter().any(|decorator| matches!(decorator.node, ExprKind::Name { id, .. } if id == "rpc".into())) {
+                    if decorator_list
-                        store_fun.call1(py, (def_id.0.into_py(py), module.getattr(py, name.to_string().as_str()).unwrap())).unwrap();
+                        .iter()
-                        rpc_ids.push((None, def_id));
+                        .any(|decorator| decorator_id_string(decorator) == Some("rpc".to_string()))
                    {
                        store_fun
                            .call1(
                                py,
                                (
                                    def_id.0.into_py(py),
                                    module.getattr(py, name.to_string().as_str()).unwrap(),
                                ),
                            )
                            .unwrap();
                        let is_async = decorator_list.iter().any(|decorator| {
                            decorator_get_flags(decorator)
                                .iter()
                                .any(|constant| *constant == Constant::Str("async".into()))
                        });
                        rpc_ids.push((None, def_id, is_async));
                    }
                }
                StmtKind::ClassDef { name, body, .. } => {
@ -488,19 +514,26 @@ 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| matches!(decorator.node, ExprKind::Name { id, .. } if id == "rpc".into())) {
+                            if decorator_list.iter().any(|decorator| {
                                decorator_id_string(decorator) == Some("rpc".to_string())
                            }) {
                                let is_async = decorator_list.iter().any(|decorator| {
                                    decorator_get_flags(decorator)
                                        .iter()
                                        .any(|constant| *constant == Constant::Str("async".into()))
                                });
                                if 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));
+                                rpc_ids.push((Some((class_obj.clone(), *name)), def_id, is_async));
                            }
                        }
                    }
                }
-                _ => ()
+                _ => (),
            }
            let id = *name_to_pyid.get(&name).unwrap();
@ -556,7 +589,7 @@ impl Nac3 {
            .unwrap();
        // Process IRRT
-        let context = inkwell::context::Context::create();
+        let context = Context::create();
        let irrt = load_irrt(&context, resolver.as_ref());
        let fun_signature =
@ -596,13 +629,12 @@ 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) in &rpc_ids {
+            for (class_data, id, is_async) in &rpc_ids {
                let mut def = defs[id.0].write();
                match &mut *def {
                    TopLevelDef::Function { codegen_callback, .. } => {
-                        *codegen_callback = Some(rpc_codegen.clone());
+                        *codegen_callback = Some(rpc_codegen_callback(*is_async));
                    }
                    TopLevelDef::Class { methods, .. } => {
                        let (class_def, method_name) = class_data.as_ref().unwrap();
@ -613,7 +645,7 @@ impl Nac3 {
                            if let TopLevelDef::Function { codegen_callback, .. } =
                                &mut *defs[id.0].write()
                            {
-                                *codegen_callback = Some(rpc_codegen.clone());
+                                *codegen_callback = Some(rpc_codegen_callback(*is_async));
                                store_fun
                                    .call1(
                                        py,
@ -628,6 +660,11 @@ impl Nac3 {
                            }
                        }
                    }
                    TopLevelDef::Variable { .. } => {
                        return Err(CompileError::new_err(String::from(
                            "Unsupported @rpc annotation on global variable",
                        )))
                    }
                }
            }
        }
@ -648,33 +685,12 @@ impl Nac3 {
        let task = CodeGenTask {
            subst: Vec::default(),
            symbol_name: "__modinit__".to_string(),
            body: instance.body,
            signature,
            resolver: resolver.clone(),
            store,
            unifier_index: instance.unifier_id,
            calls: instance.calls,
            id: 0,
        };
        let mut store = ConcreteTypeStore::new();
        let mut cache = HashMap::new();
        let signature = store.from_signature(
            &mut composer.unifier,
            &self.primitive,
            &fun_signature,
            &mut cache,
        );
        let signature = store.add_cty(signature);
        let attributes_writeback_task = CodeGenTask {
            subst: Vec::default(),
            symbol_name: "attributes_writeback".to_string(),
            body: Arc::new(Vec::default()),
            signature,
            resolver,
            store,
            unifier_index: instance.unifier_id,
-            calls: Arc::new(HashMap::default()),
+            calls: instance.calls,
            id: 0,
        };
@ -687,7 +703,7 @@ impl Nac3 {
            let buffer = buffer.as_slice().into();
            membuffer.lock().push(buffer);
        })));
-        let size_t = Context::create()
+        let size_t = context
            .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 };
@ -698,19 +714,27 @@ impl Nac3 {
            .collect();
        let membuffer = membuffers.clone();
        let mut has_return = false;
        py.allow_threads(|| {
            let (registry, handles) =
                WorkerRegistry::create_workers(threads, top_level.clone(), &self.llvm_options, &f);
            registry.add_task(task);
            registry.wait_tasks_complete(handles);
-            let mut generator =
+            let mut generator = ArtiqCodeGenerator::new("main".to_string(), size_t, self.time_fns);
-                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("main");
            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());
            module.set_triple(&target_machine.get_triple());
            module.add_basic_value_flag(
                "Debug Info Version",
                FlagBehavior::Warning,
                context.i32_type().const_int(3, false),
            );
            module.add_basic_value_flag(
                "Dwarf Version",
                FlagBehavior::Warning,
                context.i32_type().const_int(4, false),
            );
            let builder = context.create_builder();
            let (_, module, _) = gen_func_impl(
                &context,
@ -718,9 +742,27 @@ impl Nac3 {
                &registry,
                builder,
                module,
-                attributes_writeback_task,
+                task,
                |generator, ctx| {
-                    attributes_writeback(ctx, generator, inner_resolver.as_ref(), &host_attributes)
+                    assert_eq!(instance.body.len(), 1, "toplevel module should have 1 statement");
                    let StmtKind::Expr { value: ref expr, .. } = instance.body[0].node else {
                        unreachable!("toplevel statement must be an expression")
                    };
                    let ExprKind::Call { .. } = expr.node else {
                        unreachable!("toplevel expression must be a function call")
                    };
                    let return_obj =
                        generator.gen_expr(ctx, expr)?.map(|value| (expr.custom.unwrap(), value));
                    has_return = return_obj.is_some();
                    registry.wait_tasks_complete(handles);
                    attributes_writeback(
                        ctx,
                        generator,
                        inner_resolver.as_ref(),
                        &host_attributes,
                        return_obj,
                    )
                },
            )
            .unwrap();
@ -729,35 +771,23 @@ impl Nac3 {
            membuffer.lock().push(buffer);
        });
        embedding_map.setattr("expects_return", has_return).unwrap();
        // Link all modules into `main`.
        let buffers = membuffers.lock();
        let main = context
-            .create_module_from_ir(MemoryBuffer::create_from_memory_range(&buffers[0], "main"))
+            .create_module_from_ir(MemoryBuffer::create_from_memory_range(
                buffers.last().unwrap(),
                "main",
            ))
            .unwrap();
-        for buffer in buffers.iter().skip(1) {
+        for buffer in buffers.iter().rev().skip(1) {
            let other = context
                .create_module_from_ir(MemoryBuffer::create_from_memory_range(buffer, "main"))
                .unwrap();
            main.link_in_module(other).map_err(|err| CompileError::new_err(err.to_string()))?;
        }
        let builder = context.create_builder();
        let modinit_return = main
            .get_function("__modinit__")
            .unwrap()
            .get_last_basic_block()
            .unwrap()
            .get_terminator()
            .unwrap();
        builder.position_before(&modinit_return);
        builder
            .build_call(
                main.get_function("attributes_writeback").unwrap(),
                &[],
                "attributes_writeback",
            )
            .unwrap();
        main.link_in_module(irrt).map_err(|err| CompileError::new_err(err.to_string()))?;
        let mut function_iter = main.get_first_function();
@ -844,6 +874,41 @@ 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(),
@ -1025,7 +1090,12 @@ impl Nac3 {
        })
    }
-    fn analyze(&mut self, functions: &PySet, classes: &PySet) -> PyResult<()> {
+    fn analyze(
        &mut self,
        functions: &PySet,
        classes: &PySet,
        content_modules: &PySet,
    ) -> PyResult<()> {
        let (modules, class_ids) =
            Python::with_gil(|py| -> PyResult<(HashMap<u64, PyObject>, HashSet<u64>)> {
                let mut modules: HashMap<u64, PyObject> = HashMap::new();
@ -1035,14 +1105,22 @@ impl Nac3 {
                let getmodule_fn = PyModule::import(py, "inspect")?.getattr("getmodule")?;
                for function in functions {
-                    let module = getmodule_fn.call1((function,))?.extract()?;
+                    let module: PyObject = getmodule_fn.call1((function,))?.extract()?;
                    if !module.is_none(py) {
                        modules.insert(id_fn.call1((&module,))?.extract()?, module);
                    }
                }
                for class in classes {
-                    let module = getmodule_fn.call1((class,))?.extract()?;
+                    let module: PyObject = getmodule_fn.call1((class,))?.extract()?;
                    if !module.is_none(py) {
                        modules.insert(id_fn.call1((&module,))?.extract()?, module);
                    }
                    class_ids.insert(id_fn.call1((class,))?.extract()?);
                }
                for module in content_modules {
                    let module: PyObject = module.extract()?;
                    modules.insert(id_fn.call1((&module,))?.extract()?, module);
                }
                Ok((modules, class_ids))
            })?;
--- a/nac3artiq/src/symbol_resolver.rs
+++ b/nac3artiq/src/symbol_resolver.rs
@ -1,16 +1,30 @@
-use crate::PrimitivePythonId;
+use std::{
-use inkwell::{
+    collections::{HashMap, HashSet},
    sync::{
        atomic::{AtomicBool, Ordering::Relaxed},
        Arc,
    },
 };
 use itertools::Itertools;
 use parking_lot::RwLock;
 use pyo3::{
    types::{PyDict, PyTuple},
    PyAny, PyObject, PyResult, Python,
 };
 use nac3core::{
    codegen::{
        types::{NDArrayType, ProxyType},
        CodeGenContext, CodeGenerator,
    },
    inkwell::{
        module::Linkage,
        types::{BasicType, BasicTypeEnum},
        values::BasicValueEnum,
        AddressSpace,
 };
 use itertools::Itertools;
 use nac3core::{
    codegen::{
        classes::{NDArrayType, ProxyType},
        CodeGenContext, CodeGenerator,
    },
    nac3parser::ast::{self, StrRef},
    symbol_resolver::{StaticValue, SymbolResolver, SymbolValue, ValueEnum},
    toplevel::{
        helper::PrimDef,
@ -22,19 +36,8 @@ use nac3core::{
        typedef::{into_var_map, iter_type_vars, Type, TypeEnum, TypeVar, Unifier, VarMap},
    },
 };
-use nac3parser::ast::{self, StrRef};
+
-use parking_lot::RwLock;
+use super::PrimitivePythonId;
 use pyo3::{
    types::{PyDict, PyTuple},
    PyAny, PyObject, PyResult, Python,
 };
 use std::{
    collections::{HashMap, HashSet},
    sync::{
        atomic::{AtomicBool, Ordering::Relaxed},
        Arc,
    },
 };
 pub enum PrimitiveValue {
    I32(i32),
@ -1093,7 +1096,7 @@ impl InnerResolver {
                if self.global_value_ids.read().contains_key(&id) {
                    let global = ctx.module.get_global(&id_str).unwrap_or_else(|| {
                        ctx.module.add_global(
-                            ndarray_llvm_ty.as_underlying_type(),
+                            ndarray_llvm_ty.as_base_type().get_element_type().into_struct_type(),
                            Some(AddressSpace::default()),
                            &id_str,
                        )
@ -1187,7 +1190,11 @@ impl InnerResolver {
            data_global.set_initializer(&data);
            // create a global for the ndarray object and initialize it
-            let value = ndarray_llvm_ty.as_underlying_type().const_named_struct(&[
+            let value = ndarray_llvm_ty
                .as_base_type()
                .get_element_type()
                .into_struct_type()
                .const_named_struct(&[
                    llvm_usize.const_int(ndarray_ndims, false).into(),
                    shape_global
                        .as_pointer_value()
@ -1200,7 +1207,7 @@ impl InnerResolver {
                ]);
            let ndarray = ctx.module.add_global(
-                ndarray_llvm_ty.as_underlying_type(),
+                ndarray_llvm_ty.as_base_type().get_element_type().into_struct_type(),
                Some(AddressSpace::default()),
                &id_str,
            );
@ -1467,6 +1474,7 @@ impl SymbolResolver for Resolver {
        &self,
        id: StrRef,
        _: &mut CodeGenContext<'ctx, '_>,
        _: &mut dyn CodeGenerator,
    ) -> Option<ValueEnum<'ctx>> {
        let sym_value = {
            let id_to_val = self.0.id_to_pyval.read();
--- a/nac3artiq/src/timeline.rs
+++ b/nac3artiq/src/timeline.rs
@ -1,9 +1,12 @@
-use inkwell::{
+use itertools::Either;
 use nac3core::{
    codegen::CodeGenContext,
    inkwell::{
        values::{BasicValueEnum, CallSiteValue},
        AddressSpace, AtomicOrdering,
    },
 };
 use itertools::Either;
 use nac3core::codegen::CodeGenContext;
 /// Functions for manipulating the timeline.
 pub trait TimeFns {
@ -31,7 +34,7 @@ impl TimeFns for NowPinningTimeFns64 {
            .unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
        let now_hiptr = ctx
            .builder
-            .build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
+            .build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
            .map(BasicValueEnum::into_pointer_value)
            .unwrap();
@ -80,7 +83,7 @@ impl TimeFns for NowPinningTimeFns64 {
            .unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
        let now_hiptr = ctx
            .builder
-            .build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
+            .build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
            .map(BasicValueEnum::into_pointer_value)
            .unwrap();
@ -109,7 +112,7 @@ impl TimeFns for NowPinningTimeFns64 {
            .unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
        let now_hiptr = ctx
            .builder
-            .build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
+            .build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
            .map(BasicValueEnum::into_pointer_value)
            .unwrap();
@ -207,7 +210,7 @@ impl TimeFns for NowPinningTimeFns {
            .unwrap_or_else(|| ctx.module.add_global(i64_type, None, "now"));
        let now_hiptr = ctx
            .builder
-            .build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
+            .build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
            .map(BasicValueEnum::into_pointer_value)
            .unwrap();
@ -258,7 +261,7 @@ impl TimeFns for NowPinningTimeFns {
        let time_lo = ctx.builder.build_int_truncate(time, i32_type, "time.lo").unwrap();
        let now_hiptr = ctx
            .builder
-            .build_bitcast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
+            .build_bit_cast(now, i32_type.ptr_type(AddressSpace::default()), "now.hi.addr")
            .map(BasicValueEnum::into_pointer_value)
            .unwrap();
--- a/nac3ast/Cargo.toml
+++ b/nac3ast/Cargo.toml
@ -10,7 +10,6 @@ constant-optimization = ["fold"]
 fold = []
 [dependencies]
 lazy_static = "1.5"
 parking_lot = "0.12"
 string-interner = "0.17"
 fxhash = "0.2"
--- a/nac3ast/src/ast_gen.rs
+++ b/nac3ast/src/ast_gen.rs
@ -5,14 +5,12 @@ pub use crate::location::Location;
 use fxhash::FxBuildHasher;
 use parking_lot::{Mutex, MutexGuard};
-use std::{cell::RefCell, collections::HashMap, fmt};
+use std::{cell::RefCell, collections::HashMap, fmt, sync::LazyLock};
 use string_interner::{symbol::SymbolU32, DefaultBackend, StringInterner};
 pub type Interner = StringInterner<DefaultBackend, FxBuildHasher>;
-lazy_static! {
+static INTERNER: LazyLock<Mutex<Interner>> =
-    static ref INTERNER: Mutex<Interner> =
+    LazyLock::new(|| Mutex::new(StringInterner::with_hasher(FxBuildHasher::default())));
        Mutex::new(StringInterner::with_hasher(FxBuildHasher::default()));
 }
 thread_local! {
    static LOCAL_INTERNER: RefCell<HashMap<String, StrRef>> = RefCell::default();
--- a/nac3ast/src/lib.rs
+++ b/nac3ast/src/lib.rs
@ -1,10 +1,4 @@
-#![deny(
+#![deny(future_incompatible, let_underscore, nonstandard_style, clippy::all)]
    future_incompatible,
    let_underscore,
    nonstandard_style,
    rust_2024_compatibility,
    clippy::all
 )]
 #![warn(clippy::pedantic)]
 #![allow(
    clippy::missing_errors_doc,
@ -14,9 +8,6 @@
    clippy::wildcard_imports
 )]
 #[macro_use]
 extern crate lazy_static;
 mod ast_gen;
 mod constant;
 #[cfg(feature = "fold")]
--- a/nac3core/Cargo.toml
+++ b/nac3core/Cargo.toml
@ -5,22 +5,25 @@ authors = ["M-Labs"]
 edition = "2021"
 [features]
 default = ["derive"]
 derive = ["dep:nac3core_derive"]
 no-escape-analysis = []
 [dependencies]
 itertools = "0.13"
 crossbeam = "0.8"
-indexmap = "2.2"
+indexmap = "2.6"
 parking_lot = "0.12"
-rayon = "1.8"
+rayon = "1.10"
 nac3core_derive = { path = "nac3core_derive", optional = true }
 nac3parser = { path = "../nac3parser" }
 strum = "0.26"
 strum_macros = "0.26"
 [dependencies.inkwell]
-version = "0.4"
+version = "0.5"
 default-features = false
-features = ["llvm14-0", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]
+features = ["llvm14-0-prefer-dynamic", "target-x86", "target-arm", "target-riscv", "no-libffi-linking"]
 [dev-dependencies]
 test-case = "1.2.0"
--- a/nac3core/build.rs
+++ b/nac3core/build.rs
@ -1,4 +1,3 @@
 use regex::Regex;
 use std::{
    env,
    fs::File,
@ -7,6 +6,8 @@ use std::{
    process::{Command, Stdio},
 };
 use regex::Regex;
 fn main() {
    let out_dir = env::var("OUT_DIR").unwrap();
    let out_dir = Path::new(&out_dir);
@ -55,9 +56,8 @@ fn main() {
    let output = Command::new("clang-irrt")
        .args(flags)
        .output()
-        .map(|o| {
+        .inspect(|o| {
            assert!(o.status.success(), "{}", std::str::from_utf8(&o.stderr).unwrap());
            o
        })
        .unwrap();
--- a/nac3core/irrt/irrt.cpp
+++ b/nac3core/irrt/irrt.cpp
@ -1,15 +1,5 @@
 #include "irrt/exception.hpp"
 #include "irrt/int_types.hpp"
 #include "irrt/list.hpp"
 #include "irrt/math.hpp"
 #include "irrt/ndarray.hpp"
 #include "irrt/range.hpp"
 #include "irrt/slice.hpp"
 #include "irrt/ndarray/basic.hpp"
 #include "irrt/ndarray/def.hpp"
 #include "irrt/ndarray/iter.hpp"
 #include "irrt/ndarray/indexing.hpp"
 #include "irrt/ndarray/array.hpp"
 #include "irrt/ndarray/reshape.hpp"
 #include "irrt/ndarray/broadcast.hpp"
 #include "irrt/ndarray/transpose.hpp"
--- a/nac3core/irrt/irrt/cslice.hpp
+++ b/nac3core/irrt/irrt/cslice.hpp
@ -4,6 +4,6 @@
 template<typename SizeT>
 struct CSlice {
-    uint8_t* base;
+    void* base;
    SizeT len;
 };
--- a/nac3core/irrt/irrt/exception.hpp
+++ b/nac3core/irrt/irrt/exception.hpp
@ -6,7 +6,7 @@
 /**
 * @brief The int type of ARTIQ exception IDs.
 */
-typedef int32_t ExceptionId;
+using ExceptionId = int32_t;
 /*
 * Set of exceptions C++ IRRT can use.
@ -55,14 +55,14 @@ void _raise_exception_helper(ExceptionId id,
                             int64_t param2) {
    Exception<SizeT> e = {
        .id = id,
-        .filename = {.base = reinterpret_cast<uint8_t*>(const_cast<char*>(filename)),
+        .filename = {.base = reinterpret_cast<void*>(const_cast<char*>(filename)),
-                     .len = static_cast<int32_t>(__builtin_strlen(filename))},
+                     .len = static_cast<SizeT>(__builtin_strlen(filename))},
        .line = line,
        .column = 0,
-        .function = {.base = reinterpret_cast<uint8_t*>(const_cast<char*>(function)),
+        .function = {.base = reinterpret_cast<void*>(const_cast<char*>(function)),
-                     .len = static_cast<int32_t>(__builtin_strlen(function))},
+                     .len = static_cast<SizeT>(__builtin_strlen(function))},
-        .msg = {.base = reinterpret_cast<uint8_t*>(const_cast<char*>(msg)),
+        .msg = {.base = reinterpret_cast<void*>(const_cast<char*>(msg)),
-                .len = static_cast<int32_t>(__builtin_strlen(msg))},
+                .len = static_cast<SizeT>(__builtin_strlen(msg))},
    };
    e.params[0] = param0;
    e.params[1] = param1;
@ -70,6 +70,7 @@ void _raise_exception_helper(ExceptionId id,
    __nac3_raise(reinterpret_cast<void*>(&e));
    __builtin_unreachable();
 }
 }  // namespace
 /**
 * @brief Raise an exception with location details (location in the IRRT source files).
@ -82,4 +83,3 @@ void _raise_exception_helper(ExceptionId id,
 */
 #define raise_exception(SizeT, id, msg, param0, param1, param2) \
    _raise_exception_helper<SizeT>(id, __FILE__, __LINE__, __FUNCTION__, msg, param0, param1, param2)
 }  // namespace
--- a/nac3core/irrt/irrt/int_types.hpp
+++ b/nac3core/irrt/irrt/int_types.hpp
@ -1,13 +1,27 @@
 #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
 #pragma clang diagnostic push
 #pragma clang diagnostic ignored "-Wdeprecated-type"
 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);
 #pragma clang diagnostic pop
 #endif
 // NDArray indices are always `uint32_t`.
-using NDIndexInt = uint32_t;
+using NDIndex = uint32_t;
 // The type of an index or a value describing the length of a range/slice is always `int32_t`.
 using SliceIndex = int32_t;
--- a/nac3core/irrt/irrt/list.hpp
+++ b/nac3core/irrt/irrt/list.hpp
@ -2,21 +2,6 @@
 #include "irrt/int_types.hpp"
 #include "irrt/math_util.hpp"
 #include "irrt/slice.hpp"
 namespace {
 /**
 * @brief A list in NAC3.
 *
 * The `items` field is opaque. You must rely on external contexts to
 * know how to interpret it.
 */
 template<typename SizeT>
 struct List {
    uint8_t* items;
    SizeT len;
 };
 }  // namespace
 extern "C" {
 // Handle list assignment and dropping part of the list when
@ -28,12 +13,12 @@ extern "C" {
 SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
                                             SliceIndex dest_end,
                                             SliceIndex dest_step,
-                                             uint8_t* dest_arr,
+                                             void* dest_arr,
                                             SliceIndex dest_arr_len,
                                             SliceIndex src_start,
                                             SliceIndex src_end,
                                             SliceIndex src_step,
-                                             uint8_t* src_arr,
+                                             void* src_arr,
                                             SliceIndex src_arr_len,
                                             const SliceIndex size) {
    /* if dest_arr_len == 0, do nothing since we do not support extending list */
@ -44,11 +29,13 @@ SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
        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);
+            __builtin_memmove(static_cast<uint8_t*>(dest_arr) + dest_start * size,
                              static_cast<uint8_t*>(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,
+            __builtin_memmove(static_cast<uint8_t*>(dest_arr) + (dest_start + src_len) * size,
                              static_cast<uint8_t*>(dest_arr) + (dest_end + 1) * size,
                              (dest_arr_len - dest_end - 1) * size);
        }
        /* shrink size */
@ -59,7 +46,7 @@ SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
                          && !(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));
+        void* tmp = __builtin_alloca(src_arr_len * size);
        __builtin_memcpy(tmp, src_arr, src_arr_len * size);
        src_arr = tmp;
    }
@ -68,20 +55,24 @@ SliceIndex __nac3_list_slice_assign_var_size(SliceIndex 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);
+            __builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind, static_cast<uint8_t*>(src_arr) + src_ind, 1);
        } else if (size == 4) {
-            __builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
+            __builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind * 4,
                             static_cast<uint8_t*>(src_arr) + src_ind * 4, 4);
        } else if (size == 8) {
-            __builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
+            __builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind * 8,
                             static_cast<uint8_t*>(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);
+            __builtin_memcpy(static_cast<uint8_t*>(dest_arr) + dest_ind * size,
                             static_cast<uint8_t*>(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,
+        __builtin_memmove(static_cast<uint8_t*>(dest_arr) + dest_ind * size,
                          static_cast<uint8_t*>(dest_arr) + (dest_end + 1) * size,
                          (dest_arr_len - dest_end - 1) * size);
        return dest_arr_len - (dest_end - dest_ind) - 1;
    }
--- a/nac3core/irrt/irrt/math.hpp
+++ b/nac3core/irrt/irrt/math.hpp
@ -90,4 +90,4 @@ double __nac3_j0(double x) {
    return j0(x);
 }
-}
+}  // namespace
--- a/nac3core/irrt/irrt/ndarray.hpp
+++ b/nac3core/irrt/irrt/ndarray.hpp
@ -2,8 +2,6 @@
 #include "irrt/int_types.hpp"
 // TODO: To be deleted since NDArray with strides is done.
 namespace {
 template<typename SizeT>
 SizeT __nac3_ndarray_calc_size_impl(const SizeT* list_data, SizeT list_len, SizeT begin_idx, SizeT end_idx) {
@ -19,7 +17,7 @@ SizeT __nac3_ndarray_calc_size_impl(const SizeT* list_data, SizeT list_len, Size
 }
 template<typename SizeT>
-void __nac3_ndarray_calc_nd_indices_impl(SizeT index, const SizeT* dims, SizeT num_dims, NDIndexInt* idxs) {
+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;
@ -30,10 +28,7 @@ void __nac3_ndarray_calc_nd_indices_impl(SizeT index, const SizeT* dims, SizeT n
 }
 template<typename SizeT>
-SizeT __nac3_ndarray_flatten_index_impl(const SizeT* dims,
+SizeT __nac3_ndarray_flatten_index_impl(const SizeT* dims, SizeT num_dims, const NDIndex* indices, SizeT num_indices) {
                                        SizeT num_dims,
                                        const NDIndexInt* indices,
                                        SizeT num_indices) {
    SizeT idx = 0;
    SizeT stride = 1;
    for (SizeT i = 0; i < num_dims; ++i) {
@ -80,8 +75,8 @@ void __nac3_ndarray_calc_broadcast_impl(const SizeT* lhs_dims,
 template<typename SizeT>
 void __nac3_ndarray_calc_broadcast_idx_impl(const SizeT* src_dims,
                                            SizeT src_ndims,
-                                            const NDIndexInt* in_idx,
+                                            const NDIndex* in_idx,
-                                            NDIndexInt* out_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];
@ -99,23 +94,21 @@ __nac3_ndarray_calc_size64(const uint64_t* list_data, uint64_t list_len, uint64_
    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) {
+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, NDIndexInt* 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 NDIndexInt* indices, uint32_t num_indices) {
+__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
-                                        uint64_t num_dims,
+__nac3_ndarray_flatten_index64(const uint64_t* dims, uint64_t num_dims, const NDIndex* indices, uint64_t num_indices) {
                                        const NDIndexInt* indices,
                                        uint64_t num_indices) {
    return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
 }
@ -137,15 +130,15 @@ void __nac3_ndarray_calc_broadcast64(const uint64_t* lhs_dims,
 void __nac3_ndarray_calc_broadcast_idx(const uint32_t* src_dims,
                                       uint32_t src_ndims,
-                                       const NDIndexInt* in_idx,
+                                       const NDIndex* in_idx,
-                                       NDIndexInt* out_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 NDIndexInt* in_idx,
+                                         const NDIndex* in_idx,
-                                         NDIndexInt* out_idx) {
+                                         NDIndex* out_idx) {
    __nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
 }
-}
+}  // namespace
--- a/nac3core/irrt/irrt/ndarray/array.hpp
+++ b/nac3core/irrt/irrt/ndarray/array.hpp
@ -1,134 +0,0 @@
 #pragma once
 #include "irrt/debug.hpp"
 #include "irrt/exception.hpp"
 #include "irrt/int_types.hpp"
 #include "irrt/list.hpp"
 #include "irrt/ndarray/basic.hpp"
 #include "irrt/ndarray/def.hpp"
 namespace {
 namespace ndarray {
 namespace array {
 /**
 * @brief In the context of `np.array(<list>)`, deduce the ndarray's shape produced by `<list>` and raise
 * an exception if there is anything wrong with `<shape>` (e.g., inconsistent dimensions `np.array([[1.0, 2.0],
 * [3.0]])`)
 *
 * If this function finds no issues with `<list>`, the deduced shape is written to `shape`. The caller has the
 * responsibility to allocate `[SizeT; ndims]` for `shape`. The caller must also initialize `shape` with `-1`s because
 * of implementation details.
 */
 template<typename SizeT>
 void set_and_validate_list_shape_helper(SizeT axis, List<SizeT>* list, SizeT ndims, SizeT* shape) {
    if (shape[axis] == -1) {
        // Dimension is unspecified. Set it.
        shape[axis] = list->len;
    } else {
        // Dimension is specified. Check.
        if (shape[axis] != list->len) {
            // Mismatch, throw an error.
            // NOTE: NumPy's error message is more complex and needs more PARAMS to display.
            raise_exception(SizeT, EXN_VALUE_ERROR,
                            "The requested array has an inhomogenous shape "
                            "after {0} dimension(s).",
                            axis, shape[axis], list->len);
        }
    }
    if (axis + 1 == ndims) {
        // `list` has type `list[ItemType]`
        // Do nothing
    } else {
        // `list` has type `list[list[...]]`
        List<SizeT>** lists = (List<SizeT>**)(list->items);
        for (SizeT i = 0; i < list->len; i++) {
            set_and_validate_list_shape_helper<SizeT>(axis + 1, lists[i], ndims, shape);
        }
    }
 }
 /**
 * @brief See `set_and_validate_list_shape_helper`.
 */
 template<typename SizeT>
 void set_and_validate_list_shape(List<SizeT>* list, SizeT ndims, SizeT* shape) {
    for (SizeT axis = 0; axis < ndims; axis++) {
        shape[axis] = -1;  // Sentinel to say this dimension is unspecified.
    }
    set_and_validate_list_shape_helper<SizeT>(0, list, ndims, shape);
 }
 /**
 * @brief In the context of `np.array(<list>)`, copied the contents stored in `list` to `ndarray`.
 *
 * `list` is assumed to be "legal". (i.e., no inconsistent dimensions)
 *
 * # Notes on `ndarray`
 * The caller is responsible for allocating space for `ndarray`.
 * Here is what this function expects from `ndarray` when called:
 *   - `ndarray->data` has to be allocated, contiguous, and may contain uninitialized values.
 *   - `ndarray->itemsize` has to be initialized.
 *   - `ndarray->ndims` has to be initialized.
 *   - `ndarray->shape` has to be initialized.
 *   - `ndarray->strides` is ignored, but note that `ndarray->data` is contiguous.
 * When this function call ends:
 *   - `ndarray->data` is written with contents from `<list>`.
 */
 template<typename SizeT>
 void write_list_to_array_helper(SizeT axis, SizeT* index, List<SizeT>* list, NDArray<SizeT>* ndarray) {
    debug_assert_eq(SizeT, list->len, ndarray->shape[axis]);
    if (IRRT_DEBUG_ASSERT_BOOL) {
        if (!ndarray::basic::is_c_contiguous(ndarray)) {
            raise_debug_assert(SizeT, "ndarray is not C-contiguous", ndarray->strides[0], ndarray->strides[1],
                               NO_PARAM);
        }
    }
    if (axis + 1 == ndarray->ndims) {
        // `list` has type `list[scalar]`
        // `ndarray` is contiguous, so we can do this, and this is fast.
        uint8_t* dst = ndarray->data + (ndarray->itemsize * (*index));
        __builtin_memcpy(dst, list->items, ndarray->itemsize * list->len);
        *index += list->len;
    } else {
        // `list` has type `list[list[...]]`
        List<SizeT>** lists = (List<SizeT>**)(list->items);
        for (SizeT i = 0; i < list->len; i++) {
            write_list_to_array_helper<SizeT>(axis + 1, index, lists[i], ndarray);
        }
    }
 }
 /**
 * @brief See `write_list_to_array_helper`.
 */
 template<typename SizeT>
 void write_list_to_array(List<SizeT>* list, NDArray<SizeT>* ndarray) {
    SizeT index = 0;
    write_list_to_array_helper<SizeT>((SizeT)0, &index, list, ndarray);
 }
 }  // namespace array
 }  // namespace ndarray
 }  // namespace
 extern "C" {
 using namespace ndarray::array;
 void __nac3_ndarray_array_set_and_validate_list_shape(List<int32_t>* list, int32_t ndims, int32_t* shape) {
    set_and_validate_list_shape(list, ndims, shape);
 }
 void __nac3_ndarray_array_set_and_validate_list_shape64(List<int64_t>* list, int64_t ndims, int64_t* shape) {
    set_and_validate_list_shape(list, ndims, shape);
 }
 void __nac3_ndarray_array_write_list_to_array(List<int32_t>* list, NDArray<int32_t>* ndarray) {
    write_list_to_array(list, ndarray);
 }
 void __nac3_ndarray_array_write_list_to_array64(List<int64_t>* list, NDArray<int64_t>* ndarray) {
    write_list_to_array(list, ndarray);
 }
 }
--- a/nac3core/irrt/irrt/ndarray/basic.hpp
+++ b/nac3core/irrt/irrt/ndarray/basic.hpp
@ -1,341 +0,0 @@
 #pragma once
 #include "irrt/debug.hpp"
 #include "irrt/exception.hpp"
 #include "irrt/int_types.hpp"
 #include "irrt/ndarray/def.hpp"
 namespace {
 namespace ndarray {
 namespace basic {
 /**
 * @brief Assert that `shape` does not contain negative dimensions.
 *
 * @param ndims Number of dimensions in `shape`
 * @param shape The shape to check on
 */
 template<typename SizeT>
 void assert_shape_no_negative(SizeT ndims, const SizeT* shape) {
    for (SizeT axis = 0; axis < ndims; axis++) {
        if (shape[axis] < 0) {
            raise_exception(SizeT, EXN_VALUE_ERROR,
                            "negative dimensions are not allowed; axis {0} "
                            "has dimension {1}",
                            axis, shape[axis], NO_PARAM);
        }
    }
 }
 /**
 * @brief Assert that two shapes are the same in the context of writing output to an ndarray.
 */
 template<typename SizeT>
 void assert_output_shape_same(SizeT ndarray_ndims,
                              const SizeT* ndarray_shape,
                              SizeT output_ndims,
                              const SizeT* output_shape) {
    if (ndarray_ndims != output_ndims) {
        // There is no corresponding NumPy error message like this.
        raise_exception(SizeT, EXN_VALUE_ERROR, "Cannot write output of ndims {0} to an ndarray with ndims {1}",
                        output_ndims, ndarray_ndims, NO_PARAM);
    }
    for (SizeT axis = 0; axis < ndarray_ndims; axis++) {
        if (ndarray_shape[axis] != output_shape[axis]) {
            // There is no corresponding NumPy error message like this.
            raise_exception(SizeT, EXN_VALUE_ERROR,
                            "Mismatched dimensions on axis {0}, output has "
                            "dimension {1}, but destination ndarray has dimension {2}.",
                            axis, output_shape[axis], ndarray_shape[axis]);
        }
    }
 }
 /**
 * @brief Return the number of elements of an ndarray given its shape.
 *
 * @param ndims Number of dimensions in `shape`
 * @param shape The shape of the ndarray
 */
 template<typename SizeT>
 SizeT calc_size_from_shape(SizeT ndims, const SizeT* shape) {
    SizeT size = 1;
    for (SizeT axis = 0; axis < ndims; axis++)
        size *= shape[axis];
    return size;
 }
 /**
 * @brief Compute the array indices of the `nth` (0-based) element of an ndarray given only its shape.
 *
 * @param ndims Number of elements in `shape` and `indices`
 * @param shape The shape of the ndarray
 * @param indices The returned indices indexing the ndarray with shape `shape`.
 * @param nth The index of the element of interest.
 */
 template<typename SizeT>
 void set_indices_by_nth(SizeT ndims, const SizeT* shape, SizeT* indices, SizeT nth) {
    for (SizeT i = 0; i < ndims; i++) {
        SizeT axis = ndims - i - 1;
        SizeT dim = shape[axis];
        indices[axis] = nth % dim;
        nth /= dim;
    }
 }
 /**
 * @brief Return the number of elements of an `ndarray`
 *
 * This function corresponds to `<an_ndarray>.size`
 */
 template<typename SizeT>
 SizeT size(const NDArray<SizeT>* ndarray) {
    return calc_size_from_shape(ndarray->ndims, ndarray->shape);
 }
 /**
 * @brief Return of the number of its content of an `ndarray`.
 *
 * This function corresponds to `<an_ndarray>.nbytes`.
 */
 template<typename SizeT>
 SizeT nbytes(const NDArray<SizeT>* ndarray) {
    return size(ndarray) * ndarray->itemsize;
 }
 /**
 * @brief Get the `len()` of an ndarray, and asserts that `ndarray` is a sized object.
 *
 * This function corresponds to `<an_ndarray>.__len__`.
 *
 * @param dst_length The length.
 */
 template<typename SizeT>
 SizeT len(const NDArray<SizeT>* ndarray) {
    // numpy prohibits `__len__` on unsized objects
    if (ndarray->ndims == 0) {
        raise_exception(SizeT, EXN_TYPE_ERROR, "len() of unsized object", NO_PARAM, NO_PARAM, NO_PARAM);
    } else {
        return ndarray->shape[0];
    }
 }
 /**
 * @brief Return a boolean indicating if `ndarray` is (C-)contiguous.
 *
 * You may want to see ndarray's rules for C-contiguity:
 * https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45
 */
 template<typename SizeT>
 bool is_c_contiguous(const NDArray<SizeT>* ndarray) {
    // References:
    // - tinynumpy's implementation:
    // https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L102
    // - ndarray's flags["C_CONTIGUOUS"]:
    // https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html#numpy.ndarray.flags
    // - ndarray's rules for C-contiguity:
    // https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45
    // From
    // https://github.com/numpy/numpy/blob/df256d0d2f3bc6833699529824781c58f9c6e697/numpy/core/src/multiarray/flagsobject.c#L95C1-L99C45:
    //
    // The traditional rule is that for an array to be flagged as C contiguous,
    // the following must hold:
    //
    // strides[-1] == itemsize
    // strides[i] == shape[i+1] * strides[i + 1]
    // [...]
    // According to these rules, a 0- or 1-dimensional array is either both
    // C- and F-contiguous, or neither; and an array with 2+ dimensions
    // can be C- or F- contiguous, or neither, but not both. Though there
    // there are exceptions for arrays with zero or one item, in the first
    // case the check is relaxed up to and including the first dimension
    // with shape[i] == 0. In the second case `strides == itemsize` will
    // can be true for all dimensions and both flags are set.
    if (ndarray->ndims == 0) {
        return true;
    }
    if (ndarray->strides[ndarray->ndims - 1] != ndarray->itemsize) {
        return false;
    }
    for (SizeT i = 1; i < ndarray->ndims; i++) {
        SizeT axis_i = ndarray->ndims - i - 1;
        if (ndarray->strides[axis_i] != ndarray->shape[axis_i + 1] * ndarray->strides[axis_i + 1]) {
            return false;
        }
    }
    return true;
 }
 /**
 * @brief Return the pointer to the element indexed by `indices` along the ndarray's axes.
 *
 * This function does no bound check.
 */
 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 of `ndarray` in flattened view.
 *
 * This function does no bound check.
 */
 template<typename SizeT>
 uint8_t* get_nth_pelement(const NDArray<SizeT>* ndarray, SizeT nth) {
    uint8_t* element = ndarray->data;
    for (SizeT i = 0; i < ndarray->ndims; i++) {
        SizeT axis = ndarray->ndims - i - 1;
        SizeT dim = ndarray->shape[axis];
        element += ndarray->strides[axis] * (nth % dim);
        nth /= dim;
    }
    return element;
 }
 /**
 * @brief Update the strides of an ndarray given an ndarray `shape` to be contiguous.
 *
 * You might want to read https://ajcr.net/stride-guide-part-1/.
 */
 template<typename SizeT>
 void set_strides_by_shape(NDArray<SizeT>* ndarray) {
    SizeT stride_product = 1;
    for (SizeT i = 0; i < ndarray->ndims; i++) {
        SizeT axis = ndarray->ndims - i - 1;
        ndarray->strides[axis] = stride_product * ndarray->itemsize;
        stride_product *= ndarray->shape[axis];
    }
 }
 /**
 * @brief Set an element in `ndarray`.
 *
 * @param pelement Pointer to the element in `ndarray` to be set.
 * @param pvalue Pointer to the value `pelement` will be set to.
 */
 template<typename SizeT>
 void set_pelement_value(NDArray<SizeT>* ndarray, uint8_t* pelement, const uint8_t* pvalue) {
    __builtin_memcpy(pelement, pvalue, ndarray->itemsize);
 }
 /**
 * @brief Copy data from one ndarray to another of the exact same size and itemsize.
 *
 * Both ndarrays will be viewed in their flatten views when copying the elements.
 */
 template<typename SizeT>
 void copy_data(const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
    // TODO: Make this faster with memcpy when we see a contiguous segment.
    // TODO: Handle overlapping.
    debug_assert_eq(SizeT, src_ndarray->itemsize, dst_ndarray->itemsize);
    for (SizeT i = 0; i < size(src_ndarray); i++) {
        auto src_element = ndarray::basic::get_nth_pelement(src_ndarray, i);
        auto dst_element = ndarray::basic::get_nth_pelement(dst_ndarray, i);
        ndarray::basic::set_pelement_value(dst_ndarray, dst_element, src_element);
    }
 }
 }  // namespace basic
 }  // namespace ndarray
 }  // namespace
 extern "C" {
 using namespace ndarray::basic;
 void __nac3_ndarray_util_assert_shape_no_negative(int32_t ndims, int32_t* shape) {
    assert_shape_no_negative(ndims, shape);
 }
 void __nac3_ndarray_util_assert_shape_no_negative64(int64_t ndims, int64_t* shape) {
    assert_shape_no_negative(ndims, shape);
 }
 void __nac3_ndarray_util_assert_output_shape_same(int32_t ndarray_ndims,
                                                  const int32_t* ndarray_shape,
                                                  int32_t output_ndims,
                                                  const int32_t* output_shape) {
    assert_output_shape_same(ndarray_ndims, ndarray_shape, output_ndims, output_shape);
 }
 void __nac3_ndarray_util_assert_output_shape_same64(int64_t ndarray_ndims,
                                                    const int64_t* ndarray_shape,
                                                    int64_t output_ndims,
                                                    const int64_t* output_shape) {
    assert_output_shape_same(ndarray_ndims, ndarray_shape, output_ndims, output_shape);
 }
 uint32_t __nac3_ndarray_size(NDArray<int32_t>* ndarray) {
    return size(ndarray);
 }
 uint64_t __nac3_ndarray_size64(NDArray<int64_t>* ndarray) {
    return size(ndarray);
 }
 uint32_t __nac3_ndarray_nbytes(NDArray<int32_t>* ndarray) {
    return nbytes(ndarray);
 }
 uint64_t __nac3_ndarray_nbytes64(NDArray<int64_t>* ndarray) {
    return nbytes(ndarray);
 }
 int32_t __nac3_ndarray_len(NDArray<int32_t>* ndarray) {
    return len(ndarray);
 }
 int64_t __nac3_ndarray_len64(NDArray<int64_t>* ndarray) {
    return len(ndarray);
 }
 bool __nac3_ndarray_is_c_contiguous(NDArray<int32_t>* ndarray) {
    return is_c_contiguous(ndarray);
 }
 bool __nac3_ndarray_is_c_contiguous64(NDArray<int64_t>* ndarray) {
    return is_c_contiguous(ndarray);
 }
 uint8_t* __nac3_ndarray_get_nth_pelement(const NDArray<int32_t>* ndarray, int32_t nth) {
    return get_nth_pelement(ndarray, nth);
 }
 uint8_t* __nac3_ndarray_get_nth_pelement64(const NDArray<int64_t>* ndarray, int64_t nth) {
    return get_nth_pelement(ndarray, nth);
 }
 uint8_t* __nac3_ndarray_get_pelement_by_indices(const NDArray<int32_t>* ndarray, int32_t* indices) {
    return get_pelement_by_indices(ndarray, indices);
 }
 uint8_t* __nac3_ndarray_get_pelement_by_indices64(const NDArray<int64_t>* ndarray, int64_t* indices) {
    return get_pelement_by_indices(ndarray, indices);
 }
 void __nac3_ndarray_set_strides_by_shape(NDArray<int32_t>* ndarray) {
    set_strides_by_shape(ndarray);
 }
 void __nac3_ndarray_set_strides_by_shape64(NDArray<int64_t>* ndarray) {
    set_strides_by_shape(ndarray);
 }
 void __nac3_ndarray_copy_data(NDArray<int32_t>* src_ndarray, NDArray<int32_t>* dst_ndarray) {
    copy_data(src_ndarray, dst_ndarray);
 }
 void __nac3_ndarray_copy_data64(NDArray<int64_t>* src_ndarray, NDArray<int64_t>* dst_ndarray) {
    copy_data(src_ndarray, dst_ndarray);
 }
 }
--- a/nac3core/irrt/irrt/ndarray/broadcast.hpp
+++ b/nac3core/irrt/irrt/ndarray/broadcast.hpp
@ -1,165 +0,0 @@
 #pragma once
 #include "irrt/int_types.hpp"
 #include "irrt/ndarray/def.hpp"
 #include "irrt/slice.hpp"
 namespace {
 template<typename SizeT>
 struct ShapeEntry {
    SizeT ndims;
    SizeT* shape;
 };
 }  // namespace
 namespace {
 namespace ndarray {
 namespace broadcast {
 /**
 * @brief Return true if `src_shape` can broadcast to `dst_shape`.
 *
 * See https://numpy.org/doc/stable/user/basics.broadcasting.html
 */
 template<typename SizeT>
 bool can_broadcast_shape_to(SizeT target_ndims, const SizeT* target_shape, SizeT src_ndims, const SizeT* src_shape) {
    if (src_ndims > target_ndims) {
        return false;
    }
    for (SizeT i = 0; i < src_ndims; i++) {
        SizeT target_dim = target_shape[target_ndims - i - 1];
        SizeT src_dim = src_shape[src_ndims - i - 1];
        if (!(src_dim == 1 || target_dim == src_dim)) {
            return false;
        }
    }
    return true;
 }
 /**
 * @brief Performs `np.broadcast_shapes(<shapes>)`
 *
 * @param num_shapes Number of entries in `shapes`
 * @param shapes The list of shape to do `np.broadcast_shapes` on.
 * @param dst_ndims The length of `dst_shape`.
 *   `dst_ndims` must be `max([shape.ndims for shape in shapes])`, but the caller has to calculate it/provide it.
 *   for this function since they should already know in order to allocate `dst_shape` in the first place.
 * @param dst_shape The resulting shape. Must be pre-allocated by the caller. This function calculate the result
 *   of `np.broadcast_shapes` and write it here.
 */
 template<typename SizeT>
 void broadcast_shapes(SizeT num_shapes, const ShapeEntry<SizeT>* shapes, SizeT dst_ndims, SizeT* dst_shape) {
    for (SizeT dst_axis = 0; dst_axis < dst_ndims; dst_axis++) {
        dst_shape[dst_axis] = 1;
    }
 #ifdef IRRT_DEBUG_ASSERT
    SizeT max_ndims_found = 0;
 #endif
    for (SizeT i = 0; i < num_shapes; i++) {
        ShapeEntry<SizeT> entry = shapes[i];
        // Check pre-condition: `dst_ndims` must be `max([shape.ndims for shape in shapes])`
        debug_assert(SizeT, entry.ndims <= dst_ndims);
 #ifdef IRRT_DEBUG_ASSERT
        max_ndims_found = max(max_ndims_found, entry.ndims);
 #endif
        for (SizeT j = 0; j < entry.ndims; j++) {
            SizeT entry_axis = entry.ndims - j - 1;
            SizeT dst_axis = dst_ndims - j - 1;
            SizeT entry_dim = entry.shape[entry_axis];
            SizeT dst_dim = dst_shape[dst_axis];
            if (dst_dim == 1) {
                dst_shape[dst_axis] = entry_dim;
            } else if (entry_dim == 1 || entry_dim == dst_dim) {
                // Do nothing
            } else {
                raise_exception(SizeT, EXN_VALUE_ERROR,
                                "shape mismatch: objects cannot be broadcast "
                                "to a single shape.",
                                NO_PARAM, NO_PARAM, NO_PARAM);
            }
        }
    }
    // Check pre-condition: `dst_ndims` must be `max([shape.ndims for shape in shapes])`
    debug_assert_eq(SizeT, max_ndims_found, dst_ndims);
 }
 /**
 * @brief Perform `np.broadcast_to(<ndarray>, <target_shape>)` and appropriate assertions.
 *
 * This function attempts to broadcast `src_ndarray` to a new shape defined by `dst_ndarray.shape`,
 * and return the result by modifying `dst_ndarray`.
 *
 * # Notes on `dst_ndarray`
 * The caller is responsible for allocating space for the resulting ndarray.
 * Here is what this function expects from `dst_ndarray` when called:
 *   - `dst_ndarray->data` does not have to be initialized.
 *   - `dst_ndarray->itemsize` does not have to be initialized.
 *   - `dst_ndarray->ndims` must be initialized, determining the length of `dst_ndarray->shape`
 *   - `dst_ndarray->shape` must be allocated, and must contain the desired target broadcast shape.
 *   - `dst_ndarray->strides` must be allocated, through it can contain uninitialized values.
 * When this function call ends:
 *   - `dst_ndarray->data` is set to `src_ndarray->data` (`dst_ndarray` is just a view to `src_ndarray`)
 *   - `dst_ndarray->itemsize` is set to `src_ndarray->itemsize`
 *   - `dst_ndarray->ndims` is unchanged.
 *   - `dst_ndarray->shape` is unchanged.
 *   - `dst_ndarray->strides` is updated accordingly by how ndarray broadcast_to works.
 */
 template<typename SizeT>
 void broadcast_to(const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
    if (!ndarray::broadcast::can_broadcast_shape_to(dst_ndarray->ndims, dst_ndarray->shape, src_ndarray->ndims,
                                                    src_ndarray->shape)) {
        raise_exception(SizeT, EXN_VALUE_ERROR, "operands could not be broadcast together", NO_PARAM, NO_PARAM,
                        NO_PARAM);
    }
    dst_ndarray->data = src_ndarray->data;
    dst_ndarray->itemsize = src_ndarray->itemsize;
    for (SizeT i = 0; i < dst_ndarray->ndims; i++) {
        SizeT src_axis = src_ndarray->ndims - i - 1;
        SizeT dst_axis = dst_ndarray->ndims - i - 1;
        if (src_axis < 0 || (src_ndarray->shape[src_axis] == 1 && dst_ndarray->shape[dst_axis] != 1)) {
            // Freeze the steps in-place
            dst_ndarray->strides[dst_axis] = 0;
        } else {
            dst_ndarray->strides[dst_axis] = src_ndarray->strides[src_axis];
        }
    }
 }
 }  // namespace broadcast
 }  // namespace ndarray
 }  // namespace
 extern "C" {
 using namespace ndarray::broadcast;
 void __nac3_ndarray_broadcast_to(NDArray<int32_t>* src_ndarray, NDArray<int32_t>* dst_ndarray) {
    broadcast_to(src_ndarray, dst_ndarray);
 }
 void __nac3_ndarray_broadcast_to64(NDArray<int64_t>* src_ndarray, NDArray<int64_t>* dst_ndarray) {
    broadcast_to(src_ndarray, dst_ndarray);
 }
 void __nac3_ndarray_broadcast_shapes(int32_t num_shapes,
                                     const ShapeEntry<int32_t>* shapes,
                                     int32_t dst_ndims,
                                     int32_t* dst_shape) {
    broadcast_shapes(num_shapes, shapes, dst_ndims, dst_shape);
 }
 void __nac3_ndarray_broadcast_shapes64(int64_t num_shapes,
                                       const ShapeEntry<int64_t>* shapes,
                                       int64_t dst_ndims,
                                       int64_t* dst_shape) {
    broadcast_shapes(num_shapes, shapes, dst_ndims, dst_shape);
 }
 }
--- a/nac3core/irrt/irrt/ndarray/def.hpp
+++ b/nac3core/irrt/irrt/ndarray/def.hpp
@ -1,45 +0,0 @@
 #pragma once
 #include "irrt/int_types.hpp"
 namespace {
 /**
 * @brief The NDArray object
 *
 * Official numpy implementation:
 * 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.
     */
    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 or contain 0.
     */
    SizeT* strides;
 };
 }  // namespace
--- a/nac3core/irrt/irrt/ndarray/indexing.hpp
+++ b/nac3core/irrt/irrt/ndarray/indexing.hpp
@ -1,220 +0,0 @@
 #pragma once
 #include "irrt/exception.hpp"
 #include "irrt/int_types.hpp"
 #include "irrt/ndarray/basic.hpp"
 #include "irrt/ndarray/def.hpp"
 #include "irrt/range.hpp"
 #include "irrt/slice.hpp"
 namespace {
 typedef uint8_t NDIndexType;
 /**
 * @brief A single element index
 *
 * `data` points to a `int32_t`.
 */
 const NDIndexType ND_INDEX_TYPE_SINGLE_ELEMENT = 0;
 /**
 * @brief A slice index
 *
 * `data` points to a `Slice<int32_t>`.
 */
 const NDIndexType ND_INDEX_TYPE_SLICE = 1;
 /**
 * @brief `np.newaxis` / `None`
 *
 * `data` is unused.
 */
 const NDIndexType ND_INDEX_TYPE_NEWAXIS = 2;
 /**
 * @brief `Ellipsis` / `...`
 *
 * `data` is unused.
 */
 const NDIndexType ND_INDEX_TYPE_ELLIPSIS = 3;
 /**
 * @brief An index used in ndarray indexing
 *
 * That is:
 * ```
 * my_ndarray[::-1, 3, ..., np.newaxis]
 *            ^^^^  ^  ^^^  ^^^^^^^^^^ each of these is represented by an NDIndex.
 * ```
 */
 struct NDIndex {
    /**
     * @brief Enum tag to specify the type of index.
     *
     * Please see the comment of each enum constant.
     */
    NDIndexType type;
    /**
     * @brief The accompanying data associated with `type`.
     *
     * Please see the comment of each enum constant.
     */
    uint8_t* data;
 };
 }  // namespace
 namespace {
 namespace ndarray {
 namespace indexing {
 /**
 * @brief Perform ndarray "basic indexing" (https://numpy.org/doc/stable/user/basics.indexing.html#basic-indexing)
 *
 * This function is very similar to performing `dst_ndarray = src_ndarray[indices]` in Python.
 *
 * This function also does proper assertions on `indices` to check for out of bounds access and more.
 *
 * # Notes on `dst_ndarray`
 * The caller is responsible for allocating space for the resulting ndarray.
 * Here is what this function expects from `dst_ndarray` when called:
 *   - `dst_ndarray->data` does not have to be initialized.
 *   - `dst_ndarray->itemsize` does not have to be initialized.
 *   - `dst_ndarray->ndims` must be initialized, and it must be equal to the expected `ndims` of the `dst_ndarray` after
 *       indexing `src_ndarray` with `indices`.
 *   - `dst_ndarray->shape` must be allocated, through it can contain uninitialized values.
 *   - `dst_ndarray->strides` must be allocated, through it can contain uninitialized values.
 * When this function call ends:
 *   - `dst_ndarray->data` is set to `src_ndarray->data`.
 *   - `dst_ndarray->itemsize` is set to `src_ndarray->itemsize`.
 *   - `dst_ndarray->ndims` is unchanged.
 *   - `dst_ndarray->shape` is updated according to how `src_ndarray` is indexed.
 *   - `dst_ndarray->strides` is updated accordingly by how ndarray indexing works.
 *
 * @param indices indices to index `src_ndarray`, ordered in the same way you would write them in Python.
 * @param src_ndarray The NDArray to be indexed.
 * @param dst_ndarray The resulting NDArray after indexing. Further details in the comments above,
 */
 template<typename SizeT>
 void index(SizeT num_indices, const NDIndex* indices, const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray) {
    // Validate `indices`.
    // Expected value of `dst_ndarray->ndims`.
    SizeT expected_dst_ndims = src_ndarray->ndims;
    // To check for "too many indices for array: array is ?-dimensional, but ? were indexed"
    SizeT num_indexed = 0;
    // There may be ellipsis `...` in `indices`. There can only be 0 or 1 ellipsis.
    SizeT num_ellipsis = 0;
    for (SizeT i = 0; i < num_indices; i++) {
        if (indices[i].type == ND_INDEX_TYPE_SINGLE_ELEMENT) {
            expected_dst_ndims--;
            num_indexed++;
        } else if (indices[i].type == ND_INDEX_TYPE_SLICE) {
            num_indexed++;
        } else if (indices[i].type == ND_INDEX_TYPE_NEWAXIS) {
            expected_dst_ndims++;
        } else if (indices[i].type == ND_INDEX_TYPE_ELLIPSIS) {
            num_ellipsis++;
            if (num_ellipsis > 1) {
                raise_exception(SizeT, EXN_INDEX_ERROR, "an index can only have a single ellipsis ('...')", NO_PARAM,
                                NO_PARAM, NO_PARAM);
            }
        } else {
            __builtin_unreachable();
        }
    }
    debug_assert_eq(SizeT, expected_dst_ndims, dst_ndarray->ndims);
    if (src_ndarray->ndims - num_indexed < 0) {
        raise_exception(SizeT, EXN_INDEX_ERROR,
                        "too many indices for array: array is {0}-dimensional, "
                        "but {1} were indexed",
                        src_ndarray->ndims, num_indices, NO_PARAM);
    }
    dst_ndarray->data = src_ndarray->data;
    dst_ndarray->itemsize = src_ndarray->itemsize;
    // Reference code:
    // https://github.com/wadetb/tinynumpy/blob/0d23d22e07062ffab2afa287374c7b366eebdda1/tinynumpy/tinynumpy.py#L652
    SizeT src_axis = 0;
    SizeT dst_axis = 0;
    for (int32_t i = 0; i < num_indices; i++) {
        const NDIndex* index = &indices[i];
        if (index->type == ND_INDEX_TYPE_SINGLE_ELEMENT) {
            SizeT input = (SizeT) * ((int32_t*)index->data);
            SizeT k = slice::resolve_index_in_length(src_ndarray->shape[src_axis], input);
            if (k == -1) {
                raise_exception(SizeT, EXN_INDEX_ERROR,
                                "index {0} is out of bounds for axis {1} "
                                "with size {2}",
                                input, src_axis, src_ndarray->shape[src_axis]);
            }
            dst_ndarray->data += k * src_ndarray->strides[src_axis];
            src_axis++;
        } else if (index->type == ND_INDEX_TYPE_SLICE) {
            Slice<int32_t>* slice = (Slice<int32_t>*)index->data;
            Range<int32_t> range = slice->indices_checked<SizeT>(src_ndarray->shape[src_axis]);
            dst_ndarray->data += (SizeT)range.start * src_ndarray->strides[src_axis];
            dst_ndarray->strides[dst_axis] = ((SizeT)range.step) * src_ndarray->strides[src_axis];
            dst_ndarray->shape[dst_axis] = (SizeT)range.len<SizeT>();
            dst_axis++;
            src_axis++;
        } else if (index->type == ND_INDEX_TYPE_NEWAXIS) {
            dst_ndarray->strides[dst_axis] = 0;
            dst_ndarray->shape[dst_axis] = 1;
            dst_axis++;
        } else if (index->type == ND_INDEX_TYPE_ELLIPSIS) {
            // The number of ':' entries this '...' implies.
            SizeT ellipsis_size = src_ndarray->ndims - num_indexed;
            for (SizeT j = 0; j < ellipsis_size; j++) {
                dst_ndarray->strides[dst_axis] = src_ndarray->strides[src_axis];
                dst_ndarray->shape[dst_axis] = src_ndarray->shape[src_axis];
                dst_axis++;
                src_axis++;
            }
        } else {
            __builtin_unreachable();
        }
    }
    for (; dst_axis < dst_ndarray->ndims; dst_axis++, src_axis++) {
        dst_ndarray->shape[dst_axis] = src_ndarray->shape[src_axis];
        dst_ndarray->strides[dst_axis] = src_ndarray->strides[src_axis];
    }
    debug_assert_eq(SizeT, src_ndarray->ndims, src_axis);
    debug_assert_eq(SizeT, dst_ndarray->ndims, dst_axis);
 }
 }  // namespace indexing
 }  // namespace ndarray
 }  // namespace
 extern "C" {
 using namespace ndarray::indexing;
 void __nac3_ndarray_index(int32_t num_indices,
                          NDIndex* indices,
                          NDArray<int32_t>* src_ndarray,
                          NDArray<int32_t>* dst_ndarray) {
    index(num_indices, indices, src_ndarray, dst_ndarray);
 }
 void __nac3_ndarray_index64(int64_t num_indices,
                            NDIndex* indices,
                            NDArray<int64_t>* src_ndarray,
                            NDArray<int64_t>* dst_ndarray) {
    index(num_indices, indices, src_ndarray, dst_ndarray);
 }
 }
--- a/nac3core/irrt/irrt/ndarray/iter.hpp
+++ b/nac3core/irrt/irrt/ndarray/iter.hpp
@ -1,146 +0,0 @@
 #pragma once
 #include "irrt/int_types.hpp"
 #include "irrt/ndarray/def.hpp"
 namespace {
 /**
 * @brief Helper struct to enumerate through an ndarray *efficiently*.
 *
 * Example usage (in pseudo-code):
 * ```
 * // Suppose my_ndarray has been initialized, with shape [2, 3] and dtype `double`
 * NDIter nditer;
 * nditer.initialize(my_ndarray);
 * while (nditer.has_element()) {
 *    // This body is run 6 (= my_ndarray.size) times.
 *
 *    // [0, 0] -> [0, 1] -> [0, 2] -> [1, 0] -> [1, 1] -> [1, 2] -> end
 *    print(nditer.indices);
 *
 *    // 0 -> 1 -> 2 -> 3 -> 4 -> 5
 *    print(nditer.nth);
 *
 *    // <1st element> -> <2nd element> -> ... -> <6th element> -> end
 *    print(*((double *) nditer.element))
 *
 *    nditer.next(); // Go to next element.
 * }
 * ```
 *
 * Interesting cases:
 * - If `my_ndarray.ndims` == 0, there is one iteration.
 * - If `my_ndarray.shape` contains zeroes, there are no iterations.
 */
 template<typename SizeT>
 struct NDIter {
    // Information about the ndarray being iterated over.
    SizeT ndims;
    SizeT* shape;
    SizeT* strides;
    /**
     * @brief The current indices.
     *
     * Must be allocated by the caller.
     */
    SizeT* indices;
    /**
     * @brief The nth (0-based) index of the current indices.
     *
     * Initially this is 0.
     */
    SizeT nth;
    /**
     * @brief Pointer to the current element.
     *
     * Initially this points to first element of the ndarray.
     */
    uint8_t* element;
    /**
     * @brief Cache for the product of shape.
     *
     * Could be 0 if `shape` has 0s in it.
     */
    SizeT size;
    void initialize(SizeT ndims, SizeT* shape, SizeT* strides, uint8_t* element, SizeT* indices) {
        this->ndims = ndims;
        this->shape = shape;
        this->strides = strides;
        this->indices = indices;
        this->element = element;
        // Compute size
        this->size = 1;
        for (SizeT i = 0; i < ndims; i++) {
            this->size *= shape[i];
        }
        // `indices` starts on all 0s.
        for (SizeT axis = 0; axis < ndims; axis++)
            indices[axis] = 0;
        nth = 0;
    }
    void initialize_by_ndarray(NDArray<SizeT>* ndarray, SizeT* indices) {
        // NOTE: ndarray->data is pointing to the first element, and `NDIter`'s `element` should also point to the first
        // element as well.
        this->initialize(ndarray->ndims, ndarray->shape, ndarray->strides, ndarray->data, indices);
    }
    // Is the current iteration valid?
    // If true, then `element`, `indices` and `nth` contain details about the current element.
    bool has_element() { return nth < size; }
    // Go to the next element.
    void next() {
        for (SizeT i = 0; i < ndims; i++) {
            SizeT axis = ndims - i - 1;
            indices[axis]++;
            if (indices[axis] >= shape[axis]) {
                indices[axis] = 0;
                // TODO: There is something called backstrides to speedup iteration.
                // See https://ajcr.net/stride-guide-part-1/, and
                // https://docs.scipy.org/doc/numpy-1.13.0/reference/c-api.types-and-structures.html#c.PyArrayIterObject.PyArrayIterObject.backstrides.
                element -= strides[axis] * (shape[axis] - 1);
            } else {
                element += strides[axis];
                break;
            }
        }
        nth++;
    }
 };
 }  // namespace
 extern "C" {
 void __nac3_nditer_initialize(NDIter<int32_t>* iter, NDArray<int32_t>* ndarray, int32_t* indices) {
    iter->initialize_by_ndarray(ndarray, indices);
 }
 void __nac3_nditer_initialize64(NDIter<int64_t>* iter, NDArray<int64_t>* ndarray, int64_t* indices) {
    iter->initialize_by_ndarray(ndarray, indices);
 }
 bool __nac3_nditer_has_element(NDIter<int32_t>* iter) {
    return iter->has_element();
 }
 bool __nac3_nditer_has_element64(NDIter<int64_t>* iter) {
    return iter->has_element();
 }
 void __nac3_nditer_next(NDIter<int32_t>* iter) {
    iter->next();
 }
 void __nac3_nditer_next64(NDIter<int64_t>* iter) {
    iter->next();
 }
 }
--- a/nac3core/irrt/irrt/ndarray/reshape.hpp
+++ b/nac3core/irrt/irrt/ndarray/reshape.hpp
@ -1,99 +0,0 @@
 #pragma once
 #include "irrt/exception.hpp"
 #include "irrt/int_types.hpp"
 #include "irrt/ndarray/def.hpp"
 namespace {
 namespace ndarray {
 namespace reshape {
 /**
 * @brief Perform assertions on and resolve unknown dimensions in `new_shape` in `np.reshape(<ndarray>, new_shape)`
 *
 * If `new_shape` indeed contains unknown dimensions (specified with `-1`, just like numpy), `new_shape` will be
 * modified to contain the resolved dimension.
 *
 * To perform assertions on and resolve unknown dimensions in `new_shape`, we don't need the actual
 * `<ndarray>` object itself, but only the `.size` of the `<ndarray>`.
 *
 * @param size The `.size` of `<ndarray>`
 * @param new_ndims Number of elements in `new_shape`
 * @param new_shape Target shape to reshape to
 */
 template<typename SizeT>
 void resolve_and_check_new_shape(SizeT size, SizeT new_ndims, SizeT* new_shape) {
    // Is there a -1 in `new_shape`?
    bool neg1_exists = false;
    // Location of -1, only initialized if `neg1_exists` is true
    SizeT neg1_axis_i;
    // The computed ndarray size of `new_shape`
    SizeT new_size = 1;
    for (SizeT axis_i = 0; axis_i < new_ndims; axis_i++) {
        SizeT dim = new_shape[axis_i];
        if (dim < 0) {
            if (dim == -1) {
                if (neg1_exists) {
                    // Multiple `-1` found. Throw an error.
                    raise_exception(SizeT, EXN_VALUE_ERROR, "can only specify one unknown dimension", NO_PARAM,
                                    NO_PARAM, NO_PARAM);
                } else {
                    neg1_exists = true;
                    neg1_axis_i = axis_i;
                }
            } else {
                // TODO: What? In `np.reshape` any negative dimensions is
                // treated like its `-1`.
                //
                // Try running `np.zeros((3, 4)).reshape((-999, 2))`
                //
                // It is not documented by numpy.
                // Throw an error for now...
                raise_exception(SizeT, EXN_VALUE_ERROR, "Found non -1 negative dimension {0} on axis {1}", dim, axis_i,
                                NO_PARAM);
            }
        } else {
            new_size *= dim;
        }
    }
    bool can_reshape;
    if (neg1_exists) {
        // Let `x` be the unknown dimension
        // Solve `x * <new_size> = <size>`
        if (new_size == 0 && size == 0) {
            // `x` has infinitely many solutions
            can_reshape = false;
        } else if (new_size == 0 && size != 0) {
            // `x` has no solutions
            can_reshape = false;
        } else if (size % new_size != 0) {
            // `x` has no integer solutions
            can_reshape = false;
        } else {
            can_reshape = true;
            new_shape[neg1_axis_i] = size / new_size;  // Resolve dimension
        }
    } else {
        can_reshape = (new_size == size);
    }
    if (!can_reshape) {
        raise_exception(SizeT, EXN_VALUE_ERROR, "cannot reshape array of size {0} into given shape", size, NO_PARAM,
                        NO_PARAM);
    }
 }
 }  // namespace reshape
 }  // namespace ndarray
 }  // namespace
 extern "C" {
 void __nac3_ndarray_reshape_resolve_and_check_new_shape(int32_t size, int32_t new_ndims, int32_t* new_shape) {
    ndarray::reshape::resolve_and_check_new_shape(size, new_ndims, new_shape);
 }
 void __nac3_ndarray_reshape_resolve_and_check_new_shape64(int64_t size, int64_t new_ndims, int64_t* new_shape) {
    ndarray::reshape::resolve_and_check_new_shape(size, new_ndims, new_shape);
 }
 }
--- a/nac3core/irrt/irrt/ndarray/transpose.hpp
+++ b/nac3core/irrt/irrt/ndarray/transpose.hpp
@ -1,145 +0,0 @@
 #pragma once
 #include "irrt/debug.hpp"
 #include "irrt/exception.hpp"
 #include "irrt/int_types.hpp"
 #include "irrt/ndarray/def.hpp"
 #include "irrt/slice.hpp"
 /*
 * Notes on `np.transpose(<array>, <axes>)`
 *
 * TODO: `axes`, if specified, can actually contain negative indices,
 * but it is not documented in numpy.
 *
 * Supporting it for now.
 */
 namespace {
 namespace ndarray {
 namespace transpose {
 /**
 * @brief Do assertions on `<axes>` in `np.transpose(<array>, <axes>)`.
 *
 * Note that `np.transpose`'s `<axe>` argument is optional. If the argument
 * is specified but the user, use this function to do assertions on it.
 *
 * @param ndims The number of dimensions of `<array>`
 * @param num_axes Number of elements in `<axes>` as specified by the user.
 *   This should be equal to `ndims`. If not, a "ValueError: axes don't match array" is thrown.
 * @param axes The user specified `<axes>`.
 */
 template<typename SizeT>
 void assert_transpose_axes(SizeT ndims, SizeT num_axes, const SizeT* axes) {
    if (ndims != num_axes) {
        raise_exception(SizeT, EXN_VALUE_ERROR, "axes don't match array", NO_PARAM, NO_PARAM, NO_PARAM);
    }
    // TODO: Optimize this
    bool* axe_specified = (bool*)__builtin_alloca(sizeof(bool) * ndims);
    for (SizeT i = 0; i < ndims; i++)
        axe_specified[i] = false;
    for (SizeT i = 0; i < ndims; i++) {
        SizeT axis = slice::resolve_index_in_length(ndims, axes[i]);
        if (axis == -1) {
            // TODO: numpy actually throws a `numpy.exceptions.AxisError`
            raise_exception(SizeT, EXN_VALUE_ERROR, "axis {0} is out of bounds for array of dimension {1}", axis, ndims,
                            NO_PARAM);
        }
        if (axe_specified[axis]) {
            raise_exception(SizeT, EXN_VALUE_ERROR, "repeated axis in transpose", NO_PARAM, NO_PARAM, NO_PARAM);
        }
        axe_specified[axis] = true;
    }
 }
 /**
 * @brief Create a transpose view of `src_ndarray` and perform proper assertions.
 *
 * This function is very similar to doing `dst_ndarray = np.transpose(src_ndarray, <axes>)`.
 * If `<axes>` is supposed to be `None`, caller can pass in a `nullptr` to `<axes>`.
 *
 * The transpose view created is returned by modifying `dst_ndarray`.
 *
 * The caller is responsible for setting up `dst_ndarray` before calling this function.
 * Here is what this function expects from `dst_ndarray` when called:
 *   - `dst_ndarray->data` does not have to be initialized.
 *   - `dst_ndarray->itemsize` does not have to be initialized.
 *   - `dst_ndarray->ndims` must be initialized, must be equal to `src_ndarray->ndims`.
 *   - `dst_ndarray->shape` must be allocated, through it can contain uninitialized values.
 *   - `dst_ndarray->strides` must be allocated, through it can contain uninitialized values.
 * When this function call ends:
 *   - `dst_ndarray->data` is set to `src_ndarray->data` (`dst_ndarray` is just a view to `src_ndarray`)
 *   - `dst_ndarray->itemsize` is set to `src_ndarray->itemsize`
 *   - `dst_ndarray->ndims` is unchanged
 *   - `dst_ndarray->shape` is updated according to how `np.transpose` works
 *   - `dst_ndarray->strides` is updated according to how `np.transpose` works
 *
 * @param src_ndarray The NDArray to build a transpose view on
 * @param dst_ndarray The resulting NDArray after transpose. Further details in the comments above,
 * @param num_axes Number of elements in axes. Unused if `axes` is nullptr.
 * @param axes Axes permutation. Set it to `nullptr` if `<axes>` is `None`.
 */
 template<typename SizeT>
 void transpose(const NDArray<SizeT>* src_ndarray, NDArray<SizeT>* dst_ndarray, SizeT num_axes, const SizeT* axes) {
    debug_assert_eq(SizeT, src_ndarray->ndims, dst_ndarray->ndims);
    const auto ndims = src_ndarray->ndims;
    if (axes != nullptr)
        assert_transpose_axes(ndims, num_axes, axes);
    dst_ndarray->data = src_ndarray->data;
    dst_ndarray->itemsize = src_ndarray->itemsize;
    // Check out https://ajcr.net/stride-guide-part-2/ to see how `np.transpose` works behind the scenes.
    if (axes == nullptr) {
        // `np.transpose(<array>, axes=None)`
        /*
         * Minor note: `np.transpose(<array>, axes=None)` is equivalent to
         * `np.transpose(<array>, axes=[N-1, N-2, ..., 0])` - basically it
         * is reversing the order of strides and shape.
         *
         * This is a fast implementation to handle this special (but very common) case.
         */
        for (SizeT axis = 0; axis < ndims; axis++) {
            dst_ndarray->shape[axis] = src_ndarray->shape[ndims - axis - 1];
            dst_ndarray->strides[axis] = src_ndarray->strides[ndims - axis - 1];
        }
    } else {
        // `np.transpose(<array>, <axes>)`
        // Permute strides and shape according to `axes`, while resolving negative indices in `axes`
        for (SizeT axis = 0; axis < ndims; axis++) {
            // `i` cannot be OUT_OF_BOUNDS because of assertions
            SizeT i = slice::resolve_index_in_length(ndims, axes[axis]);
            dst_ndarray->shape[axis] = src_ndarray->shape[i];
            dst_ndarray->strides[axis] = src_ndarray->strides[i];
        }
    }
 }
 }  // namespace transpose
 }  // namespace ndarray
 }  // namespace
 extern "C" {
 using namespace ndarray::transpose;
 void __nac3_ndarray_transpose(const NDArray<int32_t>* src_ndarray,
                              NDArray<int32_t>* dst_ndarray,
                              int32_t num_axes,
                              const int32_t* axes) {
    transpose(src_ndarray, dst_ndarray, num_axes, axes);
 }
 void __nac3_ndarray_transpose64(const NDArray<int64_t>* src_ndarray,
                                NDArray<int64_t>* dst_ndarray,
                                int64_t num_axes,
                                const int64_t* axes) {
    transpose(src_ndarray, dst_ndarray, num_axes, axes);
 }
 }
--- a/nac3core/irrt/irrt/range.hpp
+++ b/nac3core/irrt/irrt/range.hpp
@ -1,47 +0,0 @@
 #pragma once
 #include "irrt/debug.hpp"
 #include "irrt/int_types.hpp"
 namespace {
 namespace range {
 template<typename T>
 T len(T start, T stop, T step) {
    // Reference:
    // https://github.com/python/cpython/blob/9dbd12375561a393eaec4b21ee4ac568a407cdb0/Objects/rangeobject.c#L933
    if (step > 0 && start < stop)
        return 1 + (stop - 1 - start) / step;
    else if (step < 0 && start > stop)
        return 1 + (start - 1 - stop) / (-step);
    else
        return 0;
 }
 }  // namespace range
 /**
 * @brief A Python range.
 */
 template<typename T>
 struct Range {
    T start;
    T stop;
    T step;
    /**
     * @brief Calculate the `len()` of this range.
     */
    template<typename SizeT>
    T len() {
        debug_assert(SizeT, step != 0);
        return range::len(start, stop, step);
    }
 };
 }  // namespace
 extern "C" {
 using namespace range;
 SliceIndex __nac3_range_slice_len(const SliceIndex start, const SliceIndex end, const SliceIndex step) {
    return len(start, end, step);
 }
 }
--- a/nac3core/irrt/irrt/slice.hpp
+++ b/nac3core/irrt/irrt/slice.hpp
@ -1,145 +1,6 @@
 #pragma once
 #include "irrt/debug.hpp"
 #include "irrt/exception.hpp"
 #include "irrt/int_types.hpp"
 #include "irrt/math_util.hpp"
 #include "irrt/range.hpp"
 namespace {
 namespace slice {
 /**
 * @brief Resolve a possibly negative index in a list of a known length.
 *
 * Returns -1 if the resolved index is out of the list's bounds.
 */
 template<typename T>
 T resolve_index_in_length(T length, T index) {
    T resolved = index < 0 ? length + index : index;
    if (0 <= resolved && resolved < length) {
        return resolved;
    } else {
        return -1;
    }
 }
 /**
 * @brief Resolve a slice as a range.
 *
 * This is equivalent to `range(*slice(start, stop, step).indices(length))` in Python.
 */
 template<typename T>
 void indices(bool start_defined,
             T start,
             bool stop_defined,
             T stop,
             bool step_defined,
             T step,
             T length,
             T* range_start,
             T* range_stop,
             T* range_step) {
    // Reference: https://github.com/python/cpython/blob/main/Objects/sliceobject.c#L388
    *range_step = step_defined ? step : 1;
    bool step_is_negative = *range_step < 0;
    T lower, upper;
    if (step_is_negative) {
        lower = -1;
        upper = length - 1;
    } else {
        lower = 0;
        upper = length;
    }
    if (start_defined) {
        *range_start = start < 0 ? max(lower, start + length) : min(upper, start);
    } else {
        *range_start = step_is_negative ? upper : lower;
    }
    if (stop_defined) {
        *range_stop = stop < 0 ? max(lower, stop + length) : min(upper, stop);
    } else {
        *range_stop = step_is_negative ? lower : upper;
    }
 }
 }  // namespace slice
 /**
 * @brief A Python-like slice with **unresolved** indices.
 */
 template<typename T>
 struct Slice {
    bool start_defined;
    T start;
    bool stop_defined;
    T stop;
    bool step_defined;
    T step;
    Slice() { this->reset(); }
    void reset() {
        this->start_defined = false;
        this->stop_defined = false;
        this->step_defined = false;
    }
    void set_start(T start) {
        this->start_defined = true;
        this->start = start;
    }
    void set_stop(T stop) {
        this->stop_defined = true;
        this->stop = stop;
    }
    void set_step(T step) {
        this->step_defined = true;
        this->step = step;
    }
    /**
     * @brief Resolve this slice as a range.
     *
     * In Python, this would be `range(*slice(start, stop, step).indices(length))`.
     */
    template<typename SizeT>
    Range<T> indices(T length) {
        // Reference:
        // https://github.com/python/cpython/blob/main/Objects/sliceobject.c#L388
        debug_assert(SizeT, length >= 0);
        Range<T> result;
        slice::indices(start_defined, start, stop_defined, stop, step_defined, step, length, &result.start,
                       &result.stop, &result.step);
        return result;
    }
    /**
     * @brief Like `.indices()` but with assertions.
     */
    template<typename SizeT>
    Range<T> indices_checked(T length) {
        // TODO: Switch to `SizeT length`
        if (length < 0) {
            raise_exception(SizeT, EXN_VALUE_ERROR, "length should not be negative, got {0}", length, NO_PARAM,
                            NO_PARAM);
        }
        if (this->step_defined && this->step == 0) {
            raise_exception(SizeT, EXN_VALUE_ERROR, "slice step cannot be zero", NO_PARAM, NO_PARAM, NO_PARAM);
        }
        return this->indices<SizeT>(length);
    }
 };
 }  // namespace
 extern "C" {
 SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
@ -153,4 +14,15 @@ SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex 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;
    }
 }
 }  // namespace
--- a/nac3core/nac3core_derive/Cargo.toml
+++ b/nac3core/nac3core_derive/Cargo.toml
@ -0,0 +1,21 @@
 [package]
 name = "nac3core_derive"
 version = "0.1.0"
 edition = "2021"
 [lib]
 proc-macro = true
 [[test]]
 name = "structfields_tests"
 path = "tests/structfields_test.rs"
 [dev-dependencies]
 nac3core = { path = ".." }
 trybuild = { version = "1.0", features = ["diff"] }
 [dependencies]
 proc-macro2 = "1.0"
 proc-macro-error = "1.0"
 syn = "2.0"
 quote = "1.0"
--- a/nac3core/nac3core_derive/src/lib.rs
+++ b/nac3core/nac3core_derive/src/lib.rs
@ -0,0 +1,320 @@
 use proc_macro::TokenStream;
 use proc_macro_error::{abort, proc_macro_error};
 use quote::quote;
 use syn::{
    parse_macro_input, spanned::Spanned, Data, DataStruct, Expr, ExprField, ExprMethodCall,
    ExprPath, GenericArgument, Ident, LitStr, Path, PathArguments, Type, TypePath,
 };
 /// Extracts all generic arguments of a [`Type`] into a [`Vec`].
 ///
 /// Returns [`Some`] of a possibly-empty [`Vec`] if the path of `ty` matches with
 /// `expected_ty_name`, otherwise returns [`None`].
 fn extract_generic_args(expected_ty_name: &'static str, ty: &Type) -> Option<Vec<GenericArgument>> {
    let Type::Path(TypePath { qself: None, path, .. }) = ty else {
        return None;
    };
    let segments = &path.segments;
    if segments.len() != 1 {
        return None;
    };
    let segment = segments.iter().next().unwrap();
    if segment.ident != expected_ty_name {
        return None;
    }
    let PathArguments::AngleBracketed(path_args) = &segment.arguments else {
        return Some(Vec::new());
    };
    let args = &path_args.args;
    Some(args.iter().cloned().collect::<Vec<_>>())
 }
 /// Maps a `path` matching one of the `target_idents` into the `replacement` [`Ident`].
 fn map_path_to_ident(path: &Path, target_idents: &[&str], replacement: &str) -> Option<Ident> {
    path.require_ident()
        .ok()
        .filter(|ident| target_idents.iter().any(|target| ident == target))
        .map(|ident| Ident::new(replacement, ident.span()))
 }
 /// Extracts the left-hand side of a dot-expression.
 fn extract_dot_operand(expr: &Expr) -> Option<&Expr> {
    match expr {
        Expr::MethodCall(ExprMethodCall { receiver: operand, .. })
        | Expr::Field(ExprField { base: operand, .. }) => Some(operand),
        _ => None,
    }
 }
 /// Replaces the top-level receiver of a dot-expression with an [`Ident`], returning `Some(&mut expr)` if the
 /// replacement is performed.
 ///
 /// The top-level receiver is the left-most receiver expression, e.g. the top-level receiver of `a.b.c.foo()` is `a`.
 fn replace_top_level_receiver(expr: &mut Expr, ident: Ident) -> Option<&mut Expr> {
    if let Expr::MethodCall(ExprMethodCall { receiver: operand, .. })
    | Expr::Field(ExprField { base: operand, .. }) = expr
    {
        return if extract_dot_operand(operand).is_some() {
            if replace_top_level_receiver(operand, ident).is_some() {
                Some(expr)
            } else {
                None
            }
        } else {
            *operand = Box::new(Expr::Path(ExprPath {
                attrs: Vec::default(),
                qself: None,
                path: ident.into(),
            }));
            Some(expr)
        };
    }
    None
 }
 /// Iterates all operands to the left-hand side of the `.` of an [expression][`Expr`], i.e. the container operand of all
 /// [`Expr::Field`] and the receiver operand of all [`Expr::MethodCall`].
 ///
 /// The iterator will return the operand expressions in reverse order of appearance. For example, `a.b.c.func()` will
 /// return `vec![c, b, a]`.
 fn iter_dot_operands(expr: &Expr) -> impl Iterator<Item = &Expr> {
    let mut o = extract_dot_operand(expr);
    std::iter::from_fn(move || {
        let this = o;
        o = o.as_ref().and_then(|o| extract_dot_operand(o));
        this
    })
 }
 /// Normalizes a value expression for use when creating an instance of this structure, returning a
 /// [`proc_macro2::TokenStream`] of tokens representing the normalized expression.
 fn normalize_value_expr(expr: &Expr) -> proc_macro2::TokenStream {
    match &expr {
        Expr::Path(ExprPath { qself: None, path, .. }) => {
            if let Some(ident) = map_path_to_ident(path, &["usize", "size_t"], "llvm_usize") {
                quote! { #ident }
            } else {
                abort!(
                    path,
                    format!(
                        "Expected one of `size_t`, `usize`, or an implicit call expression in #[value_type(...)], found {}", 
                        quote!(#expr).to_string(),
                    )
                )
            }
        }
        Expr::Call(_) => {
            quote! { ctx.#expr }
        }
        Expr::MethodCall(_) => {
            let base_receiver = iter_dot_operands(expr).last();
            match base_receiver {
                // `usize.{...}`, `size_t.{...}` -> Rewrite the identifiers to `llvm_usize`
                Some(Expr::Path(ExprPath { qself: None, path, .. }))
                    if map_path_to_ident(path, &["usize", "size_t"], "llvm_usize").is_some() =>
                {
                    let ident =
                        map_path_to_ident(path, &["usize", "size_t"], "llvm_usize").unwrap();
                    let mut expr = expr.clone();
                    let expr = replace_top_level_receiver(&mut expr, ident).unwrap();
                    quote!(#expr)
                }
                // `ctx.{...}`, `context.{...}` -> Rewrite the identifiers to `ctx`
                Some(Expr::Path(ExprPath { qself: None, path, .. }))
                    if map_path_to_ident(path, &["ctx", "context"], "ctx").is_some() =>
                {
                    let ident = map_path_to_ident(path, &["ctx", "context"], "ctx").unwrap();
                    let mut expr = expr.clone();
                    let expr = replace_top_level_receiver(&mut expr, ident).unwrap();
                    quote!(#expr)
                }
                // No reserved identifier prefix -> Prepend `ctx.` to the entire expression
                _ => quote! { ctx.#expr },
            }
        }
        _ => {
            abort!(
                expr,
                format!(
                    "Expected one of `size_t`, `usize`, or an implicit call expression in #[value_type(...)], found {}", 
                    quote!(#expr).to_string(),
                )
            )
        }
    }
 }
 /// Derives an implementation of `codegen::types::structure::StructFields`.
 ///
 /// The benefit of using `#[derive(StructFields)]` is that all index- or order-dependent logic required by
 /// `impl StructFields` is automatically generated by this implementation, including the field index as required by
 /// `StructField::new` and the fields as returned by `StructFields::to_vec`.
 ///
 /// # Prerequisites
 ///
 /// In order to derive from [`StructFields`], you must implement (or derive) [`Eq`] and [`Copy`] as required by
 /// `StructFields`.
 ///
 /// Moreover, `#[derive(StructFields)]` can only be used for `struct`s with named fields, and may only contain fields
 /// with either `StructField` or [`PhantomData`] types.
 ///
 /// # Attributes for [`StructFields`]
 ///
 /// Each `StructField` field must be declared with the `#[value_type(...)]` attribute. The argument of `value_type`
 /// accepts one of the following:
 ///
 /// - An expression returning an instance of `inkwell::types::BasicType` (with or without the receiver `ctx`/`context`).
 /// For example, `context.i8_type()`, `ctx.i8_type()`, and `i8_type()` all refer to `i8`.
 /// - The reserved identifiers `usize` and `size_t` referring to an `inkwell::types::IntType` of the platform-dependent
 /// integer size. `usize` and `size_t` can also be used as the receiver to other method calls, e.g.
 /// `usize.array_type(3)`.
 ///
 /// # Example
 ///
 /// The following is an example of an LLVM slice implemented using `#[derive(StructFields)]`.
 ///
 /// ```rust,ignore
 /// use nac3core::{
 ///     codegen::types::structure::StructField,
 ///     inkwell::{
 ///         values::{IntValue, PointerValue},
 ///         AddressSpace,
 ///     },
 /// };
 /// use nac3core_derive::StructFields;
 ///
 /// // All classes that implement StructFields must also implement Eq and Copy
 /// #[derive(PartialEq, Eq, Clone, Copy, StructFields)]
 /// pub struct SliceValue<'ctx> {
 ///     // Declares ptr have a value type of i8*
 ///     //
 ///     // Can also be written as `ctx.i8_type().ptr_type(...)` or `context.i8_type().ptr_type(...)`
 ///     #[value_type(i8_type().ptr_type(AddressSpace::default()))]
 ///     ptr: StructField<'ctx, PointerValue<'ctx>>,
 ///
 ///     // Declares len have a value type of usize, depending on the target compilation platform
 ///     #[value_type(usize)]
 ///     len: StructField<'ctx, IntValue<'ctx>>,
 /// }
 /// ```
 #[proc_macro_derive(StructFields, attributes(value_type))]
 #[proc_macro_error]
 pub fn derive(input: TokenStream) -> TokenStream {
    let input = parse_macro_input!(input as syn::DeriveInput);
    let ident = &input.ident;
    let Data::Struct(DataStruct { fields, .. }) = &input.data else {
        abort!(input, "Only structs with named fields are supported");
    };
    if let Err(err_span) =
        fields
            .iter()
            .try_for_each(|field| if field.ident.is_some() { Ok(()) } else { Err(field.span()) })
    {
        abort!(err_span, "Only structs with named fields are supported");
    };
    // Check if struct<'ctx>
    if input.generics.params.len() != 1 {
        abort!(input.generics, "Expected exactly 1 generic parameter")
    }
    let phantom_info = fields
        .iter()
        .filter(|field| extract_generic_args("PhantomData", &field.ty).is_some())
        .map(|field| field.ident.as_ref().unwrap())
        .cloned()
        .collect::<Vec<_>>();
    let field_info = fields
        .iter()
        .filter(|field| extract_generic_args("PhantomData", &field.ty).is_none())
        .map(|field| {
            let ident = field.ident.as_ref().unwrap();
            let ty = &field.ty;
            let Some(_) = extract_generic_args("StructField", ty) else {
                abort!(field, "Only StructField and PhantomData are allowed")
            };
            let attrs = &field.attrs;
            let Some(value_type_attr) =
                attrs.iter().find(|attr| attr.path().is_ident("value_type"))
            else {
                abort!(field, "Expected #[value_type(...)] attribute for field");
            };
            let Ok(value_type_expr) = value_type_attr.parse_args::<Expr>() else {
                abort!(value_type_attr, "Expected expression in #[value_type(...)]");
            };
            let value_expr_toks = normalize_value_expr(&value_type_expr);
            (ident.clone(), value_expr_toks)
        })
        .collect::<Vec<_>>();
    // `<*>::new` impl of `StructField` and `PhantomData` for `StructFields::new`
    let phantoms_create = phantom_info
        .iter()
        .map(|id| quote! { #id: ::std::marker::PhantomData })
        .collect::<Vec<_>>();
    let fields_create = field_info
        .iter()
        .map(|(id, ty)| {
            let id_lit = LitStr::new(&id.to_string(), id.span());
            quote! {
                #id: ::nac3core::codegen::types::structure::StructField::create(
                    &mut counter,
                    #id_lit,
                    #ty,
                )
            }
        })
        .collect::<Vec<_>>();
    // `.into()` impl of `StructField` for `StructFields::to_vec`
    let fields_into =
        field_info.iter().map(|(id, _)| quote! { self.#id.into() }).collect::<Vec<_>>();
    let impl_block = quote! {
        impl<'ctx> ::nac3core::codegen::types::structure::StructFields<'ctx> for #ident<'ctx> {
            fn new(ctx: impl ::nac3core::inkwell::context::AsContextRef<'ctx>, llvm_usize: ::nac3core::inkwell::types::IntType<'ctx>) -> Self {
                let ctx = unsafe { ::nac3core::inkwell::context::ContextRef::new(ctx.as_ctx_ref()) };
                let mut counter = ::nac3core::codegen::types::structure::FieldIndexCounter::default();
                #ident {
                    #(#fields_create),*
                    #(#phantoms_create),*
                }
            }
            fn to_vec(&self) -> ::std::vec::Vec<(&'static str, ::nac3core::inkwell::types::BasicTypeEnum<'ctx>)> {
                vec![
                    #(#fields_into),*
                ]
            }
        }
    };
    impl_block.into()
 }
--- a/nac3core/nac3core_derive/tests/structfields_empty.rs
+++ b/nac3core/nac3core_derive/tests/structfields_empty.rs
@ -0,0 +1,9 @@
 use nac3core_derive::StructFields;
 use std::marker::PhantomData;
 #[derive(PartialEq, Eq, Clone, Copy, StructFields)]
 pub struct EmptyValue<'ctx> {
    _phantom: PhantomData<&'ctx ()>,
 }
 fn main() {}
--- a/nac3core/nac3core_derive/tests/structfields_ndarray.rs
+++ b/nac3core/nac3core_derive/tests/structfields_ndarray.rs
@ -0,0 +1,20 @@
 use nac3core::{
    codegen::types::structure::StructField,
    inkwell::{
        values::{IntValue, PointerValue},
        AddressSpace,
    },
 };
 use nac3core_derive::StructFields;
 #[derive(PartialEq, Eq, Clone, Copy, StructFields)]
 pub struct NDArrayValue<'ctx> {
    #[value_type(usize)]
    ndims: StructField<'ctx, IntValue<'ctx>>,
    #[value_type(usize.ptr_type(AddressSpace::default()))]
    shape: StructField<'ctx, PointerValue<'ctx>>,
    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
    data: StructField<'ctx, PointerValue<'ctx>>,
 }
 fn main() {}
--- a/nac3core/nac3core_derive/tests/structfields_slice.rs
+++ b/nac3core/nac3core_derive/tests/structfields_slice.rs
@ -0,0 +1,18 @@
 use nac3core::{
    codegen::types::structure::StructField,
    inkwell::{
        values::{IntValue, PointerValue},
        AddressSpace,
    },
 };
 use nac3core_derive::StructFields;
 #[derive(PartialEq, Eq, Clone, Copy, StructFields)]
 pub struct SliceValue<'ctx> {
    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
    ptr: StructField<'ctx, PointerValue<'ctx>>,
    #[value_type(usize)]
    len: StructField<'ctx, IntValue<'ctx>>,
 }
 fn main() {}
--- a/nac3core/nac3core_derive/tests/structfields_slice_context.rs
+++ b/nac3core/nac3core_derive/tests/structfields_slice_context.rs
@ -0,0 +1,18 @@
 use nac3core::{
    codegen::types::structure::StructField,
    inkwell::{
        values::{IntValue, PointerValue},
        AddressSpace,
    },
 };
 use nac3core_derive::StructFields;
 #[derive(PartialEq, Eq, Clone, Copy, StructFields)]
 pub struct SliceValue<'ctx> {
    #[value_type(context.i8_type().ptr_type(AddressSpace::default()))]
    ptr: StructField<'ctx, PointerValue<'ctx>>,
    #[value_type(usize)]
    len: StructField<'ctx, IntValue<'ctx>>,
 }
 fn main() {}
--- a/nac3core/nac3core_derive/tests/structfields_slice_ctx.rs
+++ b/nac3core/nac3core_derive/tests/structfields_slice_ctx.rs
@ -0,0 +1,18 @@
 use nac3core::{
    codegen::types::structure::StructField,
    inkwell::{
        values::{IntValue, PointerValue},
        AddressSpace,
    },
 };
 use nac3core_derive::StructFields;
 #[derive(PartialEq, Eq, Clone, Copy, StructFields)]
 pub struct SliceValue<'ctx> {
    #[value_type(ctx.i8_type().ptr_type(AddressSpace::default()))]
    ptr: StructField<'ctx, PointerValue<'ctx>>,
    #[value_type(usize)]
    len: StructField<'ctx, IntValue<'ctx>>,
 }
 fn main() {}
--- a/nac3core/nac3core_derive/tests/structfields_slice_sizet.rs
+++ b/nac3core/nac3core_derive/tests/structfields_slice_sizet.rs
@ -0,0 +1,18 @@
 use nac3core::{
    codegen::types::structure::StructField,
    inkwell::{
        values::{IntValue, PointerValue},
        AddressSpace,
    },
 };
 use nac3core_derive::StructFields;
 #[derive(PartialEq, Eq, Clone, Copy, StructFields)]
 pub struct SliceValue<'ctx> {
    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
    ptr: StructField<'ctx, PointerValue<'ctx>>,
    #[value_type(size_t)]
    len: StructField<'ctx, IntValue<'ctx>>,
 }
 fn main() {}
--- a/nac3core/nac3core_derive/tests/structfields_test.rs
+++ b/nac3core/nac3core_derive/tests/structfields_test.rs
@ -0,0 +1,10 @@
 #[test]
 fn test_parse_empty() {
    let t = trybuild::TestCases::new();
    t.pass("tests/structfields_empty.rs");
    t.pass("tests/structfields_slice.rs");
    t.pass("tests/structfields_slice_ctx.rs");
    t.pass("tests/structfields_slice_context.rs");
    t.pass("tests/structfields_slice_sizet.rs");
    t.pass("tests/structfields_ndarray.rs");
 }
--- a/nac3core/src/codegen/builtin_fns.rs
+++ b/nac3core/src/codegen/builtin_fns.rs
@ -1,26 +1,32 @@
-use inkwell::types::BasicTypeEnum;
+use inkwell::{
-use inkwell::values::{BasicValue, BasicValueEnum, IntValue, PointerValue};
+    types::BasicTypeEnum,
-use inkwell::{FloatPredicate, IntPredicate, OptimizationLevel};
+    values::{BasicValue, BasicValueEnum, IntValue, PointerValue},
    FloatPredicate, IntPredicate, OptimizationLevel,
 };
 use itertools::Itertools;
-use crate::codegen::classes::{
+use super::{
-    NDArrayValue, ProxyValue, RangeValue, UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
+    expr::destructure_range,
    extern_fns, irrt,
    irrt::calculate_len_for_slice_range,
    llvm_intrinsics,
    macros::codegen_unreachable,
    numpy,
    numpy::ndarray_elementwise_unaryop_impl,
    stmt::gen_for_callback_incrementing,
    values::{
        ArrayLikeValue, NDArrayValue, ProxyValue, RangeValue, TypedArrayLikeAccessor,
        UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
    },
    CodeGenContext, CodeGenerator,
 };
 use crate::{
    toplevel::{
        helper::{arraylike_flatten_element_type, PrimDef},
        numpy::unpack_ndarray_var_tys,
    },
    typecheck::typedef::{Type, TypeEnum},
 };
 use crate::codegen::expr::destructure_range;
 use crate::codegen::irrt::calculate_len_for_slice_range;
 use crate::codegen::macros::codegen_unreachable;
 use crate::codegen::numpy::ndarray_elementwise_unaryop_impl;
 use crate::codegen::stmt::gen_for_callback_incrementing;
 use crate::codegen::{extern_fns, irrt, llvm_intrinsics, numpy, CodeGenContext, CodeGenerator};
 use crate::toplevel::helper::PrimDef;
 use crate::toplevel::numpy::unpack_ndarray_var_tys;
 use crate::typecheck::typedef::{Type, TypeEnum};
 use super::model::*;
 use super::object::any::AnyObject;
 use super::object::list::ListObject;
 use super::object::ndarray::NDArrayObject;
 use super::object::tuple::TupleObject;
 /// Shorthand for [`unreachable!()`] when a type of argument is not supported.
 ///
@ -39,33 +45,59 @@ pub fn call_len<'ctx, G: CodeGenerator + ?Sized>(
    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, ctx.primitives.range) {
+
-        let arg = RangeValue::from_ptr_val(arg.into_pointer_value(), Some("range"));
+    Ok(if ctx.unifier.unioned(arg_ty, range_ty) {
        let arg = RangeValue::from_pointer_value(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 {
-        let arg = AnyObject { ty: arg_ty, value: arg };
+        match &*ctx.unifier.get_ty_immutable(arg_ty) {
-        let len: Instance<'ctx, Int<Int32>> = match &*ctx.unifier.get_ty(arg_ty) {
+            TypeEnum::TTuple { ty, .. } => llvm_i32.const_int(ty.len() as u64, false),
-            TypeEnum::TTuple { .. } => {
+            TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::List.id() => {
-                let tuple = TupleObject::from_object(ctx, arg);
+                let zero = llvm_i32.const_zero();
-                tuple.len(generator, ctx).truncate_or_bit_cast(generator, ctx, Int32)
+                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, .. }
+            TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-                if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
+                let elem_ty = arraylike_flatten_element_type(&mut ctx.unifier, arg_ty);
-            {
+                let llvm_usize = generator.get_size_type(ctx.ctx);
-                let ndarray = NDArrayObject::from_object(generator, ctx, arg);
+
-                ndarray.len(generator, ctx).truncate_or_bit_cast(generator, ctx, Int32)
+                let arg = NDArrayValue::from_pointer_value(
-            }
+                    arg.into_pointer_value(),
-            TypeEnum::TObj { obj_id, .. }
+                    ctx.get_llvm_type(generator, elem_ty),
-                if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
+                    llvm_usize,
-            {
+                    None,
-                let list = ListObject::from_object(generator, ctx, arg);
+                );
-                list.len(generator, ctx).truncate_or_bit_cast(generator, ctx, Int32)
+
-            }
+                let ndims = arg.shape().size(ctx, generator);
-            _ => unsupported_type(ctx, "len", &[arg_ty]),
+                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.shape().get_typed_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
                };
-        len.value
+
                ctx.builder.build_int_truncate_or_bit_cast(len, llvm_i32, "len").unwrap()
            }
            _ => codegen_unreachable!(ctx),
        }
    })
 }
@ -114,13 +146,14 @@ pub fn call_int32<'ctx, G: CodeGenerator + ?Sized>(
            if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
        {
            let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
            let ndarray = ndarray_elementwise_unaryop_impl(
                generator,
                ctx,
                ctx.primitives.int32,
                None,
-                NDArrayValue::from_ptr_val(n, llvm_usize, None),
+                NDArrayValue::from_pointer_value(n, llvm_elem_ty, llvm_usize, None),
                |generator, ctx, val| call_int32(generator, ctx, (elem_ty, val)),
            )?;
@ -176,13 +209,14 @@ pub fn call_int64<'ctx, G: CodeGenerator + ?Sized>(
            if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
        {
            let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
            let ndarray = ndarray_elementwise_unaryop_impl(
                generator,
                ctx,
                ctx.primitives.int64,
                None,
-                NDArrayValue::from_ptr_val(n, llvm_usize, None),
+                NDArrayValue::from_pointer_value(n, llvm_elem_ty, llvm_usize, None),
                |generator, ctx, val| call_int64(generator, ctx, (elem_ty, val)),
            )?;
@ -254,13 +288,14 @@ pub fn call_uint32<'ctx, G: CodeGenerator + ?Sized>(
            if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
        {
            let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
            let ndarray = ndarray_elementwise_unaryop_impl(
                generator,
                ctx,
                ctx.primitives.uint32,
                None,
-                NDArrayValue::from_ptr_val(n, llvm_usize, None),
+                NDArrayValue::from_pointer_value(n, llvm_elem_ty, llvm_usize, None),
                |generator, ctx, val| call_uint32(generator, ctx, (elem_ty, val)),
            )?;
@ -321,13 +356,14 @@ pub fn call_uint64<'ctx, G: CodeGenerator + ?Sized>(
            if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
        {
            let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
            let ndarray = ndarray_elementwise_unaryop_impl(
                generator,
                ctx,
                ctx.primitives.uint64,
                None,
-                NDArrayValue::from_ptr_val(n, llvm_usize, None),
+                NDArrayValue::from_pointer_value(n, llvm_elem_ty, llvm_usize, None),
                |generator, ctx, val| call_uint64(generator, ctx, (elem_ty, val)),
            )?;
@ -387,13 +423,14 @@ pub fn call_float<'ctx, G: CodeGenerator + ?Sized>(
            if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
        {
            let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
            let ndarray = ndarray_elementwise_unaryop_impl(
                generator,
                ctx,
                ctx.primitives.float,
                None,
-                NDArrayValue::from_ptr_val(n, llvm_usize, None),
+                NDArrayValue::from_pointer_value(n, llvm_elem_ty, llvm_usize, None),
                |generator, ctx, val| call_float(generator, ctx, (elem_ty, val)),
            )?;
@ -433,13 +470,14 @@ pub fn call_round<'ctx, G: CodeGenerator + ?Sized>(
            if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
        {
            let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
            let ndarray = ndarray_elementwise_unaryop_impl(
                generator,
                ctx,
                ret_elem_ty,
                None,
-                NDArrayValue::from_ptr_val(n, llvm_usize, None),
+                NDArrayValue::from_pointer_value(n, llvm_elem_ty, llvm_usize, None),
                |generator, ctx, val| call_round(generator, ctx, (elem_ty, val), ret_elem_ty),
            )?;
@ -473,13 +511,14 @@ pub fn call_numpy_round<'ctx, G: CodeGenerator + ?Sized>(
            if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
        {
            let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
            let ndarray = ndarray_elementwise_unaryop_impl(
                generator,
                ctx,
                ctx.primitives.float,
                None,
-                NDArrayValue::from_ptr_val(n, llvm_usize, None),
+                NDArrayValue::from_pointer_value(n, llvm_elem_ty, llvm_usize, None),
                |generator, ctx, val| call_numpy_round(generator, ctx, (elem_ty, val)),
            )?;
@ -538,13 +577,14 @@ pub fn call_bool<'ctx, G: CodeGenerator + ?Sized>(
            if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
        {
            let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
            let ndarray = ndarray_elementwise_unaryop_impl(
                generator,
                ctx,
                ctx.primitives.bool,
                None,
-                NDArrayValue::from_ptr_val(n, llvm_usize, None),
+                NDArrayValue::from_pointer_value(n, llvm_elem_ty, llvm_usize, None),
                |generator, ctx, val| {
                    let elem = call_bool(generator, ctx, (elem_ty, val))?;
@ -592,13 +632,14 @@ pub fn call_floor<'ctx, G: CodeGenerator + ?Sized>(
            if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
        {
            let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
            let ndarray = ndarray_elementwise_unaryop_impl(
                generator,
                ctx,
                ret_elem_ty,
                None,
-                NDArrayValue::from_ptr_val(n, llvm_usize, None),
+                NDArrayValue::from_pointer_value(n, llvm_elem_ty, llvm_usize, None),
                |generator, ctx, val| call_floor(generator, ctx, (elem_ty, val), ret_elem_ty),
            )?;
@ -642,13 +683,14 @@ pub fn call_ceil<'ctx, G: CodeGenerator + ?Sized>(
            if n_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
        {
            let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, n_ty);
            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
            let ndarray = ndarray_elementwise_unaryop_impl(
                generator,
                ctx,
                ret_elem_ty,
                None,
-                NDArrayValue::from_ptr_val(n, llvm_usize, None),
+                NDArrayValue::from_pointer_value(n, llvm_elem_ty, llvm_usize, None),
                |generator, ctx, val| call_ceil(generator, ctx, (elem_ty, val), ret_elem_ty),
            )?;
@ -777,8 +819,8 @@ pub fn call_numpy_minimum<'ctx, G: CodeGenerator + ?Sized>(
                ctx,
                dtype,
                None,
-                (x1, !is_ndarray1),
+                (x1_ty, x1, !is_ndarray1),
-                (x2, !is_ndarray2),
+                (x2_ty, x2, !is_ndarray2),
                |generator, ctx, (lhs, rhs)| {
                    call_numpy_minimum(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
                },
@ -877,10 +919,10 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
            if a_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) =>
        {
            let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, a_ty);
-            let llvm_ndarray_ty = ctx.get_llvm_type(generator, elem_ty);
+            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-            let n = NDArrayValue::from_ptr_val(n, llvm_usize, None);
+            let n = NDArrayValue::from_pointer_value(n, llvm_elem_ty, llvm_usize, None);
-            let n_sz = irrt::call_ndarray_calc_size(generator, ctx, &n.dim_sizes(), (None, None));
+            let n_sz = irrt::call_ndarray_calc_size(generator, ctx, &n.shape(), (None, None));
            if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
                let n_sz_eqz = ctx
                    .builder
@ -897,7 +939,7 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
                );
            }
-            let accumulator_addr = generator.gen_var_alloc(ctx, llvm_ndarray_ty, None)?;
+            let accumulator_addr = generator.gen_var_alloc(ctx, llvm_elem_ty, None)?;
            let res_idx = generator.gen_var_alloc(ctx, llvm_int64.into(), None)?;
            unsafe {
@ -1039,8 +1081,8 @@ pub fn call_numpy_maximum<'ctx, G: CodeGenerator + ?Sized>(
                ctx,
                dtype,
                None,
-                (x1, !is_ndarray1),
+                (x1_ty, x1, !is_ndarray1),
-                (x2, !is_ndarray2),
+                (x2_ty, x2, !is_ndarray2),
                |generator, ctx, (lhs, rhs)| {
                    call_numpy_maximum(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
                },
@ -1085,6 +1127,7 @@ where
        {
            let llvm_usize = generator.get_size_type(ctx.ctx);
            let (arg_elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, arg_ty);
            let llvm_arg_elem_ty = ctx.get_llvm_type(generator, arg_elem_ty);
            let ret_elem_ty = get_ret_elem_type(ctx, arg_elem_ty);
            let ndarray = ndarray_elementwise_unaryop_impl(
@ -1092,7 +1135,7 @@ where
                ctx,
                ret_elem_ty,
                None,
-                NDArrayValue::from_ptr_val(x, llvm_usize, None),
+                NDArrayValue::from_pointer_value(x, llvm_arg_elem_ty, llvm_usize, None),
                |generator, ctx, elem_val| {
                    helper_call_numpy_unary_elementwise(
                        generator,
@ -1479,8 +1522,8 @@ pub fn call_numpy_arctan2<'ctx, G: CodeGenerator + ?Sized>(
                ctx,
                dtype,
                None,
-                (x1, !is_ndarray1),
+                (x1_ty, x1, !is_ndarray1),
-                (x2, !is_ndarray2),
+                (x2_ty, x2, !is_ndarray2),
                |generator, ctx, (lhs, rhs)| {
                    call_numpy_arctan2(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
                },
@ -1546,8 +1589,8 @@ pub fn call_numpy_copysign<'ctx, G: CodeGenerator + ?Sized>(
                ctx,
                dtype,
                None,
-                (x1, !is_ndarray1),
+                (x1_ty, x1, !is_ndarray1),
-                (x2, !is_ndarray2),
+                (x2_ty, x2, !is_ndarray2),
                |generator, ctx, (lhs, rhs)| {
                    call_numpy_copysign(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
                },
@ -1613,8 +1656,8 @@ pub fn call_numpy_fmax<'ctx, G: CodeGenerator + ?Sized>(
                ctx,
                dtype,
                None,
-                (x1, !is_ndarray1),
+                (x1_ty, x1, !is_ndarray1),
-                (x2, !is_ndarray2),
+                (x2_ty, x2, !is_ndarray2),
                |generator, ctx, (lhs, rhs)| {
                    call_numpy_fmax(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
                },
@ -1680,8 +1723,8 @@ pub fn call_numpy_fmin<'ctx, G: CodeGenerator + ?Sized>(
                ctx,
                dtype,
                None,
-                (x1, !is_ndarray1),
+                (x1_ty, x1, !is_ndarray1),
-                (x2, !is_ndarray2),
+                (x2_ty, x2, !is_ndarray2),
                |generator, ctx, (lhs, rhs)| {
                    call_numpy_fmin(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
                },
@ -1736,8 +1779,8 @@ pub fn call_numpy_ldexp<'ctx, G: CodeGenerator + ?Sized>(
                ctx,
                dtype,
                None,
-                (x1, !is_ndarray1),
+                (x1_ty, x1, !is_ndarray1),
-                (x2, !is_ndarray2),
+                (x2_ty, x2, !is_ndarray2),
                |generator, ctx, (lhs, rhs)| {
                    call_numpy_ldexp(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
                },
@ -1803,8 +1846,8 @@ pub fn call_numpy_hypot<'ctx, G: CodeGenerator + ?Sized>(
                ctx,
                dtype,
                None,
-                (x1, !is_ndarray1),
+                (x1_ty, x1, !is_ndarray1),
-                (x2, !is_ndarray2),
+                (x2_ty, x2, !is_ndarray2),
                |generator, ctx, (lhs, rhs)| {
                    call_numpy_hypot(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
                },
@ -1870,8 +1913,8 @@ pub fn call_numpy_nextafter<'ctx, G: CodeGenerator + ?Sized>(
                ctx,
                dtype,
                None,
-                (x1, !is_ndarray1),
+                (x1_ty, x1, !is_ndarray1),
-                (x2, !is_ndarray2),
+                (x2_ty, x2, !is_ndarray2),
                |generator, ctx, (lhs, rhs)| {
                    call_numpy_nextafter(generator, ctx, (x1_scalar_ty, lhs), (x2_scalar_ty, rhs))
                },
@ -1931,14 +1974,14 @@ pub fn call_np_linalg_cholesky<'ctx, G: CodeGenerator + ?Sized>(
            unsupported_type(ctx, FN_NAME, &[x1_ty]);
        };
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+        let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, llvm_usize, None);
        let dim0 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
                .into_int_value()
        };
        let dim1 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
                .into_int_value()
        };
@ -1973,14 +2016,14 @@ pub fn call_np_linalg_qr<'ctx, G: CodeGenerator + ?Sized>(
            unimplemented!("{FN_NAME} operates on float type NdArrays only");
        };
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+        let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, llvm_usize, None);
        let dim0 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
                .into_int_value()
        };
        let dim1 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
                .into_int_value()
        };
@ -2023,15 +2066,15 @@ pub fn call_np_linalg_svd<'ctx, G: CodeGenerator + ?Sized>(
            unsupported_type(ctx, FN_NAME, &[x1_ty]);
        };
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+        let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, llvm_usize, None);
        let dim0 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
                .into_int_value()
        };
        let dim1 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
                .into_int_value()
        };
@ -2078,14 +2121,14 @@ pub fn call_np_linalg_inv<'ctx, G: CodeGenerator + ?Sized>(
            unsupported_type(ctx, FN_NAME, &[x1_ty]);
        };
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+        let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, llvm_usize, None);
        let dim0 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
                .into_int_value()
        };
        let dim1 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
                .into_int_value()
        };
@ -2120,15 +2163,15 @@ pub fn call_np_linalg_pinv<'ctx, G: CodeGenerator + ?Sized>(
            unsupported_type(ctx, FN_NAME, &[x1_ty]);
        };
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+        let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, llvm_usize, None);
        let dim0 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
                .into_int_value()
        };
        let dim1 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
                .into_int_value()
        };
@ -2163,15 +2206,15 @@ pub fn call_sp_linalg_lu<'ctx, G: CodeGenerator + ?Sized>(
            unsupported_type(ctx, FN_NAME, &[x1_ty]);
        };
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+        let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, llvm_usize, None);
        let dim0 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
                .into_int_value()
        };
        let dim1 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
                .into_int_value()
        };
@ -2216,7 +2259,7 @@ pub fn call_np_linalg_matrix_power<'ctx, G: CodeGenerator + ?Sized>(
            unsupported_type(ctx, FN_NAME, &[x1_ty, x2_ty]);
        };
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+        let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, llvm_usize, None);
        // Changing second parameter to a `NDArray` for uniformity in function call
        let n2_array = numpy::create_ndarray_const_shape(
            generator,
@ -2236,12 +2279,12 @@ pub fn call_np_linalg_matrix_power<'ctx, G: CodeGenerator + ?Sized>(
        let n2_array = n2_array.as_base_value().as_basic_value_enum();
        let outdim0 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
                .into_int_value()
        };
        let outdim1 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
                .into_int_value()
        };
@ -2311,10 +2354,10 @@ pub fn call_sp_linalg_schur<'ctx, G: CodeGenerator + ?Sized>(
            unsupported_type(ctx, FN_NAME, &[x1_ty]);
        };
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+        let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, llvm_usize, None);
        let dim0 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
                .into_int_value()
        };
@ -2354,10 +2397,10 @@ pub fn call_sp_linalg_hessenberg<'ctx, G: CodeGenerator + ?Sized>(
            unsupported_type(ctx, FN_NAME, &[x1_ty]);
        };
-        let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
+        let n1 = NDArrayValue::from_pointer_value(n1, n1_elem_ty, llvm_usize, None);
        let dim0 = unsafe {
-            n1.dim_sizes()
+            n1.shape()
                .get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
                .into_int_value()
        };
--- a/nac3core/src/codegen/classes.rs
+++ b/nac3core/src/codegen/classes.rs
--- a/nac3core/src/codegen/concrete_type.rs
+++ b/nac3core/src/codegen/concrete_type.rs
@ -1,3 +1,9 @@
 use std::collections::HashMap;
 use indexmap::IndexMap;
 use nac3parser::ast::StrRef;
 use crate::{
    symbol_resolver::SymbolValue,
    toplevel::DefinitionId,
@ -9,10 +15,6 @@ use crate::{
    },
 };
 use indexmap::IndexMap;
 use nac3parser::ast::StrRef;
 use std::collections::HashMap;
 pub struct ConcreteTypeStore {
    store: Vec<ConcreteTypeEnum>,
 }
--- a/nac3core/src/codegen/expr.rs
+++ b/nac3core/src/codegen/expr.rs
@ -1,9 +1,24 @@
-use crate::{
+use std::{
-    codegen::{
+    cmp::min,
-        classes::{
+    collections::HashMap,
-            ArrayLikeIndexer, ArrayLikeValue, ListType, ListValue, NDArrayValue, ProxyType,
+    convert::TryInto,
-            ProxyValue, RangeValue, UntypedArrayLikeAccessor,
+    iter::{once, repeat, repeat_with, zip},
-        },
+};
 use inkwell::{
    attributes::{Attribute, AttributeLoc},
    types::{AnyType, BasicType, BasicTypeEnum},
    values::{BasicValueEnum, CallSiteValue, FunctionValue, IntValue, PointerValue, StructValue},
    AddressSpace, IntPredicate, OptimizationLevel,
 };
 use itertools::{chain, izip, Either, Itertools};
 use nac3parser::ast::{
    self, Boolop, Cmpop, Comprehension, Constant, Expr, ExprKind, Location, Operator, StrRef,
    Unaryop,
 };
 use super::{
    concrete_type::{ConcreteFuncArg, ConcreteTypeEnum, ConcreteTypeStore},
    gen_in_range_check, get_llvm_abi_type, get_llvm_type, get_va_count_arg_name,
    irrt::*,
@ -17,34 +32,25 @@ use crate::{
        gen_for_callback_incrementing, gen_if_callback, gen_if_else_expr_callback, gen_raise,
        gen_var,
    },
-        CodeGenContext, CodeGenTask, CodeGenerator,
+    types::{ListType, ProxyType},
    values::{
        ArrayLikeIndexer, ArrayLikeValue, ListValue, NDArrayValue, ProxyValue, RangeValue,
        TypedArrayLikeAccessor, UntypedArrayLikeAccessor,
    },
    CodeGenContext, CodeGenTask, CodeGenerator,
 };
 use crate::{
    symbol_resolver::{SymbolValue, ValueEnum},
-    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId, TopLevelDef},
+    toplevel::{
        helper::PrimDef,
        numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
        DefinitionId, TopLevelDef,
    },
    typecheck::{
        magic_methods::{Binop, BinopVariant, HasOpInfo},
        typedef::{FunSignature, FuncArg, Type, TypeEnum, TypeVarId, Unifier, VarMap},
    },
 };
 use inkwell::{
    attributes::{Attribute, AttributeLoc},
    types::{AnyType, BasicType, BasicTypeEnum},
    values::{BasicValueEnum, CallSiteValue, FunctionValue, IntValue, PointerValue, StructValue},
    AddressSpace, IntPredicate, OptimizationLevel,
 };
 use itertools::{chain, izip, Either, Itertools};
 use nac3parser::ast::{
    self, Boolop, Cmpop, Comprehension, Constant, Expr, ExprKind, Location, Operator, StrRef,
    Unaryop,
 };
 use std::cmp::min;
 use std::iter::{repeat, repeat_with};
 use std::{collections::HashMap, convert::TryInto, iter::once, iter::zip};
 use super::object::{
    any::AnyObject,
    ndarray::{indexing::util::gen_ndarray_subscript_ndindices, NDArrayObject},
 };
 pub fn get_subst_key(
    unifier: &mut Unifier,
@ -552,7 +558,7 @@ impl<'ctx, 'a> CodeGenContext<'ctx, 'a> {
                            && val_ty.get_element_type().is_struct_type()
                    } =>
                {
-                    self.builder.build_bitcast(*val, arg_ty, "call_arg_cast").unwrap()
+                    self.builder.build_bit_cast(*val, arg_ty, "call_arg_cast").unwrap()
                }
                _ => *val,
            })
@ -972,6 +978,7 @@ pub fn gen_call<'ctx, G: CodeGenerator>(
            TopLevelDef::Class { .. } => {
                return Ok(Some(generator.gen_constructor(ctx, fun.0, &def, params)?))
            }
            TopLevelDef::Variable { .. } => unreachable!(),
        }
    }
    .or_else(|_: String| {
@ -1161,7 +1168,8 @@ pub fn gen_comprehension<'ctx, G: CodeGenerator>(
        TypeEnum::TObj { obj_id, .. }
            if *obj_id == ctx.primitives.range.obj_id(&ctx.unifier).unwrap() =>
        {
-            let iter_val = RangeValue::from_ptr_val(iter_val.into_pointer_value(), Some("range"));
+            let iter_val =
                RangeValue::from_pointer_value(iter_val.into_pointer_value(), Some("range"));
            let (start, stop, step) = destructure_range(ctx, iter_val);
            let diff = ctx.builder.build_int_sub(stop, start, "diff").unwrap();
            // add 1 to the length as the value is rounded to zero
@ -1392,8 +1400,10 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
                let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty1);
                let sizeof_elem = llvm_elem_ty.size_of().unwrap();
-                let lhs = ListValue::from_ptr_val(left_val.into_pointer_value(), llvm_usize, None);
+                let lhs =
-                let rhs = ListValue::from_ptr_val(right_val.into_pointer_value(), llvm_usize, None);
+                    ListValue::from_pointer_value(left_val.into_pointer_value(), llvm_usize, None);
                let rhs =
                    ListValue::from_pointer_value(right_val.into_pointer_value(), llvm_usize, None);
                let size = ctx
                    .builder
@ -1476,7 +1486,7 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
                        codegen_unreachable!(ctx)
                    };
                let list_val =
-                    ListValue::from_ptr_val(list_val.into_pointer_value(), llvm_usize, None);
+                    ListValue::from_pointer_value(list_val.into_pointer_value(), llvm_usize, None);
                let int_val = ctx
                    .builder
                    .build_int_s_extend(int_val.into_int_value(), llvm_usize, "")
@ -1554,10 +1564,21 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
            assert!(ctx.unifier.unioned(ndarray_dtype1, ndarray_dtype2));
-            let left_val =
+            let llvm_ndarray_dtype1 = ctx.get_llvm_type(generator, ndarray_dtype1);
-                NDArrayValue::from_ptr_val(left_val.into_pointer_value(), llvm_usize, None);
+            let llvm_ndarray_dtype2 = ctx.get_llvm_type(generator, ndarray_dtype2);
-            let right_val =
+
-                NDArrayValue::from_ptr_val(right_val.into_pointer_value(), llvm_usize, None);
+            let left_val = NDArrayValue::from_pointer_value(
                left_val.into_pointer_value(),
                llvm_ndarray_dtype1,
                llvm_usize,
                None,
            );
            let right_val = NDArrayValue::from_pointer_value(
                right_val.into_pointer_value(),
                llvm_ndarray_dtype2,
                llvm_usize,
                None,
            );
            let res = if op.base == Operator::MatMult {
                // MatMult is the only binop which is not an elementwise op
@ -1581,8 +1602,8 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
                        BinopVariant::Normal => None,
                        BinopVariant::AugAssign => Some(left_val),
                    },
-                    (left_val.as_base_value().into(), false),
+                    (ty1, left_val.as_base_value().into(), false),
-                    (right_val.as_base_value().into(), false),
+                    (ty2, right_val.as_base_value().into(), false),
                    |generator, ctx, (lhs, rhs)| {
                        gen_binop_expr_with_values(
                            generator,
@ -1606,8 +1627,10 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
        } else {
            let (ndarray_dtype, _) =
                unpack_ndarray_var_tys(&mut ctx.unifier, if is_ndarray1 { ty1 } else { ty2 });
-            let ndarray_val = NDArrayValue::from_ptr_val(
+            let llvm_ndarray_dtype = ctx.get_llvm_type(generator, ndarray_dtype);
            let ndarray_val = NDArrayValue::from_pointer_value(
                if is_ndarray1 { left_val } else { right_val }.into_pointer_value(),
                llvm_ndarray_dtype,
                llvm_usize,
                None,
            );
@ -1619,8 +1642,8 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
                    BinopVariant::Normal => None,
                    BinopVariant::AugAssign => Some(ndarray_val),
                },
-                (left_val, !is_ndarray1),
+                (ty1, left_val, !is_ndarray1),
-                (right_val, !is_ndarray2),
+                (ty2, right_val, !is_ndarray2),
                |generator, ctx, (lhs, rhs)| {
                    gen_binop_expr_with_values(
                        generator,
@ -1771,7 +1794,12 @@ pub fn gen_unaryop_expr_with_values<'ctx, G: CodeGenerator>(
            ast::Unaryop::Invert => ctx.builder.build_not(val, "not").map(Into::into).unwrap(),
            ast::Unaryop::Not => ctx
                .builder
-                .build_xor(val, val.get_type().const_all_ones(), "not")
+                .build_int_compare(
                    inkwell::IntPredicate::EQ,
                    val,
                    val.get_type().const_zero(),
                    "not",
                )
                .map(Into::into)
                .unwrap(),
            ast::Unaryop::UAdd => val.into(),
@ -1795,8 +1823,14 @@ pub fn gen_unaryop_expr_with_values<'ctx, G: CodeGenerator>(
    } else if ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) {
        let llvm_usize = generator.get_size_type(ctx.ctx);
        let (ndarray_dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
        let llvm_ndarray_dtype = ctx.get_llvm_type(generator, ndarray_dtype);
-        let val = NDArrayValue::from_ptr_val(val.into_pointer_value(), llvm_usize, None);
+        let val = NDArrayValue::from_pointer_value(
            val.into_pointer_value(),
            llvm_ndarray_dtype,
            llvm_usize,
            None,
        );
        // ndarray uses `~` rather than `not` to perform elementwise inversion, convert it before
        // passing it to the elementwise codegen function
@ -1887,15 +1921,21 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
                assert!(ctx.unifier.unioned(ndarray_dtype1, ndarray_dtype2));
-                let left_val =
+                let llvm_ndarray_dtype1 = ctx.get_llvm_type(generator, ndarray_dtype1);
-                    NDArrayValue::from_ptr_val(lhs.into_pointer_value(), llvm_usize, None);
+
                let left_val = NDArrayValue::from_pointer_value(
                    lhs.into_pointer_value(),
                    llvm_ndarray_dtype1,
                    llvm_usize,
                    None,
                );
                let res = numpy::ndarray_elementwise_binop_impl(
                    generator,
                    ctx,
                    ctx.primitives.bool,
                    None,
-                    (left_val.as_base_value().into(), false),
+                    (left_ty, left_val.as_base_value().into(), false),
-                    (rhs, false),
+                    (right_ty, rhs, false),
                    |generator, ctx, (lhs, rhs)| {
                        let val = gen_cmpop_expr_with_values(
                            generator,
@ -1926,8 +1966,8 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
                    ctx,
                    ctx.primitives.bool,
                    None,
-                    (lhs, !is_ndarray1),
+                    (left_ty, lhs, !is_ndarray1),
-                    (rhs, !is_ndarray2),
+                    (right_ty, rhs, !is_ndarray2),
                    |generator, ctx, (lhs, rhs)| {
                        let val = gen_cmpop_expr_with_values(
                            generator,
@ -2190,9 +2230,9 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
                    }
                    let left_val =
-                        ListValue::from_ptr_val(lhs.into_pointer_value(), llvm_usize, None);
+                        ListValue::from_pointer_value(lhs.into_pointer_value(), llvm_usize, None);
                    let right_val =
-                        ListValue::from_ptr_val(rhs.into_pointer_value(), llvm_usize, None);
+                        ListValue::from_pointer_value(rhs.into_pointer_value(), llvm_usize, None);
                    Ok(gen_if_else_expr_callback(
                        generator,
@ -2499,6 +2539,343 @@ pub fn gen_cmpop_expr<'ctx, G: CodeGenerator>(
    )
 }
 /// Generates code for a subscript expression on an `ndarray`.
 ///
 /// * `ty` - The `Type` of the `NDArray` elements.
 /// * `ndims` - The `Type` of the `NDArray` number-of-dimensions `Literal`.
 /// * `v` - The `NDArray` value.
 /// * `slice` - The slice expression used to subscript into the `ndarray`.
 fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
    ty: Type,
    ndims: Type,
    v: NDArrayValue<'ctx>,
    slice: &Expr<Option<Type>>,
 ) -> Result<Option<ValueEnum<'ctx>>, String> {
    let llvm_i1 = ctx.ctx.bool_type();
    let llvm_i32 = ctx.ctx.i32_type();
    let llvm_usize = generator.get_size_type(ctx.ctx);
    let TypeEnum::TLiteral { values, .. } = &*ctx.unifier.get_ty_immutable(ndims) else {
        codegen_unreachable!(ctx)
    };
    let ndims = values
        .iter()
        .map(|ndim| u64::try_from(ndim.clone()).map_err(|()| ndim.clone()))
        .collect::<Result<Vec<_>, _>>()
        .map_err(|val| {
            format!(
                "Expected non-negative literal for ndarray.ndims, got {}",
                i128::try_from(val).unwrap()
            )
        })?;
    assert!(!ndims.is_empty());
    // The number of dimensions subscripted by the index expression.
    // Slicing a ndarray will yield the same number of dimensions, whereas indexing into a
    // dimension will remove a dimension.
    let subscripted_dims = match &slice.node {
        ExprKind::Tuple { elts, .. } => elts.iter().fold(0, |acc, value_subexpr| {
            if let ExprKind::Slice { .. } = &value_subexpr.node {
                acc
            } else {
                acc + 1
            }
        }),
        ExprKind::Slice { .. } => 0,
        _ => 1,
    };
    let ndarray_ndims_ty = ctx.unifier.get_fresh_literal(
        ndims.iter().map(|v| SymbolValue::U64(v - subscripted_dims)).collect(),
        None,
    );
    let ndarray_ty =
        make_ndarray_ty(&mut ctx.unifier, &ctx.primitives, Some(ty), Some(ndarray_ndims_ty));
    let llvm_pndarray_t = ctx.get_llvm_type(generator, ndarray_ty).into_pointer_type();
    let llvm_ndarray_t = llvm_pndarray_t.get_element_type().into_struct_type();
    let llvm_ndarray_data_t = ctx.get_llvm_type(generator, ty).as_basic_type_enum();
    let sizeof_elem = llvm_ndarray_data_t.size_of().unwrap();
    // Check that len is non-zero
    let len = v.load_ndims(ctx);
    ctx.make_assert(
        generator,
        ctx.builder.build_int_compare(IntPredicate::SGT, len, llvm_usize.const_zero(), "").unwrap(),
        "0:IndexError",
        "too many indices for array: array is {0}-dimensional but 1 were indexed",
        [Some(len), None, None],
        slice.location,
    );
    // Normalizes a possibly-negative index to its corresponding positive index
    let normalize_index = |generator: &mut G,
                           ctx: &mut CodeGenContext<'ctx, '_>,
                           index: IntValue<'ctx>,
                           dim: u64| {
        gen_if_else_expr_callback(
            generator,
            ctx,
            |_, ctx| {
                Ok(ctx
                    .builder
                    .build_int_compare(IntPredicate::SGE, index, index.get_type().const_zero(), "")
                    .unwrap())
            },
            |_, _| Ok(Some(index)),
            |generator, ctx| {
                let llvm_i32 = ctx.ctx.i32_type();
                let len = unsafe {
                    v.shape().get_typed_unchecked(
                        ctx,
                        generator,
                        &llvm_usize.const_int(dim, true),
                        None,
                    )
                };
                let index = ctx
                    .builder
                    .build_int_add(
                        len,
                        ctx.builder.build_int_s_extend(index, llvm_usize, "").unwrap(),
                        "",
                    )
                    .unwrap();
                Ok(Some(ctx.builder.build_int_truncate(index, llvm_i32, "").unwrap()))
            },
        )
        .map(|v| v.map(BasicValueEnum::into_int_value))
    };
    // Converts a slice expression into a slice-range tuple
    let expr_to_slice = |generator: &mut G,
                         ctx: &mut CodeGenContext<'ctx, '_>,
                         node: &ExprKind<Option<Type>>,
                         dim: u64| {
        match node {
            ExprKind::Constant { value: Constant::Int(v), .. } => {
                let Some(index) =
                    normalize_index(generator, ctx, llvm_i32.const_int(*v as u64, true), dim)?
                else {
                    return Ok(None);
                };
                Ok(Some((index, index, llvm_i32.const_int(1, true))))
            }
            ExprKind::Slice { lower, upper, step } => {
                let dim_sz = unsafe {
                    v.shape().get_typed_unchecked(
                        ctx,
                        generator,
                        &llvm_usize.const_int(dim, false),
                        None,
                    )
                };
                handle_slice_indices(lower, upper, step, ctx, generator, dim_sz)
            }
            _ => {
                let Some(index) = generator.gen_expr(ctx, slice)? else { return Ok(None) };
                let index = index
                    .to_basic_value_enum(ctx, generator, slice.custom.unwrap())?
                    .into_int_value();
                let Some(index) = normalize_index(generator, ctx, index, dim)? else {
                    return Ok(None);
                };
                Ok(Some((index, index, llvm_i32.const_int(1, true))))
            }
        }
    };
    let make_indices_arr = |generator: &mut G,
                            ctx: &mut CodeGenContext<'ctx, '_>|
     -> Result<_, String> {
        Ok(if let ExprKind::Tuple { elts, .. } = &slice.node {
            let llvm_int_ty = ctx.get_llvm_type(generator, elts[0].custom.unwrap());
            let index_addr = generator.gen_array_var_alloc(
                ctx,
                llvm_int_ty,
                llvm_usize.const_int(elts.len() as u64, false),
                None,
            )?;
            for (i, elt) in elts.iter().enumerate() {
                let Some(index) = generator.gen_expr(ctx, elt)? else {
                    return Ok(None);
                };
                let index = index
                    .to_basic_value_enum(ctx, generator, elt.custom.unwrap())?
                    .into_int_value();
                let Some(index) = normalize_index(generator, ctx, index, 0)? else {
                    return Ok(None);
                };
                let store_ptr = unsafe {
                    index_addr.ptr_offset_unchecked(
                        ctx,
                        generator,
                        &llvm_usize.const_int(i as u64, false),
                        None,
                    )
                };
                ctx.builder.build_store(store_ptr, index).unwrap();
            }
            Some(index_addr)
        } else if let Some(index) = generator.gen_expr(ctx, slice)? {
            let llvm_int_ty = ctx.get_llvm_type(generator, slice.custom.unwrap());
            let index_addr = generator.gen_array_var_alloc(
                ctx,
                llvm_int_ty,
                llvm_usize.const_int(1u64, false),
                None,
            )?;
            let index =
                index.to_basic_value_enum(ctx, generator, slice.custom.unwrap())?.into_int_value();
            let Some(index) = normalize_index(generator, ctx, index, 0)? else { return Ok(None) };
            let store_ptr = unsafe {
                index_addr.ptr_offset_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
            };
            ctx.builder.build_store(store_ptr, index).unwrap();
            Some(index_addr)
        } else {
            None
        })
    };
    Ok(Some(if ndims.len() == 1 && ndims[0] - subscripted_dims == 0 {
        let Some(index_addr) = make_indices_arr(generator, ctx)? else { return Ok(None) };
        v.data().get(ctx, generator, &index_addr, None).into()
    } else {
        match &slice.node {
            ExprKind::Tuple { elts, .. } => {
                let slices = elts
                    .iter()
                    .enumerate()
                    .map(|(dim, elt)| expr_to_slice(generator, ctx, &elt.node, dim as u64))
                    .take_while_inclusive(|slice| slice.as_ref().is_ok_and(Option::is_some))
                    .collect::<Result<Vec<_>, _>>()?;
                if slices.len() < elts.len() {
                    return Ok(None);
                }
                let slices = slices.into_iter().map(Option::unwrap).collect_vec();
                numpy::ndarray_sliced_copy(generator, ctx, ty, v, &slices)?.as_base_value().into()
            }
            ExprKind::Slice { .. } => {
                let Some(slice) = expr_to_slice(generator, ctx, &slice.node, 0)? else {
                    return Ok(None);
                };
                numpy::ndarray_sliced_copy(generator, ctx, ty, v, &[slice])?.as_base_value().into()
            }
            _ => {
                // Accessing an element from a multi-dimensional `ndarray`
                let Some(index_addr) = make_indices_arr(generator, ctx)? else { return Ok(None) };
                // Create a new array, remove the top dimension from the dimension-size-list, and copy the
                // elements over
                let subscripted_ndarray =
                    generator.gen_var_alloc(ctx, llvm_ndarray_t.into(), None)?;
                let ndarray = NDArrayValue::from_pointer_value(
                    subscripted_ndarray,
                    llvm_ndarray_data_t,
                    llvm_usize,
                    None,
                );
                let num_dims = v.load_ndims(ctx);
                ndarray.store_ndims(
                    ctx,
                    generator,
                    ctx.builder
                        .build_int_sub(num_dims, llvm_usize.const_int(1, false), "")
                        .unwrap(),
                );
                let ndarray_num_dims = ndarray.load_ndims(ctx);
                ndarray.create_shape(ctx, llvm_usize, ndarray_num_dims);
                let ndarray_num_dims = ctx
                    .builder
                    .build_int_z_extend_or_bit_cast(
                        ndarray.load_ndims(ctx),
                        llvm_usize.size_of().get_type(),
                        "",
                    )
                    .unwrap();
                let v_dims_src_ptr = unsafe {
                    v.shape().ptr_offset_unchecked(
                        ctx,
                        generator,
                        &llvm_usize.const_int(1, false),
                        None,
                    )
                };
                call_memcpy_generic(
                    ctx,
                    ndarray.shape().base_ptr(ctx, generator),
                    v_dims_src_ptr,
                    ctx.builder
                        .build_int_mul(ndarray_num_dims, llvm_usize.size_of(), "")
                        .map(Into::into)
                        .unwrap(),
                    llvm_i1.const_zero(),
                );
                let ndarray_num_elems = call_ndarray_calc_size(
                    generator,
                    ctx,
                    &ndarray.shape().as_slice_value(ctx, generator),
                    (None, None),
                );
                let ndarray_num_elems = ctx
                    .builder
                    .build_int_z_extend_or_bit_cast(ndarray_num_elems, sizeof_elem.get_type(), "")
                    .unwrap();
                ndarray.create_data(ctx, llvm_ndarray_data_t, ndarray_num_elems);
                let v_data_src_ptr = v.data().ptr_offset(ctx, generator, &index_addr, None);
                call_memcpy_generic(
                    ctx,
                    ndarray.data().base_ptr(ctx, generator),
                    v_data_src_ptr,
                    ctx.builder
                        .build_int_mul(
                            ndarray_num_elems,
                            llvm_ndarray_data_t.size_of().unwrap(),
                            "",
                        )
                        .map(Into::into)
                        .unwrap(),
                    llvm_i1.const_zero(),
                );
                ndarray.as_base_value().into()
            }
        }
    }))
 }
 /// See [`CodeGenerator::gen_expr`].
 pub fn gen_expr<'ctx, G: CodeGenerator>(
    generator: &mut G,
@ -2548,7 +2925,31 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
            Some((_, Some(static_value), _)) => ValueEnum::Static(static_value.clone()),
            None => {
                let resolver = ctx.resolver.clone();
-                resolver.get_symbol_value(*id, ctx).unwrap()
+                let value = resolver.get_symbol_value(*id, ctx, generator).unwrap();
                let globals = ctx
                    .top_level
                    .definitions
                    .read()
                    .iter()
                    .filter_map(|def| {
                        if let TopLevelDef::Variable { simple_name, ty, .. } = &*def.read() {
                            Some((*simple_name, *ty))
                        } else {
                            None
                        }
                    })
                    .collect_vec();
                if let Some((_, ty)) = globals.iter().find(|(name, _)| name == id) {
                    let ptr = value
                        .to_basic_value_enum(ctx, generator, *ty)
                        .map(BasicValueEnum::into_pointer_value)?;
                    ctx.builder.build_load(ptr, id.to_string().as_str()).map(Into::into).unwrap()
                } else {
                    value
                }
            }
        },
        ExprKind::List { elts, .. } => {
@ -2741,48 +3142,53 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
            };
            let left = generator.bool_to_i1(ctx, left);
            let current = ctx.builder.get_insert_block().unwrap().get_parent().unwrap();
-            let a_bb = ctx.ctx.append_basic_block(current, "a");
+            let a_begin_bb = ctx.ctx.append_basic_block(current, "a_begin");
-            let b_bb = ctx.ctx.append_basic_block(current, "b");
+            let a_end_bb = ctx.ctx.append_basic_block(current, "a_end");
            let b_begin_bb = ctx.ctx.append_basic_block(current, "b_begin");
            let b_end_bb = ctx.ctx.append_basic_block(current, "b_end");
            let cont_bb = ctx.ctx.append_basic_block(current, "cont");
-            ctx.builder.build_conditional_branch(left, a_bb, b_bb).unwrap();
+            ctx.builder.build_conditional_branch(left, a_begin_bb, b_begin_bb).unwrap();
            ctx.builder.position_at_end(a_end_bb);
            ctx.builder.build_unconditional_branch(cont_bb).unwrap();
            ctx.builder.position_at_end(b_end_bb);
            ctx.builder.build_unconditional_branch(cont_bb).unwrap();
            let (a, b) = match op {
                Boolop::Or => {
-                    ctx.builder.position_at_end(a_bb);
+                    ctx.builder.position_at_end(a_begin_bb);
                    let a = ctx.ctx.i8_type().const_int(1, false);
-                    ctx.builder.build_unconditional_branch(cont_bb).unwrap();
+                    ctx.builder.build_unconditional_branch(a_end_bb).unwrap();
-                    ctx.builder.position_at_end(b_bb);
+                    ctx.builder.position_at_end(b_begin_bb);
                    let b = if let Some(v) = generator.gen_expr(ctx, &values[1])? {
                        let b = v
                            .to_basic_value_enum(ctx, generator, values[1].custom.unwrap())?
                            .into_int_value();
                        let b = generator.bool_to_i8(ctx, b);
                        ctx.builder.build_unconditional_branch(cont_bb).unwrap();
                        Some(b)
                    } else {
                        None
                    };
                    ctx.builder.build_unconditional_branch(b_end_bb).unwrap();
                    (Some(a), b)
                }
                Boolop::And => {
-                    ctx.builder.position_at_end(a_bb);
+                    ctx.builder.position_at_end(a_begin_bb);
                    let a = if let Some(v) = generator.gen_expr(ctx, &values[1])? {
                        let a = v
                            .to_basic_value_enum(ctx, generator, values[1].custom.unwrap())?
                            .into_int_value();
                        let a = generator.bool_to_i8(ctx, a);
                        ctx.builder.build_unconditional_branch(cont_bb).unwrap();
                        Some(a)
                    } else {
                        None
                    };
                    ctx.builder.build_unconditional_branch(a_end_bb).unwrap();
-                    ctx.builder.position_at_end(b_bb);
+                    ctx.builder.position_at_end(b_begin_bb);
                    let b = ctx.ctx.i8_type().const_zero();
-                    ctx.builder.build_unconditional_branch(cont_bb).unwrap();
+                    ctx.builder.build_unconditional_branch(b_end_bb).unwrap();
                    (a, Some(b))
                }
@ -2792,7 +3198,7 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
            match (a, b) {
                (Some(a), Some(b)) => {
                    let phi = ctx.builder.build_phi(ctx.ctx.i8_type(), "").unwrap();
-                    phi.add_incoming(&[(&a, a_bb), (&b, b_bb)]);
+                    phi.add_incoming(&[(&a, a_end_bb), (&b, b_end_bb)]);
                    phi.as_basic_value().into()
                }
                (Some(a), None) => a.into(),
@ -3030,7 +3436,7 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
                    } else {
                        return Ok(None);
                    };
-                    let v = ListValue::from_ptr_val(v, usize, Some("arr"));
+                    let v = ListValue::from_pointer_value(v, usize, Some("arr"));
                    let ty = ctx.get_llvm_type(generator, *ty);
                    if let ExprKind::Slice { lower, upper, step } = &slice.node {
                        let one = int32.const_int(1, false);
@ -3131,26 +3537,19 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
                        v.data().get(ctx, generator, &index, None).into()
                    }
                }
-                TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
+                TypeEnum::TObj { obj_id, params, .. } if *obj_id == PrimDef::NDArray.id() => {
-                    let Some(ndarray) = generator.gen_expr(ctx, value)? else {
+                    let (ty, ndims) = params.iter().map(|(_, ty)| ty).collect_tuple().unwrap();
                    let llvm_ty = ctx.get_llvm_type(generator, *ty);
                    let v = if let Some(v) = generator.gen_expr(ctx, value)? {
                        v.to_basic_value_enum(ctx, generator, value.custom.unwrap())?
                            .into_pointer_value()
                    } else {
                        return Ok(None);
                    };
                    let v = NDArrayValue::from_pointer_value(v, llvm_ty, usize, None);
-                    let ndarray_ty = value.custom.unwrap();
+                    return gen_ndarray_subscript_expr(generator, ctx, *ty, *ndims, v, slice);
                    let ndarray = ndarray.to_basic_value_enum(ctx, generator, ndarray_ty)?;
                    let ndarray = NDArrayObject::from_object(
                        generator,
                        ctx,
                        AnyObject { ty: ndarray_ty, value: ndarray },
                    );
                    let indices = gen_ndarray_subscript_ndindices(generator, ctx, slice)?;
                    let result = ndarray
                        .index(generator, ctx, &indices)
                        .split_unsized(generator, ctx)
                        .to_basic_value_enum();
                    return Ok(Some(ValueEnum::Dynamic(result)));
                }
                TypeEnum::TTuple { .. } => {
                    let index: u32 =
--- a/nac3core/src/codegen/extern_fns.rs
+++ b/nac3core/src/codegen/extern_fns.rs
@ -1,8 +1,10 @@
-use inkwell::attributes::{Attribute, AttributeLoc};
+use inkwell::{
-use inkwell::values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue};
+    attributes::{Attribute, AttributeLoc},
    values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue},
 };
 use itertools::Either;
-use crate::codegen::CodeGenContext;
+use super::CodeGenContext;
 /// Macro to generate extern function
 /// Both function return type and function parameter type are `FloatValue`
--- a/nac3core/src/codegen/generator.rs
+++ b/nac3core/src/codegen/generator.rs
@ -1,16 +1,18 @@
 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, expr::*, stmt::*, values::ArraySliceValue, CodeGenContext};
 use crate::{
    symbol_resolver::ValueEnum,
    toplevel::{DefinitionId, TopLevelDef},
    typecheck::typedef::{FunSignature, Type},
 };
 pub trait CodeGenerator {
    /// Return the module name for the code generator.
    fn get_name(&self) -> &str;
--- a/nac3core/src/codegen/irrt/list.rs
+++ b/nac3core/src/codegen/irrt/list.rs
@ -0,0 +1,162 @@
 use inkwell::{
    types::BasicTypeEnum,
    values::{BasicValueEnum, CallSiteValue, IntValue},
    AddressSpace, IntPredicate,
 };
 use itertools::Either;
 use super::calculate_len_for_slice_range;
 use crate::codegen::{
    macros::codegen_unreachable,
    values::{ArrayLikeValue, ListValue},
    CodeGenContext, CodeGenerator,
 };
 /// This function handles 'end' **inclusively**.
 /// Order of tuples `assign_idx` and `value_idx` is ('start', 'end', 'step').
 /// Negative index should be handled before entering this function
 pub fn list_slice_assignment<'ctx, G: CodeGenerator + ?Sized>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
    ty: BasicTypeEnum<'ctx>,
    dest_arr: ListValue<'ctx>,
    dest_idx: (IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>),
    src_arr: ListValue<'ctx>,
    src_idx: (IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>),
 ) {
    let size_ty = generator.get_size_type(ctx.ctx);
    let int8_ptr = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
    let int32 = ctx.ctx.i32_type();
    let (fun_symbol, elem_ptr_type) = ("__nac3_list_slice_assign_var_size", int8_ptr);
    let slice_assign_fun = {
        let ty_vec = vec![
            int32.into(),         // dest start idx
            int32.into(),         // dest end idx
            int32.into(),         // dest step
            elem_ptr_type.into(), // dest arr ptr
            int32.into(),         // dest arr len
            int32.into(),         // src start idx
            int32.into(),         // src end idx
            int32.into(),         // src step
            elem_ptr_type.into(), // src arr ptr
            int32.into(),         // src arr len
            int32.into(),         // size
        ];
        ctx.module.get_function(fun_symbol).unwrap_or_else(|| {
            let fn_t = int32.fn_type(ty_vec.as_slice(), false);
            ctx.module.add_function(fun_symbol, fn_t, None)
        })
    };
    let zero = int32.const_zero();
    let one = int32.const_int(1, false);
    let dest_arr_ptr = dest_arr.data().base_ptr(ctx, generator);
    let dest_arr_ptr =
        ctx.builder.build_pointer_cast(dest_arr_ptr, elem_ptr_type, "dest_arr_ptr_cast").unwrap();
    let dest_len = dest_arr.load_size(ctx, Some("dest.len"));
    let dest_len = ctx.builder.build_int_truncate_or_bit_cast(dest_len, int32, "srclen32").unwrap();
    let src_arr_ptr = src_arr.data().base_ptr(ctx, generator);
    let src_arr_ptr =
        ctx.builder.build_pointer_cast(src_arr_ptr, elem_ptr_type, "src_arr_ptr_cast").unwrap();
    let src_len = src_arr.load_size(ctx, Some("src.len"));
    let src_len = ctx.builder.build_int_truncate_or_bit_cast(src_len, int32, "srclen32").unwrap();
    // index in bound and positive should be done
    // assert if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest), and
    // throw exception if not satisfied
    let src_end = ctx
        .builder
        .build_select(
            ctx.builder.build_int_compare(IntPredicate::SLT, src_idx.2, zero, "is_neg").unwrap(),
            ctx.builder.build_int_sub(src_idx.1, one, "e_min_one").unwrap(),
            ctx.builder.build_int_add(src_idx.1, one, "e_add_one").unwrap(),
            "final_e",
        )
        .map(BasicValueEnum::into_int_value)
        .unwrap();
    let dest_end = ctx
        .builder
        .build_select(
            ctx.builder.build_int_compare(IntPredicate::SLT, dest_idx.2, zero, "is_neg").unwrap(),
            ctx.builder.build_int_sub(dest_idx.1, one, "e_min_one").unwrap(),
            ctx.builder.build_int_add(dest_idx.1, one, "e_add_one").unwrap(),
            "final_e",
        )
        .map(BasicValueEnum::into_int_value)
        .unwrap();
    let src_slice_len =
        calculate_len_for_slice_range(generator, ctx, src_idx.0, src_end, src_idx.2);
    let dest_slice_len =
        calculate_len_for_slice_range(generator, ctx, dest_idx.0, dest_end, dest_idx.2);
    let src_eq_dest = ctx
        .builder
        .build_int_compare(IntPredicate::EQ, src_slice_len, dest_slice_len, "slice_src_eq_dest")
        .unwrap();
    let src_slt_dest = ctx
        .builder
        .build_int_compare(IntPredicate::SLT, src_slice_len, dest_slice_len, "slice_src_slt_dest")
        .unwrap();
    let dest_step_eq_one = ctx
        .builder
        .build_int_compare(
            IntPredicate::EQ,
            dest_idx.2,
            dest_idx.2.get_type().const_int(1, false),
            "slice_dest_step_eq_one",
        )
        .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,
        cond,
        "0:ValueError",
        "attempt to assign sequence of size {0} to slice of size {1} with step size {2}",
        [Some(src_slice_len), Some(dest_slice_len), Some(dest_idx.2)],
        ctx.current_loc,
    );
    let new_len = {
        let args = vec![
            dest_idx.0.into(),   // dest start idx
            dest_idx.1.into(),   // dest end idx
            dest_idx.2.into(),   // dest step
            dest_arr_ptr.into(), // dest arr ptr
            dest_len.into(),     // dest arr len
            src_idx.0.into(),    // src start idx
            src_idx.1.into(),    // src end idx
            src_idx.2.into(),    // src step
            src_arr_ptr.into(),  // src arr ptr
            src_len.into(),      // src arr len
            {
                let s = match ty {
                    BasicTypeEnum::FloatType(t) => t.size_of(),
                    BasicTypeEnum::IntType(t) => t.size_of(),
                    BasicTypeEnum::PointerType(t) => t.size_of(),
                    BasicTypeEnum::StructType(t) => t.size_of().unwrap(),
                    _ => codegen_unreachable!(ctx),
                };
                ctx.builder.build_int_truncate_or_bit_cast(s, int32, "size").unwrap()
            }
            .into(),
        ];
        ctx.builder
            .build_call(slice_assign_fun, args.as_slice(), "slice_assign")
            .map(CallSiteValue::try_as_basic_value)
            .map(|v| v.map_left(BasicValueEnum::into_int_value))
            .map(Either::unwrap_left)
            .unwrap()
    };
    // update length
    let need_update =
        ctx.builder.build_int_compare(IntPredicate::NE, new_len, dest_len, "need_update").unwrap();
    let current = ctx.builder.get_insert_block().unwrap().get_parent().unwrap();
    let update_bb = ctx.ctx.append_basic_block(current, "update");
    let cont_bb = ctx.ctx.append_basic_block(current, "cont");
    ctx.builder.build_conditional_branch(need_update, update_bb, cont_bb).unwrap();
    ctx.builder.position_at_end(update_bb);
    let new_len = ctx.builder.build_int_z_extend_or_bit_cast(new_len, size_ty, "new_len").unwrap();
    dest_arr.store_size(ctx, generator, new_len);
    ctx.builder.build_unconditional_branch(cont_bb).unwrap();
    ctx.builder.position_at_end(cont_bb);
 }
--- a/nac3core/src/codegen/irrt/math.rs
+++ b/nac3core/src/codegen/irrt/math.rs
@ -0,0 +1,152 @@
 use inkwell::{
    values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue},
    IntPredicate,
 };
 use itertools::Either;
 use crate::codegen::{
    macros::codegen_unreachable,
    {CodeGenContext, CodeGenerator},
 };
 // repeated squaring method adapted from GNU Scientific Library:
 // https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
 pub fn integer_power<'ctx, G: CodeGenerator + ?Sized>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
    base: IntValue<'ctx>,
    exp: IntValue<'ctx>,
    signed: bool,
 ) -> IntValue<'ctx> {
    let symbol = match (base.get_type().get_bit_width(), exp.get_type().get_bit_width(), signed) {
        (32, 32, true) => "__nac3_int_exp_int32_t",
        (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),
    };
    let base_type = base.get_type();
    let pow_fun = ctx.module.get_function(symbol).unwrap_or_else(|| {
        let fn_type = base_type.fn_type(&[base_type.into(), base_type.into()], false);
        ctx.module.add_function(symbol, fn_type, None)
    });
    // throw exception when exp < 0
    let ge_zero = ctx
        .builder
        .build_int_compare(
            IntPredicate::SGE,
            exp,
            exp.get_type().const_zero(),
            "assert_int_pow_ge_0",
        )
        .unwrap();
    ctx.make_assert(
        generator,
        ge_zero,
        "0:ValueError",
        "integer power must be positive or zero",
        [None, None, None],
        ctx.current_loc,
    );
    ctx.builder
        .build_call(pow_fun, &[base.into(), exp.into()], "call_int_pow")
        .map(CallSiteValue::try_as_basic_value)
        .map(|v| v.map_left(BasicValueEnum::into_int_value))
        .map(Either::unwrap_left)
        .unwrap()
 }
 /// Generates a call to `isinf` in IR. Returns an `i1` representing the result.
 pub fn call_isinf<'ctx, G: CodeGenerator + ?Sized>(
    generator: &mut G,
    ctx: &CodeGenContext<'ctx, '_>,
    v: FloatValue<'ctx>,
 ) -> IntValue<'ctx> {
    let intrinsic_fn = ctx.module.get_function("__nac3_isinf").unwrap_or_else(|| {
        let fn_type = ctx.ctx.i32_type().fn_type(&[ctx.ctx.f64_type().into()], false);
        ctx.module.add_function("__nac3_isinf", fn_type, None)
    });
    let ret = ctx
        .builder
        .build_call(intrinsic_fn, &[v.into()], "isinf")
        .map(CallSiteValue::try_as_basic_value)
        .map(|v| v.map_left(BasicValueEnum::into_int_value))
        .map(Either::unwrap_left)
        .unwrap();
    generator.bool_to_i1(ctx, ret)
 }
 /// Generates a call to `isnan` in IR. Returns an `i1` representing the result.
 pub fn call_isnan<'ctx, G: CodeGenerator + ?Sized>(
    generator: &mut G,
    ctx: &CodeGenContext<'ctx, '_>,
    v: FloatValue<'ctx>,
 ) -> IntValue<'ctx> {
    let intrinsic_fn = ctx.module.get_function("__nac3_isnan").unwrap_or_else(|| {
        let fn_type = ctx.ctx.i32_type().fn_type(&[ctx.ctx.f64_type().into()], false);
        ctx.module.add_function("__nac3_isnan", fn_type, None)
    });
    let ret = ctx
        .builder
        .build_call(intrinsic_fn, &[v.into()], "isnan")
        .map(CallSiteValue::try_as_basic_value)
        .map(|v| v.map_left(BasicValueEnum::into_int_value))
        .map(Either::unwrap_left)
        .unwrap();
    generator.bool_to_i1(ctx, ret)
 }
 /// Generates a call to `gamma` in IR. Returns an `f64` representing the result.
 pub fn call_gamma<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
    let llvm_f64 = ctx.ctx.f64_type();
    let intrinsic_fn = ctx.module.get_function("__nac3_gamma").unwrap_or_else(|| {
        let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
        ctx.module.add_function("__nac3_gamma", fn_type, None)
    });
    ctx.builder
        .build_call(intrinsic_fn, &[v.into()], "gamma")
        .map(CallSiteValue::try_as_basic_value)
        .map(|v| v.map_left(BasicValueEnum::into_float_value))
        .map(Either::unwrap_left)
        .unwrap()
 }
 /// Generates a call to `gammaln` in IR. Returns an `f64` representing the result.
 pub fn call_gammaln<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
    let llvm_f64 = ctx.ctx.f64_type();
    let intrinsic_fn = ctx.module.get_function("__nac3_gammaln").unwrap_or_else(|| {
        let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
        ctx.module.add_function("__nac3_gammaln", fn_type, None)
    });
    ctx.builder
        .build_call(intrinsic_fn, &[v.into()], "gammaln")
        .map(CallSiteValue::try_as_basic_value)
        .map(|v| v.map_left(BasicValueEnum::into_float_value))
        .map(Either::unwrap_left)
        .unwrap()
 }
 /// Generates a call to `j0` in IR. Returns an `f64` representing the result.
 pub fn call_j0<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> FloatValue<'ctx> {
    let llvm_f64 = ctx.ctx.f64_type();
    let intrinsic_fn = ctx.module.get_function("__nac3_j0").unwrap_or_else(|| {
        let fn_type = llvm_f64.fn_type(&[llvm_f64.into()], false);
        ctx.module.add_function("__nac3_j0", fn_type, None)
    });
    ctx.builder
        .build_call(intrinsic_fn, &[v.into()], "j0")
        .map(CallSiteValue::try_as_basic_value)
        .map(|v| v.map_left(BasicValueEnum::into_float_value))
        .map(Either::unwrap_left)
        .unwrap()
 }
--- a/nac3core/src/codegen/irrt/mod.rs
+++ b/nac3core/src/codegen/irrt/mod.rs
--- a/nac3core/src/codegen/irrt/ndarray.rs
+++ b/nac3core/src/codegen/irrt/ndarray.rs
@ -0,0 +1,384 @@
 use inkwell::{
    types::IntType,
    values::{BasicValueEnum, CallSiteValue, IntValue},
    AddressSpace, IntPredicate,
 };
 use itertools::Either;
 use crate::codegen::{
    llvm_intrinsics,
    macros::codegen_unreachable,
    stmt::gen_for_callback_incrementing,
    values::{
        ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, NDArrayValue, TypedArrayLikeAccessor,
        TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
    },
    CodeGenContext, CodeGenerator,
 };
 /// Generates a call to `__nac3_ndarray_calc_size`. Returns an [`IntValue`] representing the
 /// calculated total size.
 ///
 /// * `dims` - An [`ArrayLikeIndexer`] containing the size of each dimension.
 /// * `range` - The dimension index to begin and end (exclusively) calculating the dimensions for,
 ///   or [`None`] if starting from the first dimension and ending at the last dimension
 ///   respectively.
 pub fn call_ndarray_calc_size<'ctx, G, Dims>(
    generator: &G,
    ctx: &CodeGenContext<'ctx, '_>,
    dims: &Dims,
    (begin, end): (Option<IntValue<'ctx>>, Option<IntValue<'ctx>>),
 ) -> IntValue<'ctx>
 where
    G: CodeGenerator + ?Sized,
    Dims: ArrayLikeIndexer<'ctx>,
 {
    let llvm_usize = generator.get_size_type(ctx.ctx);
    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
    let ndarray_calc_size_fn_name = match llvm_usize.get_bit_width() {
        32 => "__nac3_ndarray_calc_size",
        64 => "__nac3_ndarray_calc_size64",
        bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
    };
    let ndarray_calc_size_fn_t = llvm_usize.fn_type(
        &[llvm_pusize.into(), llvm_usize.into(), llvm_usize.into(), llvm_usize.into()],
        false,
    );
    let ndarray_calc_size_fn =
        ctx.module.get_function(ndarray_calc_size_fn_name).unwrap_or_else(|| {
            ctx.module.add_function(ndarray_calc_size_fn_name, ndarray_calc_size_fn_t, None)
        });
    let begin = begin.unwrap_or_else(|| llvm_usize.const_zero());
    let end = end.unwrap_or_else(|| dims.size(ctx, generator));
    ctx.builder
        .build_call(
            ndarray_calc_size_fn,
            &[
                dims.base_ptr(ctx, generator).into(),
                dims.size(ctx, generator).into(),
                begin.into(),
                end.into(),
            ],
            "",
        )
        .map(CallSiteValue::try_as_basic_value)
        .map(|v| v.map_left(BasicValueEnum::into_int_value))
        .map(Either::unwrap_left)
        .unwrap()
 }
 /// Generates a call to `__nac3_ndarray_calc_nd_indices`. Returns a [`TypeArrayLikeAdpater`]
 /// containing `i32` indices of the flattened index.
 ///
 /// * `index` - The index to compute the multidimensional index for.
 /// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
 ///   `NDArray`.
 pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
    generator: &G,
    ctx: &mut CodeGenContext<'ctx, '_>,
    index: IntValue<'ctx>,
    ndarray: NDArrayValue<'ctx>,
 ) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
    let llvm_void = ctx.ctx.void_type();
    let llvm_i32 = ctx.ctx.i32_type();
    let llvm_usize = generator.get_size_type(ctx.ctx);
    let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
    let ndarray_calc_nd_indices_fn_name = match llvm_usize.get_bit_width() {
        32 => "__nac3_ndarray_calc_nd_indices",
        64 => "__nac3_ndarray_calc_nd_indices64",
        bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
    };
    let ndarray_calc_nd_indices_fn =
        ctx.module.get_function(ndarray_calc_nd_indices_fn_name).unwrap_or_else(|| {
            let fn_type = llvm_void.fn_type(
                &[llvm_usize.into(), llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into()],
                false,
            );
            ctx.module.add_function(ndarray_calc_nd_indices_fn_name, fn_type, None)
        });
    let ndarray_num_dims = ndarray.load_ndims(ctx);
    let ndarray_dims = ndarray.shape();
    let indices = ctx.builder.build_array_alloca(llvm_i32, ndarray_num_dims, "").unwrap();
    ctx.builder
        .build_call(
            ndarray_calc_nd_indices_fn,
            &[
                index.into(),
                ndarray_dims.base_ptr(ctx, generator).into(),
                ndarray_num_dims.into(),
                indices.into(),
            ],
            "",
        )
        .unwrap();
    TypedArrayLikeAdapter::from(
        ArraySliceValue::from_ptr_val(indices, ndarray_num_dims, None),
        Box::new(|_, v| v.into_int_value()),
        Box::new(|_, v| v.into()),
    )
 }
 fn call_ndarray_flatten_index_impl<'ctx, G, Indices>(
    generator: &G,
    ctx: &CodeGenContext<'ctx, '_>,
    ndarray: NDArrayValue<'ctx>,
    indices: &Indices,
 ) -> IntValue<'ctx>
 where
    G: CodeGenerator + ?Sized,
    Indices: ArrayLikeIndexer<'ctx>,
 {
    let llvm_i32 = ctx.ctx.i32_type();
    let llvm_usize = generator.get_size_type(ctx.ctx);
    let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
    debug_assert_eq!(
        IntType::try_from(indices.element_type(ctx, generator))
            .map(IntType::get_bit_width)
            .unwrap_or_default(),
        llvm_i32.get_bit_width(),
        "Expected i32 value for argument `indices` to `call_ndarray_flatten_index_impl`"
    );
    debug_assert_eq!(
        indices.size(ctx, generator).get_type().get_bit_width(),
        llvm_usize.get_bit_width(),
        "Expected usize integer value for argument `indices_size` to `call_ndarray_flatten_index_impl`"
    );
    let ndarray_flatten_index_fn_name = match llvm_usize.get_bit_width() {
        32 => "__nac3_ndarray_flatten_index",
        64 => "__nac3_ndarray_flatten_index64",
        bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
    };
    let ndarray_flatten_index_fn =
        ctx.module.get_function(ndarray_flatten_index_fn_name).unwrap_or_else(|| {
            let fn_type = llvm_usize.fn_type(
                &[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_usize.into()],
                false,
            );
            ctx.module.add_function(ndarray_flatten_index_fn_name, fn_type, None)
        });
    let ndarray_num_dims = ndarray.load_ndims(ctx);
    let ndarray_dims = ndarray.shape();
    let index = ctx
        .builder
        .build_call(
            ndarray_flatten_index_fn,
            &[
                ndarray_dims.base_ptr(ctx, generator).into(),
                ndarray_num_dims.into(),
                indices.base_ptr(ctx, generator).into(),
                indices.size(ctx, generator).into(),
            ],
            "",
        )
        .map(CallSiteValue::try_as_basic_value)
        .map(|v| v.map_left(BasicValueEnum::into_int_value))
        .map(Either::unwrap_left)
        .unwrap();
    index
 }
 /// Generates a call to `__nac3_ndarray_flatten_index`. Returns the flattened index for the
 /// multidimensional index.
 ///
 /// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
 ///   `NDArray`.
 /// * `indices` - The multidimensional index to compute the flattened index for.
 pub fn call_ndarray_flatten_index<'ctx, G, Index>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
    ndarray: NDArrayValue<'ctx>,
    indices: &Index,
 ) -> IntValue<'ctx>
 where
    G: CodeGenerator + ?Sized,
    Index: ArrayLikeIndexer<'ctx>,
 {
    call_ndarray_flatten_index_impl(generator, ctx, ndarray, indices)
 }
 /// Generates a call to `__nac3_ndarray_calc_broadcast`. Returns a tuple containing the number of
 /// dimension and size of each dimension of the resultant `ndarray`.
 pub fn call_ndarray_calc_broadcast<'ctx, G: CodeGenerator + ?Sized>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
    lhs: NDArrayValue<'ctx>,
    rhs: NDArrayValue<'ctx>,
 ) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
    let llvm_usize = generator.get_size_type(ctx.ctx);
    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
    let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
        32 => "__nac3_ndarray_calc_broadcast",
        64 => "__nac3_ndarray_calc_broadcast64",
        bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
    };
    let ndarray_calc_broadcast_fn =
        ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
            let fn_type = llvm_usize.fn_type(
                &[
                    llvm_pusize.into(),
                    llvm_usize.into(),
                    llvm_pusize.into(),
                    llvm_usize.into(),
                    llvm_pusize.into(),
                ],
                false,
            );
            ctx.module.add_function(ndarray_calc_broadcast_fn_name, fn_type, None)
        });
    let lhs_ndims = lhs.load_ndims(ctx);
    let rhs_ndims = rhs.load_ndims(ctx);
    let min_ndims = llvm_intrinsics::call_int_umin(ctx, lhs_ndims, rhs_ndims, None);
    gen_for_callback_incrementing(
        generator,
        ctx,
        None,
        llvm_usize.const_zero(),
        (min_ndims, false),
        |generator, ctx, _, idx| {
            let idx = ctx.builder.build_int_sub(min_ndims, idx, "").unwrap();
            let (lhs_dim_sz, rhs_dim_sz) = unsafe {
                (
                    lhs.shape().get_typed_unchecked(ctx, generator, &idx, None),
                    rhs.shape().get_typed_unchecked(ctx, generator, &idx, None),
                )
            };
            let llvm_usize_const_one = llvm_usize.const_int(1, false);
            let lhs_eqz = ctx
                .builder
                .build_int_compare(IntPredicate::EQ, lhs_dim_sz, llvm_usize_const_one, "")
                .unwrap();
            let rhs_eqz = ctx
                .builder
                .build_int_compare(IntPredicate::EQ, rhs_dim_sz, llvm_usize_const_one, "")
                .unwrap();
            let lhs_or_rhs_eqz = ctx.builder.build_or(lhs_eqz, rhs_eqz, "").unwrap();
            let lhs_eq_rhs = ctx
                .builder
                .build_int_compare(IntPredicate::EQ, lhs_dim_sz, rhs_dim_sz, "")
                .unwrap();
            let is_compatible = ctx.builder.build_or(lhs_or_rhs_eqz, lhs_eq_rhs, "").unwrap();
            ctx.make_assert(
                generator,
                is_compatible,
                "0:ValueError",
                "operands could not be broadcast together",
                [None, None, None],
                ctx.current_loc,
            );
            Ok(())
        },
        llvm_usize.const_int(1, false),
    )
    .unwrap();
    let max_ndims = llvm_intrinsics::call_int_umax(ctx, lhs_ndims, rhs_ndims, None);
    let lhs_dims = lhs.shape().base_ptr(ctx, generator);
    let lhs_ndims = lhs.load_ndims(ctx);
    let rhs_dims = rhs.shape().base_ptr(ctx, generator);
    let rhs_ndims = rhs.load_ndims(ctx);
    let out_dims = ctx.builder.build_array_alloca(llvm_usize, max_ndims, "").unwrap();
    let out_dims = ArraySliceValue::from_ptr_val(out_dims, max_ndims, None);
    ctx.builder
        .build_call(
            ndarray_calc_broadcast_fn,
            &[
                lhs_dims.into(),
                lhs_ndims.into(),
                rhs_dims.into(),
                rhs_ndims.into(),
                out_dims.base_ptr(ctx, generator).into(),
            ],
            "",
        )
        .unwrap();
    TypedArrayLikeAdapter::from(
        out_dims,
        Box::new(|_, v| v.into_int_value()),
        Box::new(|_, v| v.into()),
    )
 }
 /// Generates a call to `__nac3_ndarray_calc_broadcast_idx`. Returns an [`ArrayAllocaValue`]
 /// containing the indices used for accessing `array` corresponding to the index of the broadcasted
 /// array `broadcast_idx`.
 pub fn call_ndarray_calc_broadcast_index<
    'ctx,
    G: CodeGenerator + ?Sized,
    BroadcastIdx: UntypedArrayLikeAccessor<'ctx>,
 >(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
    array: NDArrayValue<'ctx>,
    broadcast_idx: &BroadcastIdx,
 ) -> TypedArrayLikeAdapter<'ctx, IntValue<'ctx>> {
    let llvm_i32 = ctx.ctx.i32_type();
    let llvm_usize = generator.get_size_type(ctx.ctx);
    let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
    let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
        32 => "__nac3_ndarray_calc_broadcast_idx",
        64 => "__nac3_ndarray_calc_broadcast_idx64",
        bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
    };
    let ndarray_calc_broadcast_fn =
        ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
            let fn_type = llvm_usize.fn_type(
                &[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_pi32.into()],
                false,
            );
            ctx.module.add_function(ndarray_calc_broadcast_fn_name, fn_type, None)
        });
    let broadcast_size = broadcast_idx.size(ctx, generator);
    let out_idx = ctx.builder.build_array_alloca(llvm_i32, broadcast_size, "").unwrap();
    let array_dims = array.shape().base_ptr(ctx, generator);
    let array_ndims = array.load_ndims(ctx);
    let broadcast_idx_ptr = unsafe {
        broadcast_idx.ptr_offset_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
    };
    ctx.builder
        .build_call(
            ndarray_calc_broadcast_fn,
            &[array_dims.into(), array_ndims.into(), broadcast_idx_ptr.into(), out_idx.into()],
            "",
        )
        .unwrap();
    TypedArrayLikeAdapter::from(
        ArraySliceValue::from_ptr_val(out_idx, broadcast_size, None),
        Box::new(|_, v| v.into_int_value()),
        Box::new(|_, v| v.into()),
    )
 }
--- a/nac3core/src/codegen/irrt/slice.rs
+++ b/nac3core/src/codegen/irrt/slice.rs
@ -0,0 +1,76 @@
 use inkwell::{
    values::{BasicValueEnum, CallSiteValue, IntValue},
    IntPredicate,
 };
 use itertools::Either;
 use nac3parser::ast::Expr;
 use crate::{
    codegen::{CodeGenContext, CodeGenerator},
    typecheck::typedef::Type,
 };
 /// this function allows index out of range, since python
 /// allows index out of range in slice (`a = [1,2,3]; a[1:10] == [2,3]`).
 pub fn handle_slice_index_bound<'ctx, G: CodeGenerator>(
    i: &Expr<Option<Type>>,
    ctx: &mut CodeGenContext<'ctx, '_>,
    generator: &mut G,
    length: IntValue<'ctx>,
 ) -> Result<Option<IntValue<'ctx>>, String> {
    const SYMBOL: &str = "__nac3_slice_index_bound";
    let func = ctx.module.get_function(SYMBOL).unwrap_or_else(|| {
        let i32_t = ctx.ctx.i32_type();
        let fn_t = i32_t.fn_type(&[i32_t.into(), i32_t.into()], false);
        ctx.module.add_function(SYMBOL, fn_t, None)
    });
    let i = if let Some(v) = generator.gen_expr(ctx, i)? {
        v.to_basic_value_enum(ctx, generator, i.custom.unwrap())?
    } else {
        return Ok(None);
    };
    Ok(Some(
        ctx.builder
            .build_call(func, &[i.into(), length.into()], "bounded_ind")
            .map(CallSiteValue::try_as_basic_value)
            .map(|v| v.map_left(BasicValueEnum::into_int_value))
            .map(Either::unwrap_left)
            .unwrap(),
    ))
 }
 pub fn calculate_len_for_slice_range<'ctx, G: CodeGenerator + ?Sized>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
    start: IntValue<'ctx>,
    end: IntValue<'ctx>,
    step: IntValue<'ctx>,
 ) -> IntValue<'ctx> {
    const SYMBOL: &str = "__nac3_range_slice_len";
    let len_func = ctx.module.get_function(SYMBOL).unwrap_or_else(|| {
        let i32_t = ctx.ctx.i32_type();
        let fn_t = i32_t.fn_type(&[i32_t.into(), i32_t.into(), i32_t.into()], false);
        ctx.module.add_function(SYMBOL, fn_t, None)
    });
    // assert step != 0, throw exception if not
    let not_zero = ctx
        .builder
        .build_int_compare(IntPredicate::NE, step, step.get_type().const_zero(), "range_step_ne")
        .unwrap();
    ctx.make_assert(
        generator,
        not_zero,
        "0:ValueError",
        "step must not be zero",
        [None, None, None],
        ctx.current_loc,
    );
    ctx.builder
        .build_call(len_func, &[start.into(), end.into(), step.into()], "calc_len")
        .map(CallSiteValue::try_as_basic_value)
        .map(|v| v.map_left(BasicValueEnum::into_int_value))
        .map(Either::unwrap_left)
        .unwrap()
 }
--- a/nac3core/src/codegen/llvm_intrinsics.rs
+++ b/nac3core/src/codegen/llvm_intrinsics.rs
@ -1,12 +1,14 @@
-use crate::codegen::CodeGenContext;
+use inkwell::{
-use inkwell::context::Context;
+    context::Context,
-use inkwell::intrinsics::Intrinsic;
+    intrinsics::Intrinsic,
-use inkwell::types::AnyTypeEnum::IntType;
+    types::{AnyTypeEnum::IntType, FloatType},
-use inkwell::types::FloatType;
+    values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue, PointerValue},
-use inkwell::values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue, PointerValue};
+    AddressSpace,
-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 {
@ -183,7 +185,7 @@ pub fn call_memcpy_generic<'ctx>(
        dest
    } else {
        ctx.builder
-            .build_bitcast(dest, llvm_p0i8, "")
+            .build_bit_cast(dest, llvm_p0i8, "")
            .map(BasicValueEnum::into_pointer_value)
            .unwrap()
    };
@ -191,7 +193,7 @@ pub fn call_memcpy_generic<'ctx>(
        src
    } else {
        ctx.builder
-            .build_bitcast(src, llvm_p0i8, "")
+            .build_bit_cast(src, llvm_p0i8, "")
            .map(BasicValueEnum::into_pointer_value)
            .unwrap()
    };
--- a/nac3core/src/codegen/mod.rs
+++ b/nac3core/src/codegen/mod.rs
@ -1,12 +1,12 @@
-use crate::{
+use std::{
-    codegen::classes::{ListType, ProxyType, RangeType},
+    collections::{HashMap, HashSet},
-    symbol_resolver::{StaticValue, SymbolResolver},
+    sync::{
-    toplevel::{helper::PrimDef, TopLevelContext, TopLevelDef},
+        atomic::{AtomicBool, Ordering},
-    typecheck::{
+        Arc,
        type_inferencer::{CodeLocation, PrimitiveStore},
        typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
    },
    thread,
 };
 use crossbeam::channel::{unbounded, Receiver, Sender};
 use inkwell::{
    attributes::{Attribute, AttributeLoc},
@ -24,36 +24,37 @@ use inkwell::{
    AddressSpace, IntPredicate, OptimizationLevel,
 };
 use itertools::Itertools;
 use model::*;
 use nac3parser::ast::{Location, Stmt, StrRef};
 use object::ndarray::NDArray;
 use parking_lot::{Condvar, Mutex};
-use std::collections::{HashMap, HashSet};
+
-use std::sync::{
+use nac3parser::ast::{Location, Stmt, StrRef};
-    atomic::{AtomicBool, Ordering},
+
-    Arc,
+use crate::{
    symbol_resolver::{StaticValue, SymbolResolver},
    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, TopLevelContext, TopLevelDef},
    typecheck::{
        type_inferencer::{CodeLocation, PrimitiveStore},
        typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
    },
 };
-use std::thread;
+use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
 pub use generator::{CodeGenerator, DefaultCodeGenerator};
 use types::{ListType, NDArrayType, ProxyType, RangeType};
 pub mod builtin_fns;
 pub mod classes;
 pub mod concrete_type;
 pub mod expr;
 pub mod extern_fns;
 mod generator;
 pub mod irrt;
 pub mod llvm_intrinsics;
 pub mod model;
 pub mod numpy;
 pub mod object;
 pub mod stmt;
 pub mod types;
 pub mod values;
 #[cfg(test)]
 mod test;
 use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
 pub use generator::{CodeGenerator, DefaultCodeGenerator};
 mod macros {
    /// Codegen-variant of [`std::unreachable`] which accepts an instance of [`CodeGenContext`] as
    /// its first argument to provide Python source information to indicate the codegen location
@ -509,7 +510,12 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
                        }
                        TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-                            Ptr(Struct(NDArray)).llvm_type(generator, ctx).as_basic_type_enum()
+                            let (dtype, _) = unpack_ndarray_var_tys(unifier, ty);
                            let element_type = get_llvm_type(
                                ctx, module, generator, unifier, top_level, type_cache, dtype,
                            );
                            NDArrayType::new(generator, ctx, element_type).as_base_type().into()
                        }
                        _ => unreachable!(
@ -847,10 +853,9 @@ 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);
    // Store non-vararg argument values into local variables
    for (n, arg) in args.iter().enumerate().filter(|(_, arg)| !arg.is_vararg) {
        let param = fn_val.get_nth_param((n as u32) + offset).unwrap();
        let local_type = get_llvm_type(
--- a/nac3core/src/codegen/model/any.rs
+++ b/nac3core/src/codegen/model/any.rs
@ -1,42 +0,0 @@
 use inkwell::{
    context::Context,
    types::{BasicType, BasicTypeEnum},
    values::BasicValueEnum,
 };
 use crate::codegen::CodeGenerator;
 use super::*;
 /// A [`Model`] of any [`BasicTypeEnum`].
 ///
 /// Use this when it is infeasible to use model abstractions.
 #[derive(Debug, Clone, Copy)]
 pub struct Any<'ctx>(pub BasicTypeEnum<'ctx>);
 impl<'ctx> Model<'ctx> for Any<'ctx> {
    type Value = BasicValueEnum<'ctx>;
    type Type = BasicTypeEnum<'ctx>;
    fn llvm_type<G: CodeGenerator + ?Sized>(
        &self,
        _generator: &G,
        _ctx: &'ctx Context,
    ) -> Self::Type {
        self.0
    }
    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        _generator: &mut G,
        _ctx: &'ctx Context,
        ty: T,
    ) -> Result<(), ModelError> {
        let ty = ty.as_basic_type_enum();
        if ty == self.0 {
            Ok(())
        } else {
            Err(ModelError(format!("Expecting {}, but got {}", self.0, ty)))
        }
    }
 }
--- a/nac3core/src/codegen/model/array.rs
+++ b/nac3core/src/codegen/model/array.rs
@ -1,147 +0,0 @@
 use std::fmt;
 use inkwell::{
    context::Context,
    types::{ArrayType, BasicType, BasicTypeEnum},
    values::{ArrayValue, IntValue},
 };
 use crate::codegen::{CodeGenContext, CodeGenerator};
 use super::*;
 /// Trait for Rust structs identifying length values for [`Array`].
 pub trait ArrayLen: fmt::Debug + Clone + Copy {
    fn length(&self) -> u32;
 }
 /// A statically known length.
 #[derive(Debug, Clone, Copy, Default)]
 pub struct Len<const N: u32>;
 /// A dynamically known length.
 #[derive(Debug, Clone, Copy)]
 pub struct AnyLen(pub u32);
 impl<const N: u32> ArrayLen for Len<N> {
    fn length(&self) -> u32 {
        N
    }
 }
 impl ArrayLen for AnyLen {
    fn length(&self) -> u32 {
        self.0
    }
 }
 /// A Model for an [`ArrayType`].
 ///
 /// `Len` should be of a [`LenKind`] and `Item` should be a of [`Model`].
 #[derive(Debug, Clone, Copy, Default)]
 pub struct Array<Len, Item> {
    /// Length of this array.
    pub len: Len,
    /// [`Model`] of the array items.
    pub item: Item,
 }
 impl<'ctx, Len: ArrayLen, Item: Model<'ctx>> Model<'ctx> for Array<Len, Item> {
    type Value = ArrayValue<'ctx>;
    type Type = ArrayType<'ctx>;
    fn llvm_type<G: CodeGenerator + ?Sized>(
        &self,
        generator: &G,
        ctx: &'ctx Context,
    ) -> Self::Type {
        self.item.llvm_type(generator, ctx).array_type(self.len.length())
    }
    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
        ty: T,
    ) -> Result<(), ModelError> {
        let ty = ty.as_basic_type_enum();
        let BasicTypeEnum::ArrayType(ty) = ty else {
            return Err(ModelError(format!("Expecting ArrayType, but got {ty:?}")));
        };
        if ty.len() != self.len.length() {
            return Err(ModelError(format!(
                "Expecting ArrayType with size {}, but got an ArrayType with size {}",
                ty.len(),
                self.len.length()
            )));
        }
        self.item
            .check_type(generator, ctx, ty.get_element_type())
            .map_err(|err| err.under_context("an ArrayType"))?;
        Ok(())
    }
 }
 impl<'ctx, Len: ArrayLen, Item: Model<'ctx>> Instance<'ctx, Ptr<Array<Len, Item>>> {
    /// Get the pointer to the `i`-th (0-based) array element.
    pub fn gep(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        i: IntValue<'ctx>,
    ) -> Instance<'ctx, Ptr<Item>> {
        let zero = ctx.ctx.i32_type().const_zero();
        let ptr = unsafe { ctx.builder.build_in_bounds_gep(self.value, &[zero, i], "").unwrap() };
        unsafe { Ptr(self.model.0.item).believe_value(ptr) }
    }
    /// Like `gep` but `i` is a constant.
    pub fn gep_const(&self, ctx: &CodeGenContext<'ctx, '_>, i: u64) -> Instance<'ctx, Ptr<Item>> {
        assert!(
            i < u64::from(self.model.0.len.length()),
            "Index {i} is out of bounds. Array length = {}",
            self.model.0.len.length()
        );
        let i = ctx.ctx.i32_type().const_int(i, false);
        self.gep(ctx, i)
    }
    /// Convenience function equivalent to `.gep(...).load(...)`.
    pub fn get<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        i: IntValue<'ctx>,
    ) -> Instance<'ctx, Item> {
        self.gep(ctx, i).load(generator, ctx)
    }
    /// Like `get` but `i` is a constant.
    pub fn get_const<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        i: u64,
    ) -> Instance<'ctx, Item> {
        self.gep_const(ctx, i).load(generator, ctx)
    }
    /// Convenience function equivalent to `.gep(...).store(...)`.
    pub fn set(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        i: IntValue<'ctx>,
        value: Instance<'ctx, Item>,
    ) {
        self.gep(ctx, i).store(ctx, value);
    }
    /// Like `set` but `i` is a constant.
    pub fn set_const(&self, ctx: &CodeGenContext<'ctx, '_>, i: u64, value: Instance<'ctx, Item>) {
        self.gep_const(ctx, i).store(ctx, value);
    }
 }
--- a/nac3core/src/codegen/model/core.rs
+++ b/nac3core/src/codegen/model/core.rs
@ -1,207 +0,0 @@
 use std::fmt;
 use inkwell::{context::Context, types::*, values::*};
 use itertools::Itertools;
 use super::*;
 use crate::codegen::{CodeGenContext, CodeGenerator};
 /// A error type for reporting any [`Model`]-related error (e.g., a [`BasicType`] mismatch).
 #[derive(Debug, Clone)]
 pub struct ModelError(pub String);
 impl ModelError {
    /// Append a context message to the error.
    pub(super) fn under_context(mut self, context: &str) -> Self {
        self.0.push_str(" ... in ");
        self.0.push_str(context);
        self
    }
 }
 /// Trait for Rust structs identifying [`BasicType`]s in the context of a known [`CodeGenerator`] and [`CodeGenContext`].
 ///
 /// For instance,
 /// - [`Int<Int32>`] identifies an [`IntType`] with 32-bits.
 /// - [`Int<SizeT>`] identifies an [`IntType`] with bit-width [`CodeGenerator::get_size_type`].
 /// - [`Ptr<Int<SizeT>>`] identifies a [`PointerType`] that points to an [`IntType`] with bit-width [`CodeGenerator::get_size_type`].
 /// - [`Int<AnyInt>`] identifies an [`IntType`] with bit-width of whatever is set in the [`AnyInt`] object.
 /// - [`Any`] identifies a [`BasicType`] set in the [`Any`] object itself.
 ///
 /// You can get the [`BasicType`] out of a model with [`Model::get_type`].
 ///
 /// Furthermore, [`Instance<'ctx, M>`] is a simple structure that carries a [`BasicValue`] with [`BasicType`] identified by model `M`.
 ///
 /// The main purpose of this abstraction is to have a more Rust type-safe way to use Inkwell and give type-hints for programmers.
 ///
 /// ### Notes on `Default` trait
 ///
 /// For some models like [`Int<Int32>`] or [`Int<SizeT>`], they have a [`Default`] trait since just by looking at their types, it is possible
 /// to tell the [`BasicType`]s they are identifying.
 ///
 /// This can be used to create strongly-typed interfaces accepting only values of a specific [`BasicType`] without having to worry about
 /// writing debug assertions to check, for example, if the programmer has passed in an [`IntValue`] with the wrong bit-width.
 /// ```ignore
 /// fn give_me_i32_and_get_a_size_t_back<'ctx>(i32: Instance<'ctx, Int<Int32>>) -> Instance<'ctx, Int<SizeT>> {
 ///     // code...
 /// }
 /// ```
 ///
 /// ### Notes on converting between Inkwell and model/ge.
 ///
 /// Suppose you have an [`IntValue`], and you want to pass it into a function that takes a [`Instance<'ctx, Int<Int32>>`]. You can do use
 /// [`Model::check_value`] or [`Model::believe_value`].
 /// ```ignore
 /// let my_value: IntValue<'ctx>;
 ///
 /// let my_value = Int(Int32).check_value(my_value).unwrap(); // Panics if `my_value` is not 32-bit with a descriptive error message.
 ///
 /// // or, if you are absolutely certain that `my_value` is 32-bit and doing extra checks is a waste of time:
 /// let my_value = Int(Int32).believe_value(my_value);
 /// ```
 pub trait Model<'ctx>: fmt::Debug + Clone + Copy {
    /// The [`BasicType`] *variant* this model is identifying.
    type Type: BasicType<'ctx>;
    /// The [`BasicValue`] type of the [`BasicType`] of this model.
    type Value: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>>;
    /// Return the [`BasicType`] of this model.
    #[must_use]
    fn llvm_type<G: CodeGenerator + ?Sized>(&self, generator: &G, ctx: &'ctx Context)
        -> Self::Type;
    /// Get the number of bytes of the [`BasicType`] of this model.
    fn size_of<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
    ) -> IntValue<'ctx> {
        self.llvm_type(generator, ctx).size_of().unwrap()
    }
    /// Check if a [`BasicType`] matches the [`BasicType`] of this model.
    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
        ty: T,
    ) -> Result<(), ModelError>;
    /// Create an instance from a value.
    ///
    /// # Safety
    ///
    /// Caller must make sure the type of `value` and the type of this `model` are equivalent.
    #[must_use]
    unsafe fn believe_value(&self, value: Self::Value) -> Instance<'ctx, Self> {
        Instance { model: *self, value }
    }
    /// Check if a [`BasicValue`]'s type is equivalent to the type of this model.
    /// Wrap the [`BasicValue`] into an [`Instance`] if it is.
    fn check_value<V: BasicValue<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
        value: V,
    ) -> Result<Instance<'ctx, Self>, ModelError> {
        let value = value.as_basic_value_enum();
        self.check_type(generator, ctx, value.get_type())
            .map_err(|err| err.under_context(format!("the value {value:?}").as_str()))?;
        let Ok(value) = Self::Value::try_from(value) else {
            unreachable!("check_type() has bad implementation")
        };
        unsafe { Ok(self.believe_value(value)) }
    }
    // Allocate a value on the stack and return its pointer.
    fn alloca<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
    ) -> Instance<'ctx, Ptr<Self>> {
        let p = ctx.builder.build_alloca(self.llvm_type(generator, ctx.ctx), "").unwrap();
        unsafe { Ptr(*self).believe_value(p) }
    }
    // Allocate an array on the stack and return its pointer.
    fn array_alloca<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        len: IntValue<'ctx>,
    ) -> Instance<'ctx, Ptr<Self>> {
        let p =
            ctx.builder.build_array_alloca(self.llvm_type(generator, ctx.ctx), len, "").unwrap();
        unsafe { Ptr(*self).believe_value(p) }
    }
    fn var_alloca<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        name: Option<&str>,
    ) -> Result<Instance<'ctx, Ptr<Self>>, String> {
        let ty = self.llvm_type(generator, ctx.ctx).as_basic_type_enum();
        let p = generator.gen_var_alloc(ctx, ty, name)?;
        unsafe { Ok(Ptr(*self).believe_value(p)) }
    }
    fn array_var_alloca<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        len: IntValue<'ctx>,
        name: Option<&'ctx str>,
    ) -> Result<Instance<'ctx, Ptr<Self>>, String> {
        // TODO: Remove ArraySliceValue
        let ty = self.llvm_type(generator, ctx.ctx).as_basic_type_enum();
        let p = generator.gen_array_var_alloc(ctx, ty, len, name)?;
        unsafe { Ok(Ptr(*self).believe_value(PointerValue::from(p))) }
    }
    /// Allocate a constant array.
    fn const_array<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
        values: &[Instance<'ctx, Self>],
    ) -> Instance<'ctx, Array<AnyLen, Self>> {
        macro_rules! make {
            ($t:expr, $into_value:expr) => {
                $t.const_array(
                    &values
                        .iter()
                        .map(|x| $into_value(x.value.as_basic_value_enum()))
                        .collect_vec(),
                )
            };
        }
        let value = match self.llvm_type(generator, ctx).as_basic_type_enum() {
            BasicTypeEnum::ArrayType(t) => make!(t, BasicValueEnum::into_array_value),
            BasicTypeEnum::IntType(t) => make!(t, BasicValueEnum::into_int_value),
            BasicTypeEnum::FloatType(t) => make!(t, BasicValueEnum::into_float_value),
            BasicTypeEnum::PointerType(t) => make!(t, BasicValueEnum::into_pointer_value),
            BasicTypeEnum::StructType(t) => make!(t, BasicValueEnum::into_struct_value),
            BasicTypeEnum::VectorType(t) => make!(t, BasicValueEnum::into_vector_value),
        };
        Array { len: AnyLen(values.len() as u32), item: *self }
            .check_value(generator, ctx, value)
            .unwrap()
    }
 }
 #[derive(Debug, Clone, Copy)]
 pub struct Instance<'ctx, M: Model<'ctx>> {
    /// The model of this instance.
    pub model: M,
    /// The value of this instance.
    ///
    /// It is guaranteed the [`BasicType`] of `value` is consistent with that of `model`.
    pub value: M::Value,
 }
--- a/nac3core/src/codegen/model/float.rs
+++ b/nac3core/src/codegen/model/float.rs
@ -1,94 +0,0 @@
 use std::fmt;
 use inkwell::{
    context::Context,
    types::{BasicType, FloatType},
    values::FloatValue,
 };
 use crate::codegen::CodeGenerator;
 use super::*;
 pub trait FloatKind<'ctx>: fmt::Debug + Clone + Copy {
    fn get_float_type<G: CodeGenerator + ?Sized>(
        &self,
        generator: &G,
        ctx: &'ctx Context,
    ) -> FloatType<'ctx>;
 }
 #[derive(Debug, Clone, Copy, Default)]
 pub struct Float32;
 #[derive(Debug, Clone, Copy, Default)]
 pub struct Float64;
 impl<'ctx> FloatKind<'ctx> for Float32 {
    fn get_float_type<G: CodeGenerator + ?Sized>(
        &self,
        _generator: &G,
        ctx: &'ctx Context,
    ) -> FloatType<'ctx> {
        ctx.f32_type()
    }
 }
 impl<'ctx> FloatKind<'ctx> for Float64 {
    fn get_float_type<G: CodeGenerator + ?Sized>(
        &self,
        _generator: &G,
        ctx: &'ctx Context,
    ) -> FloatType<'ctx> {
        ctx.f64_type()
    }
 }
 #[derive(Debug, Clone, Copy)]
 pub struct AnyFloat<'ctx>(FloatType<'ctx>);
 impl<'ctx> FloatKind<'ctx> for AnyFloat<'ctx> {
    fn get_float_type<G: CodeGenerator + ?Sized>(
        &self,
        _generator: &G,
        _ctx: &'ctx Context,
    ) -> FloatType<'ctx> {
        self.0
    }
 }
 #[derive(Debug, Clone, Copy, Default)]
 pub struct Float<N>(pub N);
 impl<'ctx, N: FloatKind<'ctx>> Model<'ctx> for Float<N> {
    type Value = FloatValue<'ctx>;
    type Type = FloatType<'ctx>;
    fn llvm_type<G: CodeGenerator + ?Sized>(
        &self,
        generator: &G,
        ctx: &'ctx Context,
    ) -> Self::Type {
        self.0.get_float_type(generator, ctx)
    }
    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
        ty: T,
    ) -> Result<(), ModelError> {
        let ty = ty.as_basic_type_enum();
        let Ok(ty) = FloatType::try_from(ty) else {
            return Err(ModelError(format!("Expecting FloatType, but got {ty:?}")));
        };
        let exp_ty = self.0.get_float_type(generator, ctx);
        // TODO: Inkwell does not have get_bit_width for FloatType?
        if ty != exp_ty {
            return Err(ModelError(format!("Expecting {exp_ty:?}, but got {ty:?}")));
        }
        Ok(())
    }
 }
--- a/nac3core/src/codegen/model/function.rs
+++ b/nac3core/src/codegen/model/function.rs
@ -1,122 +0,0 @@
 use inkwell::{
    attributes::{Attribute, AttributeLoc},
    types::{BasicMetadataTypeEnum, BasicType, FunctionType},
    values::{AnyValue, BasicMetadataValueEnum, BasicValue, BasicValueEnum, CallSiteValue},
 };
 use itertools::Itertools;
 use crate::codegen::{CodeGenContext, CodeGenerator};
 use super::*;
 #[derive(Debug, Clone, Copy)]
 struct Arg<'ctx> {
    ty: BasicMetadataTypeEnum<'ctx>,
    val: BasicMetadataValueEnum<'ctx>,
 }
 /// A convenience structure to construct & call an LLVM function.
 ///
 /// ### Usage
 ///
 /// The syntax is like this:
 /// ```ignore
 /// let result = CallFunction::begin("my_function_name")
 ///   .attrs(...)
 ///   .arg(arg1)
 ///   .arg(arg2)
 ///   .arg(arg3)
 ///   .returning("my_function_result", Int32);
 /// ```
 ///
 /// The function `my_function_name` is called when `.returning()` (or its variants) is called, returning
 /// the result as an `Instance<'ctx, Int<Int32>>`.
 ///
 /// If `my_function_name` has not been declared in `ctx.module`, once `.returning()` is called, a function
 /// declaration of `my_function_name` is added to `ctx.module`, where the [`FunctionType`] is deduced from
 /// the argument types and returning type.
 pub struct FnCall<'ctx, 'a, 'b, 'c, 'd, G: CodeGenerator + ?Sized> {
    generator: &'d mut G,
    ctx: &'b CodeGenContext<'ctx, 'a>,
    /// Function name
    name: &'c str,
    /// Call arguments
    args: Vec<Arg<'ctx>>,
    /// LLVM function Attributes
    attrs: Vec<&'static str>,
 }
 impl<'ctx, 'a, 'b, 'c, 'd, G: CodeGenerator + ?Sized> FnCall<'ctx, 'a, 'b, 'c, 'd, G> {
    pub fn builder(generator: &'d mut G, ctx: &'b CodeGenContext<'ctx, 'a>, name: &'c str) -> Self {
        FnCall { generator, ctx, name, args: Vec::new(), attrs: Vec::new() }
    }
    /// Push a list of LLVM function attributes to the function declaration.
    #[must_use]
    pub fn attrs(mut self, attrs: Vec<&'static str>) -> Self {
        self.attrs = attrs;
        self
    }
    /// Push a call argument to the function call.
    #[allow(clippy::needless_pass_by_value)]
    #[must_use]
    pub fn arg<M: Model<'ctx>>(mut self, arg: Instance<'ctx, M>) -> Self {
        let arg = Arg {
            ty: arg.model.llvm_type(self.generator, self.ctx.ctx).as_basic_type_enum().into(),
            val: arg.value.as_basic_value_enum().into(),
        };
        self.args.push(arg);
        self
    }
    /// Call the function and expect the function to return a value of type of `return_model`.
    #[must_use]
    pub fn returning<M: Model<'ctx>>(self, name: &str, return_model: M) -> Instance<'ctx, M> {
        let ret_ty = return_model.llvm_type(self.generator, self.ctx.ctx);
        let ret = self.call(|tys| ret_ty.fn_type(tys, false), name);
        let ret = BasicValueEnum::try_from(ret.as_any_value_enum()).unwrap(); // Must work
        let ret = return_model.check_value(self.generator, self.ctx.ctx, ret).unwrap(); // Must work
        ret
    }
    /// Like [`CallFunction::returning_`] but `return_model` is automatically inferred.
    #[must_use]
    pub fn returning_auto<M: Model<'ctx> + Default>(self, name: &str) -> Instance<'ctx, M> {
        self.returning(name, M::default())
    }
    /// Call the function and expect the function to return a void-type.
    pub fn returning_void(self) {
        let ret_ty = self.ctx.ctx.void_type();
        let _ = self.call(|tys| ret_ty.fn_type(tys, false), "");
    }
    fn call<F>(&self, make_fn_type: F, return_value_name: &str) -> CallSiteValue<'ctx>
    where
        F: FnOnce(&[BasicMetadataTypeEnum<'ctx>]) -> FunctionType<'ctx>,
    {
        // Get the LLVM function.
        let func = self.ctx.module.get_function(self.name).unwrap_or_else(|| {
            // Declare the function if it doesn't exist.
            let tys = self.args.iter().map(|arg| arg.ty).collect_vec();
            let func_type = make_fn_type(&tys);
            let func = self.ctx.module.add_function(self.name, func_type, None);
            for attr in &self.attrs {
                func.add_attribute(
                    AttributeLoc::Function,
                    self.ctx.ctx.create_enum_attribute(Attribute::get_named_enum_kind_id(attr), 0),
                );
            }
            func
        });
        let vals = self.args.iter().map(|arg| arg.val).collect_vec();
        self.ctx.builder.build_call(func, &vals, return_value_name).unwrap()
    }
 }
--- a/nac3core/src/codegen/model/int.rs
+++ b/nac3core/src/codegen/model/int.rs
@ -1,422 +0,0 @@
 use std::{cmp::Ordering, fmt};
 use inkwell::{
    context::Context,
    types::{BasicType, IntType},
    values::IntValue,
    IntPredicate,
 };
 use crate::codegen::{CodeGenContext, CodeGenerator};
 use super::*;
 pub trait IntKind<'ctx>: fmt::Debug + Clone + Copy {
    fn get_int_type<G: CodeGenerator + ?Sized>(
        &self,
        generator: &G,
        ctx: &'ctx Context,
    ) -> IntType<'ctx>;
 }
 #[derive(Debug, Clone, Copy, Default)]
 pub struct Bool;
 #[derive(Debug, Clone, Copy, Default)]
 pub struct Byte;
 #[derive(Debug, Clone, Copy, Default)]
 pub struct Int32;
 #[derive(Debug, Clone, Copy, Default)]
 pub struct Int64;
 #[derive(Debug, Clone, Copy, Default)]
 pub struct SizeT;
 impl<'ctx> IntKind<'ctx> for Bool {
    fn get_int_type<G: CodeGenerator + ?Sized>(
        &self,
        _generator: &G,
        ctx: &'ctx Context,
    ) -> IntType<'ctx> {
        ctx.bool_type()
    }
 }
 impl<'ctx> IntKind<'ctx> for Byte {
    fn get_int_type<G: CodeGenerator + ?Sized>(
        &self,
        _generator: &G,
        ctx: &'ctx Context,
    ) -> IntType<'ctx> {
        ctx.i8_type()
    }
 }
 impl<'ctx> IntKind<'ctx> for Int32 {
    fn get_int_type<G: CodeGenerator + ?Sized>(
        &self,
        _generator: &G,
        ctx: &'ctx Context,
    ) -> IntType<'ctx> {
        ctx.i32_type()
    }
 }
 impl<'ctx> IntKind<'ctx> for Int64 {
    fn get_int_type<G: CodeGenerator + ?Sized>(
        &self,
        _generator: &G,
        ctx: &'ctx Context,
    ) -> IntType<'ctx> {
        ctx.i64_type()
    }
 }
 impl<'ctx> IntKind<'ctx> for SizeT {
    fn get_int_type<G: CodeGenerator + ?Sized>(
        &self,
        generator: &G,
        ctx: &'ctx Context,
    ) -> IntType<'ctx> {
        generator.get_size_type(ctx)
    }
 }
 #[derive(Debug, Clone, Copy)]
 pub struct AnyInt<'ctx>(pub IntType<'ctx>);
 impl<'ctx> IntKind<'ctx> for AnyInt<'ctx> {
    fn get_int_type<G: CodeGenerator + ?Sized>(
        &self,
        _generator: &G,
        _ctx: &'ctx Context,
    ) -> IntType<'ctx> {
        self.0
    }
 }
 #[derive(Debug, Clone, Copy, Default)]
 pub struct Int<N>(pub N);
 impl<'ctx, N: IntKind<'ctx>> Model<'ctx> for Int<N> {
    type Value = IntValue<'ctx>;
    type Type = IntType<'ctx>;
    fn llvm_type<G: CodeGenerator + ?Sized>(
        &self,
        generator: &G,
        ctx: &'ctx Context,
    ) -> Self::Type {
        self.0.get_int_type(generator, ctx)
    }
    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
        ty: T,
    ) -> Result<(), ModelError> {
        let ty = ty.as_basic_type_enum();
        let Ok(ty) = IntType::try_from(ty) else {
            return Err(ModelError(format!("Expecting IntType, but got {ty:?}")));
        };
        let exp_ty = self.0.get_int_type(generator, ctx);
        if ty.get_bit_width() != exp_ty.get_bit_width() {
            return Err(ModelError(format!(
                "Expecting IntType to have {} bit(s), but got {} bit(s)",
                exp_ty.get_bit_width(),
                ty.get_bit_width()
            )));
        }
        Ok(())
    }
 }
 impl<'ctx, N: IntKind<'ctx>> Int<N> {
    pub fn const_int<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
        value: u64,
        sign_extend: bool,
    ) -> Instance<'ctx, Self> {
        let value = self.llvm_type(generator, ctx).const_int(value, sign_extend);
        unsafe { self.believe_value(value) }
    }
    pub fn const_0<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
    ) -> Instance<'ctx, Self> {
        let value = self.llvm_type(generator, ctx).const_zero();
        unsafe { self.believe_value(value) }
    }
    pub fn const_1<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
    ) -> Instance<'ctx, Self> {
        self.const_int(generator, ctx, 1, false)
    }
    pub fn const_all_ones<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
    ) -> Instance<'ctx, Self> {
        let value = self.llvm_type(generator, ctx).const_all_ones();
        unsafe { self.believe_value(value) }
    }
    pub fn s_extend_or_bit_cast<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        value: IntValue<'ctx>,
    ) -> Instance<'ctx, Self> {
        assert!(
            value.get_type().get_bit_width()
                <= self.0.get_int_type(generator, ctx.ctx).get_bit_width()
        );
        let value = ctx
            .builder
            .build_int_s_extend_or_bit_cast(value, self.llvm_type(generator, ctx.ctx), "")
            .unwrap();
        unsafe { self.believe_value(value) }
    }
    pub fn s_extend<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        value: IntValue<'ctx>,
    ) -> Instance<'ctx, Self> {
        assert!(
            value.get_type().get_bit_width()
                < self.0.get_int_type(generator, ctx.ctx).get_bit_width()
        );
        let value =
            ctx.builder.build_int_s_extend(value, self.llvm_type(generator, ctx.ctx), "").unwrap();
        unsafe { self.believe_value(value) }
    }
    pub fn z_extend_or_bit_cast<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        value: IntValue<'ctx>,
    ) -> Instance<'ctx, Self> {
        assert!(
            value.get_type().get_bit_width()
                <= self.0.get_int_type(generator, ctx.ctx).get_bit_width()
        );
        let value = ctx
            .builder
            .build_int_z_extend_or_bit_cast(value, self.llvm_type(generator, ctx.ctx), "")
            .unwrap();
        unsafe { self.believe_value(value) }
    }
    pub fn z_extend<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        value: IntValue<'ctx>,
    ) -> Instance<'ctx, Self> {
        assert!(
            value.get_type().get_bit_width()
                < self.0.get_int_type(generator, ctx.ctx).get_bit_width()
        );
        let value =
            ctx.builder.build_int_z_extend(value, self.llvm_type(generator, ctx.ctx), "").unwrap();
        unsafe { self.believe_value(value) }
    }
    pub fn truncate_or_bit_cast<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        value: IntValue<'ctx>,
    ) -> Instance<'ctx, Self> {
        assert!(
            value.get_type().get_bit_width()
                >= self.0.get_int_type(generator, ctx.ctx).get_bit_width()
        );
        let value = ctx
            .builder
            .build_int_truncate_or_bit_cast(value, self.llvm_type(generator, ctx.ctx), "")
            .unwrap();
        unsafe { self.believe_value(value) }
    }
    pub fn truncate<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        value: IntValue<'ctx>,
    ) -> Instance<'ctx, Self> {
        assert!(
            value.get_type().get_bit_width()
                > self.0.get_int_type(generator, ctx.ctx).get_bit_width()
        );
        let value =
            ctx.builder.build_int_truncate(value, self.llvm_type(generator, ctx.ctx), "").unwrap();
        unsafe { self.believe_value(value) }
    }
    /// `sext` or `trunc` an int to this model's int type. Does nothing if equal bit-widths.
    pub fn s_extend_or_truncate<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        value: IntValue<'ctx>,
    ) -> Instance<'ctx, Self> {
        let their_width = value.get_type().get_bit_width();
        let our_width = self.0.get_int_type(generator, ctx.ctx).get_bit_width();
        match their_width.cmp(&our_width) {
            Ordering::Less => self.s_extend(generator, ctx, value),
            Ordering::Equal => unsafe { self.believe_value(value) },
            Ordering::Greater => self.truncate(generator, ctx, value),
        }
    }
    /// `zext` or `trunc` an int to this model's int type. Does nothing if equal bit-widths.
    pub fn z_extend_or_truncate<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        value: IntValue<'ctx>,
    ) -> Instance<'ctx, Self> {
        let their_width = value.get_type().get_bit_width();
        let our_width = self.0.get_int_type(generator, ctx.ctx).get_bit_width();
        match their_width.cmp(&our_width) {
            Ordering::Less => self.z_extend(generator, ctx, value),
            Ordering::Equal => unsafe { self.believe_value(value) },
            Ordering::Greater => self.truncate(generator, ctx, value),
        }
    }
 }
 impl Int<Bool> {
    #[must_use]
    pub fn const_false<'ctx, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
    ) -> Instance<'ctx, Self> {
        self.const_int(generator, ctx, 0, false)
    }
    #[must_use]
    pub fn const_true<'ctx, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
    ) -> Instance<'ctx, Self> {
        self.const_int(generator, ctx, 1, false)
    }
 }
 impl<'ctx, N: IntKind<'ctx>> Instance<'ctx, Int<N>> {
    pub fn s_extend_or_bit_cast<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        to_int_kind: NewN,
    ) -> Instance<'ctx, Int<NewN>> {
        Int(to_int_kind).s_extend_or_bit_cast(generator, ctx, self.value)
    }
    pub fn s_extend<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        to_int_kind: NewN,
    ) -> Instance<'ctx, Int<NewN>> {
        Int(to_int_kind).s_extend(generator, ctx, self.value)
    }
    pub fn z_extend_or_bit_cast<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        to_int_kind: NewN,
    ) -> Instance<'ctx, Int<NewN>> {
        Int(to_int_kind).z_extend_or_bit_cast(generator, ctx, self.value)
    }
    pub fn z_extend<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        to_int_kind: NewN,
    ) -> Instance<'ctx, Int<NewN>> {
        Int(to_int_kind).z_extend(generator, ctx, self.value)
    }
    pub fn truncate_or_bit_cast<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        to_int_kind: NewN,
    ) -> Instance<'ctx, Int<NewN>> {
        Int(to_int_kind).truncate_or_bit_cast(generator, ctx, self.value)
    }
    pub fn truncate<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        to_int_kind: NewN,
    ) -> Instance<'ctx, Int<NewN>> {
        Int(to_int_kind).truncate(generator, ctx, self.value)
    }
    pub fn s_extend_or_truncate<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        to_int_kind: NewN,
    ) -> Instance<'ctx, Int<NewN>> {
        Int(to_int_kind).s_extend_or_truncate(generator, ctx, self.value)
    }
    pub fn z_extend_or_truncate<NewN: IntKind<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        to_int_kind: NewN,
    ) -> Instance<'ctx, Int<NewN>> {
        Int(to_int_kind).z_extend_or_truncate(generator, ctx, self.value)
    }
    #[must_use]
    pub fn add(&self, ctx: &CodeGenContext<'ctx, '_>, other: Self) -> Self {
        let value = ctx.builder.build_int_add(self.value, other.value, "").unwrap();
        unsafe { self.model.believe_value(value) }
    }
    #[must_use]
    pub fn sub(&self, ctx: &CodeGenContext<'ctx, '_>, other: Self) -> Self {
        let value = ctx.builder.build_int_sub(self.value, other.value, "").unwrap();
        unsafe { self.model.believe_value(value) }
    }
    #[must_use]
    pub fn mul(&self, ctx: &CodeGenContext<'ctx, '_>, other: Self) -> Self {
        let value = ctx.builder.build_int_mul(self.value, other.value, "").unwrap();
        unsafe { self.model.believe_value(value) }
    }
    pub fn compare(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        op: IntPredicate,
        other: Self,
    ) -> Instance<'ctx, Int<Bool>> {
        let value = ctx.builder.build_int_compare(op, self.value, other.value, "").unwrap();
        unsafe { Int(Bool).believe_value(value) }
    }
 }
--- a/nac3core/src/codegen/model/mod.rs
+++ b/nac3core/src/codegen/model/mod.rs
@ -1,17 +0,0 @@
 mod any;
 mod array;
 mod core;
 mod float;
 pub mod function;
 mod int;
 mod ptr;
 mod structure;
 pub mod util;
 pub use any::*;
 pub use array::*;
 pub use core::*;
 pub use float::*;
 pub use int::*;
 pub use ptr::*;
 pub use structure::*;
--- a/nac3core/src/codegen/model/ptr.rs
+++ b/nac3core/src/codegen/model/ptr.rs
@ -1,223 +0,0 @@
 use inkwell::{
    context::Context,
    types::{BasicType, BasicTypeEnum, PointerType},
    values::{IntValue, PointerValue},
    AddressSpace,
 };
 use crate::codegen::{llvm_intrinsics::call_memcpy_generic, CodeGenContext, CodeGenerator};
 use super::*;
 /// A model for [`PointerType`].
 ///
 /// `Item` is the element type this pointer is pointing to, and should be of a [`Model`].
 ///
 // TODO: LLVM 15: `Item` is a Rust type-hint for the LLVM type of value the `.store()/.load()` family
 // of functions return. If a truly opaque pointer is needed, tell the programmer to use `OpaquePtr`.
 #[derive(Debug, Clone, Copy, Default)]
 pub struct Ptr<Item>(pub Item);
 /// An opaque pointer. Like [`Ptr`] but without any Rust type-hints about its element type.
 ///
 /// `.load()/.store()` is not available for [`Instance`]s of opaque pointers.
 pub type OpaquePtr = Ptr<()>;
 // TODO: LLVM 15: `Item: Model<'ctx>` don't even need to be a model anymore. It will only be
 // a type-hint for the `.load()/.store()` functions for the `pointee_ty`.
 //
 // See https://thedan64.github.io/inkwell/inkwell/builder/struct.Builder.html#method.build_load.
 impl<'ctx, Item: Model<'ctx>> Model<'ctx> for Ptr<Item> {
    type Value = PointerValue<'ctx>;
    type Type = PointerType<'ctx>;
    fn llvm_type<G: CodeGenerator + ?Sized>(
        &self,
        generator: &G,
        ctx: &'ctx Context,
    ) -> Self::Type {
        // TODO: LLVM 15: ctx.ptr_type(AddressSpace::default())
        self.0.llvm_type(generator, ctx).ptr_type(AddressSpace::default())
    }
    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
        ty: T,
    ) -> Result<(), ModelError> {
        let ty = ty.as_basic_type_enum();
        let Ok(ty) = PointerType::try_from(ty) else {
            return Err(ModelError(format!("Expecting PointerType, but got {ty:?}")));
        };
        let elem_ty = ty.get_element_type();
        let Ok(elem_ty) = BasicTypeEnum::try_from(elem_ty) else {
            return Err(ModelError(format!(
                "Expecting pointer element type to be a BasicTypeEnum, but got {elem_ty:?}"
            )));
        };
        // TODO: inkwell `get_element_type()` will be deprecated.
        // Remove the check for `get_element_type()` when the time comes.
        self.0
            .check_type(generator, ctx, elem_ty)
            .map_err(|err| err.under_context("a PointerType"))?;
        Ok(())
    }
 }
 impl<'ctx, Item: Model<'ctx>> Ptr<Item> {
    /// Return a ***constant*** nullptr.
    pub fn nullptr<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
    ) -> Instance<'ctx, Ptr<Item>> {
        let ptr = self.llvm_type(generator, ctx).const_null();
        unsafe { self.believe_value(ptr) }
    }
    /// Cast a pointer into this model with [`inkwell::builder::Builder::build_pointer_cast`]
    pub fn pointer_cast<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        ptr: PointerValue<'ctx>,
    ) -> Instance<'ctx, Ptr<Item>> {
        // TODO: LLVM 15: Write in an impl where `Item` does not have to be `Model<'ctx>`.
        // TODO: LLVM 15: This function will only have to be:
        // ```
        // return self.believe_value(ptr);
        // ```
        let t = self.llvm_type(generator, ctx.ctx);
        let ptr = ctx.builder.build_pointer_cast(ptr, t, "").unwrap();
        unsafe { self.believe_value(ptr) }
    }
 }
 impl<'ctx, Item: Model<'ctx>> Instance<'ctx, Ptr<Item>> {
    /// Offset the pointer by [`inkwell::builder::Builder::build_in_bounds_gep`].
    #[must_use]
    pub fn offset(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        offset: IntValue<'ctx>,
    ) -> Instance<'ctx, Ptr<Item>> {
        let p = unsafe { ctx.builder.build_in_bounds_gep(self.value, &[offset], "").unwrap() };
        unsafe { self.model.believe_value(p) }
    }
    /// Offset the pointer by [`inkwell::builder::Builder::build_in_bounds_gep`] by a constant offset.
    #[must_use]
    pub fn offset_const(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        offset: i64,
    ) -> Instance<'ctx, Ptr<Item>> {
        let offset = ctx.ctx.i32_type().const_int(offset as u64, true);
        self.offset(ctx, offset)
    }
    pub fn set_index(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        index: IntValue<'ctx>,
        value: Instance<'ctx, Item>,
    ) {
        self.offset(ctx, index).store(ctx, value);
    }
    pub fn set_index_const(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        index: i64,
        value: Instance<'ctx, Item>,
    ) {
        self.offset_const(ctx, index).store(ctx, value);
    }
    pub fn get_index<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        index: IntValue<'ctx>,
    ) -> Instance<'ctx, Item> {
        self.offset(ctx, index).load(generator, ctx)
    }
    pub fn get_index_const<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        index: i64,
    ) -> Instance<'ctx, Item> {
        self.offset_const(ctx, index).load(generator, ctx)
    }
    /// Load the value with [`inkwell::builder::Builder::build_load`].
    pub fn load<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
    ) -> Instance<'ctx, Item> {
        let value = ctx.builder.build_load(self.value, "").unwrap();
        self.model.0.check_value(generator, ctx.ctx, value).unwrap() // If unwrap() panics, there is a logic error.
    }
    /// Store a value with [`inkwell::builder::Builder::build_store`].
    pub fn store(&self, ctx: &CodeGenContext<'ctx, '_>, value: Instance<'ctx, Item>) {
        ctx.builder.build_store(self.value, value.value).unwrap();
    }
    /// Return a casted pointer of element type `NewElement` with [`inkwell::builder::Builder::build_pointer_cast`].
    pub fn pointer_cast<NewItem: Model<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        new_item: NewItem,
    ) -> Instance<'ctx, Ptr<NewItem>> {
        // TODO: LLVM 15: Write in an impl where `Item` does not have to be `Model<'ctx>`.
        Ptr(new_item).pointer_cast(generator, ctx, self.value)
    }
    /// Cast this pointer to `uint8_t*`
    pub fn cast_to_pi8<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
    ) -> Instance<'ctx, Ptr<Int<Byte>>> {
        Ptr(Int(Byte)).pointer_cast(generator, ctx, self.value)
    }
    /// Check if the pointer is null with [`inkwell::builder::Builder::build_is_null`].
    pub fn is_null(&self, ctx: &CodeGenContext<'ctx, '_>) -> Instance<'ctx, Int<Bool>> {
        let value = ctx.builder.build_is_null(self.value, "").unwrap();
        unsafe { Int(Bool).believe_value(value) }
    }
    /// Check if the pointer is not null with [`inkwell::builder::Builder::build_is_not_null`].
    pub fn is_not_null(&self, ctx: &CodeGenContext<'ctx, '_>) -> Instance<'ctx, Int<Bool>> {
        let value = ctx.builder.build_is_not_null(self.value, "").unwrap();
        unsafe { Int(Bool).believe_value(value) }
    }
    /// `memcpy` from another pointer.
    pub fn copy_from<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        source: Self,
        num_items: IntValue<'ctx>,
    ) {
        // Force extend `num_items` and `itemsize` to `i64` so their types would match.
        let itemsize = self.model.size_of(generator, ctx.ctx);
        let itemsize = Int(SizeT).z_extend_or_truncate(generator, ctx, itemsize);
        let num_items = Int(SizeT).z_extend_or_truncate(generator, ctx, num_items);
        let totalsize = itemsize.mul(ctx, num_items);
        let is_volatile = ctx.ctx.bool_type().const_zero(); // is_volatile = false
        call_memcpy_generic(ctx, self.value, source.value, totalsize.value, is_volatile);
    }
 }
--- a/nac3core/src/codegen/model/structure.rs
+++ b/nac3core/src/codegen/model/structure.rs
@ -1,364 +0,0 @@
 use std::fmt;
 use inkwell::{
    context::Context,
    types::{BasicType, BasicTypeEnum, StructType},
    values::{BasicValueEnum, StructValue},
 };
 use crate::codegen::{CodeGenContext, CodeGenerator};
 use super::*;
 /// A traveral that traverses a Rust `struct` that is used to declare an LLVM's struct's field types.
 pub trait FieldTraversal<'ctx> {
    /// Output type of [`FieldTraversal::add`].
    type Output<M>;
    /// Traverse through the type of a declared field and do something with it.
    ///
    /// * `name` - The cosmetic name of the LLVM field. Used for debugging.
    /// * `model` - The [`Model`] representing the LLVM type of this field.
    fn add<M: Model<'ctx>>(&mut self, name: &'static str, model: M) -> Self::Output<M>;
    /// Like [`FieldTraversal::add`] but [`Model`] is automatically inferred from its [`Default`] trait.
    fn add_auto<M: Model<'ctx> + Default>(&mut self, name: &'static str) -> Self::Output<M> {
        self.add(name, M::default())
    }
 }
 /// Descriptor of an LLVM struct field.
 #[derive(Debug, Clone, Copy)]
 pub struct GepField<M> {
    /// The GEP index of this field. This is the index to use with `build_gep`.
    pub gep_index: u32,
    /// The cosmetic name of this field.
    pub name: &'static str,
    /// The [`Model`] of this field's type.
    pub model: M,
 }
 /// A traversal to calculate the GEP index of fields.
 pub struct GepFieldTraversal {
    /// The current GEP index.
    gep_index_counter: u32,
 }
 impl<'ctx> FieldTraversal<'ctx> for GepFieldTraversal {
    type Output<M> = GepField<M>;
    fn add<M: Model<'ctx>>(&mut self, name: &'static str, model: M) -> Self::Output<M> {
        let gep_index = self.gep_index_counter;
        self.gep_index_counter += 1;
        Self::Output { gep_index, name, model }
    }
 }
 /// A traversal to collect the field types of a struct.
 ///
 /// This is used to collect field types and construct the LLVM struct type with [`Context::struct_type`].
 struct TypeFieldTraversal<'ctx, 'a, G: CodeGenerator + ?Sized> {
    generator: &'a G,
    ctx: &'ctx Context,
    /// The collected field types so far in exact order.
    field_types: Vec<BasicTypeEnum<'ctx>>,
 }
 impl<'ctx, 'a, G: CodeGenerator + ?Sized> FieldTraversal<'ctx> for TypeFieldTraversal<'ctx, 'a, G> {
    type Output<M> = (); // Checking types return nothing.
    fn add<M: Model<'ctx>>(&mut self, _name: &'static str, model: M) -> Self::Output<M> {
        let t = model.llvm_type(self.generator, self.ctx).as_basic_type_enum();
        self.field_types.push(t);
    }
 }
 /// A traversal to check the types of fields.
 struct CheckTypeFieldTraversal<'ctx, 'a, G: CodeGenerator + ?Sized> {
    generator: &'a mut G,
    ctx: &'ctx Context,
    /// The current GEP index, so we can tell the index of the field we are checking
    /// and report the GEP index.
    gep_index_counter: u32,
    /// The [`StructType`] to check.
    scrutinee: StructType<'ctx>,
    /// The list of collected errors so far.
    errors: Vec<ModelError>,
 }
 impl<'ctx, 'a, G: CodeGenerator + ?Sized> FieldTraversal<'ctx>
    for CheckTypeFieldTraversal<'ctx, 'a, G>
 {
    type Output<M> = (); // Checking types return nothing.
    fn add<M: Model<'ctx>>(&mut self, name: &'static str, model: M) -> Self::Output<M> {
        let gep_index = self.gep_index_counter;
        self.gep_index_counter += 1;
        if let Some(t) = self.scrutinee.get_field_type_at_index(gep_index) {
            if let Err(err) = model.check_type(self.generator, self.ctx, t) {
                self.errors
                    .push(err.under_context(format!("field #{gep_index} '{name}'").as_str()));
            }
        }
        // Otherwise, it will be caught by Struct's `check_type`.
    }
 }
 /// A trait for Rust structs identifying LLVM structures.
 ///
 /// ### Example
 ///
 /// Suppose you want to define this structure:
 /// ```c
 /// template <typename T>
 /// struct ContiguousNDArray {
 ///     size_t ndims;
 ///     size_t* shape;
 ///     T* data;
 /// }
 /// ```
 ///
 /// This is how it should be done:
 /// ```ignore
 /// pub struct ContiguousNDArrayFields<'ctx, F: FieldTraversal<'ctx>, Item: Model<'ctx>> {
 ///     pub ndims: F::Out<Int<SizeT>>,
 ///     pub shape: F::Out<Ptr<Int<SizeT>>>,
 ///     pub data: F::Out<Ptr<Item>>,
 /// }
 ///
 /// /// An ndarray without strides and non-opaque `data` field in NAC3.
 /// #[derive(Debug, Clone, Copy)]
 /// pub struct ContiguousNDArray<M> {
 ///     /// [`Model`] of the items.
 ///     pub item: M,
 /// }
 ///
 /// impl<'ctx, Item: Model<'ctx>> StructKind<'ctx> for ContiguousNDArray<Item> {
 ///     type Fields<F: FieldTraversal<'ctx>> = ContiguousNDArrayFields<'ctx, F, Item>;
 ///
 ///     fn traverse_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
 ///         // The order of `traversal.add*` is important
 ///         Self::Fields {
 ///             ndims: traversal.add_auto("ndims"),
 ///             shape: traversal.add_auto("shape"),
 ///             data: traversal.add("data", Ptr(self.item)),
 ///         }
 ///     }
 /// }
 /// ```
 ///
 /// The [`FieldTraversal`] here is a mechanism to allow the fields of `ContiguousNDArrayFields` to be
 /// traversed to do useful work such as:
 ///
 /// - To create the [`StructType`] of `ContiguousNDArray` by collecting [`BasicType`]s of the fields.
 /// - To enable the `.gep(ctx, |f| f.ndims).store(ctx, ...)` syntax.
 ///
 /// Suppose now that you have defined `ContiguousNDArray` and you want to allocate a `ContiguousNDArray`
 /// with dtype `float64` in LLVM, this is how you do it:
 /// ```ignore
 /// type F64NDArray = Struct<ContiguousNDArray<Float<Float64>>>; // Type alias for leaner documentation
 /// let model: F64NDArray = Struct(ContigousNDArray { item: Float(Float64) });
 /// let ndarray: Instance<'ctx, Ptr<F64NDArray>> = model.alloca(generator, ctx);
 /// ```
 ///
 /// ...and here is how you may manipulate/access `ndarray`:
 ///
 /// (NOTE: some arguments have been omitted)
 ///
 /// ```ignore
 /// // Get `&ndarray->data`
 /// ndarray.gep(|f| f.data); // type: Instance<'ctx, Ptr<Float<Float64>>>
 ///
 /// // Get `ndarray->ndims`
 /// ndarray.get(|f| f.ndims); // type: Instance<'ctx, Int<SizeT>>
 ///
 /// // Get `&ndarray->ndims`
 /// ndarray.gep(|f| f.ndims); // type: Instance<'ctx, Ptr<Int<SizeT>>>
 ///
 /// // Get `ndarray->shape[0]`
 /// ndarray.get(|f| f.shape).get_index_const(0); // Instance<'ctx, Int<SizeT>>
 ///
 /// // Get `&ndarray->shape[2]`
 /// ndarray.get(|f| f.shape).offset_const(2); // Instance<'ctx, Ptr<Int<SizeT>>>
 ///
 /// // Do `ndarray->ndims = 3;`
 /// let num_3 = Int(SizeT).const_int(3);
 /// ndarray.set(|f| f.ndims, num_3);
 /// ```
 pub trait StructKind<'ctx>: fmt::Debug + Clone + Copy {
    /// The associated fields of this struct.
    type Fields<F: FieldTraversal<'ctx>>;
    /// Traverse through all fields of this [`StructKind`].
    ///
    /// Only used internally in this module for implementing other components.
    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F>;
    /// Get a convenience structure to get a struct field's GEP index through its corresponding Rust field.
    ///
    /// Only used internally in this module for implementing other components.
    fn fields(&self) -> Self::Fields<GepFieldTraversal> {
        self.iter_fields(&mut GepFieldTraversal { gep_index_counter: 0 })
    }
    /// Get the LLVM [`StructType`] of this [`StructKind`].
    fn get_struct_type<G: CodeGenerator + ?Sized>(
        &self,
        generator: &G,
        ctx: &'ctx Context,
    ) -> StructType<'ctx> {
        let mut traversal = TypeFieldTraversal { generator, ctx, field_types: Vec::new() };
        self.iter_fields(&mut traversal);
        ctx.struct_type(&traversal.field_types, false)
    }
 }
 /// A model for LLVM struct.
 ///
 /// `S` should be of a [`StructKind`].
 #[derive(Debug, Clone, Copy, Default)]
 pub struct Struct<S>(pub S);
 impl<'ctx, S: StructKind<'ctx>> Struct<S> {
    /// Create a constant struct value from its fields.
    ///
    /// This function also validates `fields` and panic when there is something wrong.
    pub fn const_struct<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
        fields: &[BasicValueEnum<'ctx>],
    ) -> Instance<'ctx, Self> {
        // NOTE: There *could* have been a functor `F<M> = Instance<'ctx, M>` for `S::Fields<F>`
        // to create a more user-friendly interface, but Rust's type system is not sophisticated enough
        // and if you try doing that Rust would force you put lifetimes everywhere.
        let val = ctx.const_struct(fields, false);
        self.check_value(generator, ctx, val).unwrap()
    }
 }
 impl<'ctx, S: StructKind<'ctx>> Model<'ctx> for Struct<S> {
    type Value = StructValue<'ctx>;
    type Type = StructType<'ctx>;
    fn llvm_type<G: CodeGenerator + ?Sized>(
        &self,
        generator: &G,
        ctx: &'ctx Context,
    ) -> Self::Type {
        self.0.get_struct_type(generator, ctx)
    }
    fn check_type<T: BasicType<'ctx>, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
        ty: T,
    ) -> Result<(), ModelError> {
        let ty = ty.as_basic_type_enum();
        let Ok(ty) = StructType::try_from(ty) else {
            return Err(ModelError(format!("Expecting StructType, but got {ty:?}")));
        };
        // Check each field individually.
        let mut traversal = CheckTypeFieldTraversal {
            generator,
            ctx,
            gep_index_counter: 0,
            errors: Vec::new(),
            scrutinee: ty,
        };
        self.0.iter_fields(&mut traversal);
        // Check the number of fields.
        let exp_num_fields = traversal.gep_index_counter;
        let got_num_fields = u32::try_from(ty.get_field_types().len()).unwrap();
        if exp_num_fields != got_num_fields {
            return Err(ModelError(format!(
                "Expecting StructType with {exp_num_fields} field(s), but got {got_num_fields}"
            )));
        }
        if !traversal.errors.is_empty() {
            // Currently, only the first error is reported.
            return Err(traversal.errors[0].clone());
        }
        Ok(())
    }
 }
 impl<'ctx, S: StructKind<'ctx>> Instance<'ctx, Struct<S>> {
    /// Get a field with [`StructValue::get_field_at_index`].
    pub fn get_field<G: CodeGenerator + ?Sized, M, GetField>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
        get_field: GetField,
    ) -> Instance<'ctx, M>
    where
        M: Model<'ctx>,
        GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
    {
        let field = get_field(self.model.0.fields());
        let val = self.value.get_field_at_index(field.gep_index).unwrap();
        field.model.check_value(generator, ctx, val).unwrap()
    }
 }
 impl<'ctx, S: StructKind<'ctx>> Instance<'ctx, Ptr<Struct<S>>> {
    /// Get a pointer to a field with [`Builder::build_in_bounds_gep`].
    pub fn gep<M, GetField>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        get_field: GetField,
    ) -> Instance<'ctx, Ptr<M>>
    where
        M: Model<'ctx>,
        GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
    {
        let field = get_field(self.model.0 .0.fields());
        let llvm_i32 = ctx.ctx.i32_type();
        let ptr = unsafe {
            ctx.builder
                .build_in_bounds_gep(
                    self.value,
                    &[llvm_i32.const_zero(), llvm_i32.const_int(u64::from(field.gep_index), false)],
                    field.name,
                )
                .unwrap()
        };
        unsafe { Ptr(field.model).believe_value(ptr) }
    }
    /// Convenience function equivalent to `.gep(...).load(...)`.
    pub fn get<M, GetField, G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        get_field: GetField,
    ) -> Instance<'ctx, M>
    where
        M: Model<'ctx>,
        GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
    {
        self.gep(ctx, get_field).load(generator, ctx)
    }
    /// Convenience function equivalent to `.gep(...).store(...)`.
    pub fn set<M, GetField>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        get_field: GetField,
        value: Instance<'ctx, M>,
    ) where
        M: Model<'ctx>,
        GetField: FnOnce(S::Fields<GepFieldTraversal>) -> GepField<M>,
    {
        self.gep(ctx, get_field).store(ctx, value);
    }
 }
--- a/nac3core/src/codegen/model/util.rs
+++ b/nac3core/src/codegen/model/util.rs
@ -1,42 +0,0 @@
 use crate::codegen::{
    stmt::{gen_for_callback_incrementing, BreakContinueHooks},
    CodeGenContext, CodeGenerator,
 };
 use super::*;
 /// Like [`gen_for_callback_incrementing`] with [`Model`] abstractions.
 ///
 /// `stop` is not included.
 pub fn gen_for_model<'ctx, 'a, G, F, N>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, 'a>,
    start: Instance<'ctx, Int<N>>,
    stop: Instance<'ctx, Int<N>>,
    step: Instance<'ctx, Int<N>>,
    body: F,
 ) -> Result<(), String>
 where
    G: CodeGenerator + ?Sized,
    F: FnOnce(
        &mut G,
        &mut CodeGenContext<'ctx, 'a>,
        BreakContinueHooks<'ctx>,
        Instance<'ctx, Int<N>>,
    ) -> Result<(), String>,
    N: IntKind<'ctx> + Default,
 {
    let int_model = Int(N::default());
    gen_for_callback_incrementing(
        generator,
        ctx,
        None,
        start.value,
        (stop.value, false),
        |g, ctx, hooks, i| {
            let i = unsafe { int_model.believe_value(i) };
            body(g, ctx, hooks, i)
        },
        step.value,
    )
 }
--- a/nac3core/src/codegen/numpy.rs
+++ b/nac3core/src/codegen/numpy.rs
--- a/nac3core/src/codegen/object/any.rs
+++ b/nac3core/src/codegen/object/any.rs
@ -1,12 +0,0 @@
 use inkwell::values::BasicValueEnum;
 use crate::typecheck::typedef::Type;
 /// A NAC3 LLVM Python object of any type.
 #[derive(Debug, Clone, Copy)]
 pub struct AnyObject<'ctx> {
    /// Typechecker type of the object.
    pub ty: Type,
    /// LLVM value of the object.
    pub value: BasicValueEnum<'ctx>,
 }
--- a/nac3core/src/codegen/object/list.rs
+++ b/nac3core/src/codegen/object/list.rs
@ -1,87 +0,0 @@
 use crate::{
    codegen::{model::*, CodeGenContext, CodeGenerator},
    typecheck::typedef::{iter_type_vars, Type, TypeEnum},
 };
 use super::any::AnyObject;
 /// Fields of [`List`]
 pub struct ListFields<'ctx, F: FieldTraversal<'ctx>, Item: Model<'ctx>> {
    /// Array pointer to content
    pub items: F::Output<Ptr<Item>>,
    /// Number of items in the array
    pub len: F::Output<Int<SizeT>>,
 }
 /// A list in NAC3.
 #[derive(Debug, Clone, Copy, Default)]
 pub struct List<Item> {
    /// Model of the list items
    pub item: Item,
 }
 impl<'ctx, Item: Model<'ctx>> StructKind<'ctx> for List<Item> {
    type Fields<F: FieldTraversal<'ctx>> = ListFields<'ctx, F, Item>;
    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
        Self::Fields {
            items: traversal.add("items", Ptr(self.item)),
            len: traversal.add_auto("len"),
        }
    }
 }
 impl<'ctx, Item: Model<'ctx>> Instance<'ctx, Ptr<Struct<List<Item>>>> {
    /// Cast the items pointer to `uint8_t*`.
    pub fn with_pi8_items<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> Instance<'ctx, Ptr<Struct<List<Int<Byte>>>>> {
        self.pointer_cast(generator, ctx, Struct(List { item: Int(Byte) }))
    }
 }
 /// A NAC3 Python List object.
 #[derive(Debug, Clone, Copy)]
 pub struct ListObject<'ctx> {
    /// Typechecker type of the list items
    pub item_type: Type,
    pub instance: Instance<'ctx, Ptr<Struct<List<Any<'ctx>>>>>,
 }
 impl<'ctx> ListObject<'ctx> {
    /// Create a [`ListObject`] from an LLVM value and its typechecker [`Type`].
    pub fn from_object<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        object: AnyObject<'ctx>,
    ) -> Self {
        // Check typechecker type and extract `item_type`
        let item_type = match &*ctx.unifier.get_ty(object.ty) {
            TypeEnum::TObj { obj_id, params, .. }
                if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
            {
                iter_type_vars(params).next().unwrap().ty // Extract `item_type`
            }
            _ => {
                panic!("Expecting type to be a list, but got {}", ctx.unifier.stringify(object.ty))
            }
        };
        let plist = Ptr(Struct(List { item: Any(ctx.get_llvm_type(generator, item_type)) }));
        // Create object
        let value = plist.check_value(generator, ctx.ctx, object.value).unwrap();
        ListObject { item_type, instance: value }
    }
    /// Get the `len()` of this list.
    pub fn len<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> Instance<'ctx, Int<SizeT>> {
        self.instance.get(generator, ctx, |f| f.len)
    }
 }
--- a/nac3core/src/codegen/object/mod.rs
+++ b/nac3core/src/codegen/object/mod.rs
@ -1,5 +0,0 @@
 pub mod any;
 pub mod list;
 pub mod ndarray;
 pub mod tuple;
 pub mod utils;
--- a/nac3core/src/codegen/object/ndarray/array.rs
+++ b/nac3core/src/codegen/object/ndarray/array.rs
@ -1,184 +0,0 @@
 use super::NDArrayObject;
 use crate::{
    codegen::{
        irrt::{
            call_nac3_ndarray_array_set_and_validate_list_shape,
            call_nac3_ndarray_array_write_list_to_array,
        },
        model::*,
        object::{any::AnyObject, list::ListObject},
        stmt::gen_if_else_expr_callback,
        CodeGenContext, CodeGenerator,
    },
    toplevel::helper::{arraylike_flatten_element_type, arraylike_get_ndims},
    typecheck::typedef::{Type, TypeEnum},
 };
 /// Get the expected `dtype` and `ndims` of the ndarray returned by `np_array(list)`.
 fn get_list_object_dtype_and_ndims<'ctx>(
    ctx: &mut CodeGenContext<'ctx, '_>,
    list: ListObject<'ctx>,
 ) -> (Type, u64) {
    let dtype = arraylike_flatten_element_type(&mut ctx.unifier, list.item_type);
    let ndims = arraylike_get_ndims(&mut ctx.unifier, list.item_type);
    let ndims = ndims + 1; // To count `list` itself.
    (dtype, ndims)
 }
 impl<'ctx> NDArrayObject<'ctx> {
    /// Implementation of `np_array(<list>, copy=True)`
    fn make_np_array_list_copy_true_impl<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        list: ListObject<'ctx>,
    ) -> Self {
        let (dtype, ndims_int) = get_list_object_dtype_and_ndims(ctx, list);
        let list_value = list.instance.with_pi8_items(generator, ctx);
        // Validate `list` has a consistent shape.
        // Raise an exception if `list` is something abnormal like `[[1, 2], [3]]`.
        // If `list` has a consistent shape, deduce the shape and write it to `shape`.
        let ndims = Int(SizeT).const_int(generator, ctx.ctx, ndims_int, false);
        let shape = Int(SizeT).array_alloca(generator, ctx, ndims.value);
        call_nac3_ndarray_array_set_and_validate_list_shape(
            generator, ctx, list_value, ndims, shape,
        );
        let ndarray = NDArrayObject::alloca(generator, ctx, dtype, ndims_int);
        ndarray.copy_shape_from_array(generator, ctx, shape);
        ndarray.create_data(generator, ctx);
        // Copy all contents from the list.
        call_nac3_ndarray_array_write_list_to_array(generator, ctx, list_value, ndarray.instance);
        ndarray
    }
    /// Implementation of `np_array(<list>, copy=None)`
    fn make_np_array_list_copy_none_impl<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        list: ListObject<'ctx>,
    ) -> Self {
        // np_array without copying is only possible `list` is not nested.
        //
        // If `list` is `list[T]`, we can create an ndarray with `data` set
        // to the array pointer of `list`.
        //
        // If `list` is `list[list[T]]` or worse, copy.
        let (dtype, ndims) = get_list_object_dtype_and_ndims(ctx, list);
        if ndims == 1 {
            // `list` is not nested
            let ndarray = NDArrayObject::alloca(generator, ctx, dtype, 1);
            // Set data
            let data = list.instance.get(generator, ctx, |f| f.items).cast_to_pi8(generator, ctx);
            ndarray.instance.set(ctx, |f| f.data, data);
            // ndarray->shape[0] = list->len;
            let shape = ndarray.instance.get(generator, ctx, |f| f.shape);
            let list_len = list.instance.get(generator, ctx, |f| f.len);
            shape.set_index_const(ctx, 0, list_len);
            // Set strides, the `data` is contiguous
            ndarray.set_strides_contiguous(generator, ctx);
            ndarray
        } else {
            // `list` is nested, copy
            NDArrayObject::make_np_array_list_copy_true_impl(generator, ctx, list)
        }
    }
    /// Implementation of `np_array(<list>, copy=copy)`
    fn make_np_array_list_impl<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        list: ListObject<'ctx>,
        copy: Instance<'ctx, Int<Bool>>,
    ) -> Self {
        let (dtype, ndims) = get_list_object_dtype_and_ndims(ctx, list);
        let ndarray = gen_if_else_expr_callback(
            generator,
            ctx,
            |_generator, _ctx| Ok(copy.value),
            |generator, ctx| {
                let ndarray =
                    NDArrayObject::make_np_array_list_copy_true_impl(generator, ctx, list);
                Ok(Some(ndarray.instance.value))
            },
            |generator, ctx| {
                let ndarray =
                    NDArrayObject::make_np_array_list_copy_none_impl(generator, ctx, list);
                Ok(Some(ndarray.instance.value))
            },
        )
        .unwrap()
        .unwrap();
        NDArrayObject::from_value_and_unpacked_types(generator, ctx, ndarray, dtype, ndims)
    }
    /// Implementation of `np_array(<ndarray>, copy=copy)`.
    pub fn make_np_array_ndarray_impl<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        ndarray: NDArrayObject<'ctx>,
        copy: Instance<'ctx, Int<Bool>>,
    ) -> Self {
        let ndarray_val = gen_if_else_expr_callback(
            generator,
            ctx,
            |_generator, _ctx| Ok(copy.value),
            |generator, ctx| {
                let ndarray = ndarray.make_copy(generator, ctx); // Force copy
                Ok(Some(ndarray.instance.value))
            },
            |_generator, _ctx| {
                // No need to copy. Return `ndarray` itself.
                Ok(Some(ndarray.instance.value))
            },
        )
        .unwrap()
        .unwrap();
        NDArrayObject::from_value_and_unpacked_types(
            generator,
            ctx,
            ndarray_val,
            ndarray.dtype,
            ndarray.ndims,
        )
    }
    /// Create a new ndarray like `np.array()`.
    ///
    /// NOTE: The `ndmin` argument is not here. You may want to
    /// do [`NDArrayObject::atleast_nd`] to achieve that.
    pub fn make_np_array<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        object: AnyObject<'ctx>,
        copy: Instance<'ctx, Int<Bool>>,
    ) -> Self {
        match &*ctx.unifier.get_ty(object.ty) {
            TypeEnum::TObj { obj_id, .. }
                if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
            {
                let list = ListObject::from_object(generator, ctx, object);
                NDArrayObject::make_np_array_list_impl(generator, ctx, list, copy)
            }
            TypeEnum::TObj { obj_id, .. }
                if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
            {
                let ndarray = NDArrayObject::from_object(generator, ctx, object);
                NDArrayObject::make_np_array_ndarray_impl(generator, ctx, ndarray, copy)
            }
            _ => panic!("Unrecognized object type: {}", ctx.unifier.stringify(object.ty)), // Typechecker ensures this
        }
    }
 }
--- a/nac3core/src/codegen/object/ndarray/broadcast.rs
+++ b/nac3core/src/codegen/object/ndarray/broadcast.rs
@ -1,139 +0,0 @@
 use itertools::Itertools;
 use crate::codegen::{
    irrt::{call_nac3_ndarray_broadcast_shapes, call_nac3_ndarray_broadcast_to},
    model::*,
    CodeGenContext, CodeGenerator,
 };
 use super::NDArrayObject;
 /// Fields of [`ShapeEntry`]
 pub struct ShapeEntryFields<'ctx, F: FieldTraversal<'ctx>> {
    pub ndims: F::Output<Int<SizeT>>,
    pub shape: F::Output<Ptr<Int<SizeT>>>,
 }
 /// An IRRT structure used in broadcasting.
 #[derive(Debug, Clone, Copy, Default)]
 pub struct ShapeEntry;
 impl<'ctx> StructKind<'ctx> for ShapeEntry {
    type Fields<F: FieldTraversal<'ctx>> = ShapeEntryFields<'ctx, F>;
    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
        Self::Fields { ndims: traversal.add_auto("ndims"), shape: traversal.add_auto("shape") }
    }
 }
 impl<'ctx> NDArrayObject<'ctx> {
    /// Create a broadcast view on this ndarray with a target shape.
    ///
    /// The input shape will be checked to make sure that it contains no negative values.
    ///
    /// * `target_ndims` - The ndims type after broadcasting to the given shape.
    ///   The caller has to figure this out for this function.
    /// * `target_shape` - An array pointer pointing to the target shape.
    #[must_use]
    pub fn broadcast_to<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        target_ndims: u64,
        target_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
    ) -> Self {
        let broadcast_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, target_ndims);
        broadcast_ndarray.copy_shape_from_array(generator, ctx, target_shape);
        call_nac3_ndarray_broadcast_to(generator, ctx, self.instance, broadcast_ndarray.instance);
        broadcast_ndarray
    }
 }
 /// A result produced by [`broadcast_all_ndarrays`]
 #[derive(Debug, Clone)]
 pub struct BroadcastAllResult<'ctx> {
    /// The statically known `ndims` of the broadcast result.
    pub ndims: u64,
    /// The broadcasting shape.
    pub shape: Instance<'ctx, Ptr<Int<SizeT>>>,
    /// Broadcasted views on the inputs.
    ///
    /// All of them will have `shape` [`BroadcastAllResult::shape`] and
    /// `ndims` [`BroadcastAllResult::ndims`]. The length of the vector
    /// is the same as the input.
    pub ndarrays: Vec<NDArrayObject<'ctx>>,
 }
 /// Helper function to call `call_nac3_ndarray_broadcast_shapes`
 fn broadcast_shapes<'ctx, G: CodeGenerator + ?Sized>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
    in_shape_entries: &[(Instance<'ctx, Ptr<Int<SizeT>>>, u64)], // (shape, shape's length/ndims)
    broadcast_ndims: u64,
    broadcast_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
 ) {
    // Prepare input shape entries to be passed to `call_nac3_ndarray_broadcast_shapes`.
    let num_shape_entries = Int(SizeT).const_int(
        generator,
        ctx.ctx,
        u64::try_from(in_shape_entries.len()).unwrap(),
        false,
    );
    let shape_entries = Struct(ShapeEntry).array_alloca(generator, ctx, num_shape_entries.value);
    for (i, (in_shape, in_ndims)) in in_shape_entries.iter().enumerate() {
        let pshape_entry = shape_entries.offset_const(ctx, i64::try_from(i).unwrap());
        let in_ndims = Int(SizeT).const_int(generator, ctx.ctx, *in_ndims, false);
        pshape_entry.set(ctx, |f| f.ndims, in_ndims);
        pshape_entry.set(ctx, |f| f.shape, *in_shape);
    }
    let broadcast_ndims = Int(SizeT).const_int(generator, ctx.ctx, broadcast_ndims, false);
    call_nac3_ndarray_broadcast_shapes(
        generator,
        ctx,
        num_shape_entries,
        shape_entries,
        broadcast_ndims,
        broadcast_shape,
    );
 }
 impl<'ctx> NDArrayObject<'ctx> {
    /// Broadcast all ndarrays according to `np.broadcast()` and return a [`BroadcastAllResult`]
    /// containing all the information of the result of the broadcast operation.
    pub fn broadcast<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        ndarrays: &[Self],
    ) -> BroadcastAllResult<'ctx> {
        assert!(!ndarrays.is_empty());
        // Infer the broadcast output ndims.
        let broadcast_ndims_int = ndarrays.iter().map(|ndarray| ndarray.ndims).max().unwrap();
        let broadcast_ndims = Int(SizeT).const_int(generator, ctx.ctx, broadcast_ndims_int, false);
        let broadcast_shape = Int(SizeT).array_alloca(generator, ctx, broadcast_ndims.value);
        let shape_entries = ndarrays
            .iter()
            .map(|ndarray| (ndarray.instance.get(generator, ctx, |f| f.shape), ndarray.ndims))
            .collect_vec();
        broadcast_shapes(generator, ctx, &shape_entries, broadcast_ndims_int, broadcast_shape);
        // Broadcast all the inputs to shape `dst_shape`.
        let broadcast_ndarrays: Vec<_> = ndarrays
            .iter()
            .map(|ndarray| {
                ndarray.broadcast_to(generator, ctx, broadcast_ndims_int, broadcast_shape)
            })
            .collect_vec();
        BroadcastAllResult {
            ndims: broadcast_ndims_int,
            shape: broadcast_shape,
            ndarrays: broadcast_ndarrays,
        }
    }
 }
--- a/nac3core/src/codegen/object/ndarray/factory.rs
+++ b/nac3core/src/codegen/object/ndarray/factory.rs
@ -1,176 +0,0 @@
 use inkwell::{values::BasicValueEnum, IntPredicate};
 use crate::{
    codegen::{
        irrt::call_nac3_ndarray_util_assert_shape_no_negative, model::*, CodeGenContext,
        CodeGenerator,
    },
    typecheck::typedef::Type,
 };
 use super::NDArrayObject;
 /// Get the zero value in `np.zeros()` of a `dtype`.
 fn ndarray_zero_value<'ctx, G: CodeGenerator + ?Sized>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
    dtype: Type,
 ) -> BasicValueEnum<'ctx> {
    if [ctx.primitives.int32, ctx.primitives.uint32]
        .iter()
        .any(|ty| ctx.unifier.unioned(dtype, *ty))
    {
        ctx.ctx.i32_type().const_zero().into()
    } else if [ctx.primitives.int64, ctx.primitives.uint64]
        .iter()
        .any(|ty| ctx.unifier.unioned(dtype, *ty))
    {
        ctx.ctx.i64_type().const_zero().into()
    } else if ctx.unifier.unioned(dtype, ctx.primitives.float) {
        ctx.ctx.f64_type().const_zero().into()
    } else if ctx.unifier.unioned(dtype, ctx.primitives.bool) {
        ctx.ctx.bool_type().const_zero().into()
    } else if ctx.unifier.unioned(dtype, ctx.primitives.str) {
        ctx.gen_string(generator, "").into()
    } else {
        panic!("unrecognized dtype: {}", ctx.unifier.stringify(dtype));
    }
 }
 /// Get the one value in `np.ones()` of a `dtype`.
 fn ndarray_one_value<'ctx, G: CodeGenerator + ?Sized>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
    dtype: Type,
 ) -> BasicValueEnum<'ctx> {
    if [ctx.primitives.int32, ctx.primitives.uint32]
        .iter()
        .any(|ty| ctx.unifier.unioned(dtype, *ty))
    {
        let is_signed = ctx.unifier.unioned(dtype, ctx.primitives.int32);
        ctx.ctx.i32_type().const_int(1, is_signed).into()
    } else if [ctx.primitives.int64, ctx.primitives.uint64]
        .iter()
        .any(|ty| ctx.unifier.unioned(dtype, *ty))
    {
        let is_signed = ctx.unifier.unioned(dtype, ctx.primitives.int64);
        ctx.ctx.i64_type().const_int(1, is_signed).into()
    } else if ctx.unifier.unioned(dtype, ctx.primitives.float) {
        ctx.ctx.f64_type().const_float(1.0).into()
    } else if ctx.unifier.unioned(dtype, ctx.primitives.bool) {
        ctx.ctx.bool_type().const_int(1, false).into()
    } else if ctx.unifier.unioned(dtype, ctx.primitives.str) {
        ctx.gen_string(generator, "1").into()
    } else {
        panic!("unrecognized dtype: {}", ctx.unifier.stringify(dtype));
    }
 }
 impl<'ctx> NDArrayObject<'ctx> {
    /// Create an ndarray like `np.empty`.
    pub fn make_np_empty<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        dtype: Type,
        ndims: u64,
        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
    ) -> Self {
        // Validate `shape`
        let ndims_llvm = Int(SizeT).const_int(generator, ctx.ctx, ndims, false);
        call_nac3_ndarray_util_assert_shape_no_negative(generator, ctx, ndims_llvm, shape);
        let ndarray = NDArrayObject::alloca(generator, ctx, dtype, ndims);
        ndarray.copy_shape_from_array(generator, ctx, shape);
        ndarray.create_data(generator, ctx);
        ndarray
    }
    /// Create an ndarray like `np.full`.
    pub fn make_np_full<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        dtype: Type,
        ndims: u64,
        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
        fill_value: BasicValueEnum<'ctx>,
    ) -> Self {
        let ndarray = NDArrayObject::make_np_empty(generator, ctx, dtype, ndims, shape);
        ndarray.fill(generator, ctx, fill_value);
        ndarray
    }
    /// Create an ndarray like `np.zero`.
    pub fn make_np_zeros<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        dtype: Type,
        ndims: u64,
        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
    ) -> Self {
        let fill_value = ndarray_zero_value(generator, ctx, dtype);
        NDArrayObject::make_np_full(generator, ctx, dtype, ndims, shape, fill_value)
    }
    /// Create an ndarray like `np.ones`.
    pub fn make_np_ones<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        dtype: Type,
        ndims: u64,
        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
    ) -> Self {
        let fill_value = ndarray_one_value(generator, ctx, dtype);
        NDArrayObject::make_np_full(generator, ctx, dtype, ndims, shape, fill_value)
    }
    /// Create an ndarray like `np.eye`.
    pub fn make_np_eye<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        dtype: Type,
        nrows: Instance<'ctx, Int<SizeT>>,
        ncols: Instance<'ctx, Int<SizeT>>,
        offset: Instance<'ctx, Int<SizeT>>,
    ) -> Self {
        let ndzero = ndarray_zero_value(generator, ctx, dtype);
        let ndone = ndarray_one_value(generator, ctx, dtype);
        let ndarray = NDArrayObject::alloca_dynamic_shape(generator, ctx, dtype, &[nrows, ncols]);
        // Create data and make the matrix like look np.eye()
        ndarray.create_data(generator, ctx);
        ndarray
            .foreach(generator, ctx, |generator, ctx, _hooks, nditer| {
                // NOTE: rows and cols can never be zero here, since this ndarray's `np.size` would be zero
                // and this loop would not execute.
                // Load up `row_i` and `col_i` from indices.
                let row_i = nditer.get_indices().get_index_const(generator, ctx, 0);
                let col_i = nditer.get_indices().get_index_const(generator, ctx, 1);
                let be_one = row_i.add(ctx, offset).compare(ctx, IntPredicate::EQ, col_i);
                let value = ctx.builder.build_select(be_one.value, ndone, ndzero, "value").unwrap();
                let p = nditer.get_pointer(generator, ctx);
                ctx.builder.build_store(p, value).unwrap();
                Ok(())
            })
            .unwrap();
        ndarray
    }
    /// Create an ndarray like `np.identity`.
    pub fn make_np_identity<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        dtype: Type,
        size: Instance<'ctx, Int<SizeT>>,
    ) -> Self {
        // Convenient implementation
        let offset = Int(SizeT).const_0(generator, ctx.ctx);
        NDArrayObject::make_np_eye(generator, ctx, dtype, size, size, offset)
    }
 }
--- a/nac3core/src/codegen/object/ndarray/indexing.rs
+++ b/nac3core/src/codegen/object/ndarray/indexing.rs
@ -1,227 +0,0 @@
 use crate::codegen::{
    irrt::call_nac3_ndarray_index,
    model::*,
    object::utils::slice::{RustSlice, Slice},
    CodeGenContext, CodeGenerator,
 };
 use super::NDArrayObject;
 pub type NDIndexType = Byte;
 /// Fields of [`NDIndex`]
 #[derive(Debug, Clone, Copy)]
 pub struct NDIndexFields<'ctx, F: FieldTraversal<'ctx>> {
    pub type_: F::Output<Int<NDIndexType>>,
    pub data: F::Output<Ptr<Int<Byte>>>,
 }
 /// An IRRT representation of an ndarray subscript index.
 #[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
 pub struct NDIndex;
 impl<'ctx> StructKind<'ctx> for NDIndex {
    type Fields<F: FieldTraversal<'ctx>> = NDIndexFields<'ctx, F>;
    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
        Self::Fields { type_: traversal.add_auto("type"), data: traversal.add_auto("data") }
    }
 }
 // A convenience enum representing a [`NDIndex`].
 #[derive(Debug, Clone)]
 pub enum RustNDIndex<'ctx> {
    SingleElement(Instance<'ctx, Int<Int32>>),
    Slice(RustSlice<'ctx, Int32>),
    NewAxis,
    Ellipsis,
 }
 impl<'ctx> RustNDIndex<'ctx> {
    /// Get the value to set `NDIndex::type` for this variant.
    fn get_type_id(&self) -> u64 {
        // Defined in IRRT, must be in sync
        match self {
            RustNDIndex::SingleElement(_) => 0,
            RustNDIndex::Slice(_) => 1,
            RustNDIndex::NewAxis => 2,
            RustNDIndex::Ellipsis => 3,
        }
    }
    /// Serialize this [`RustNDIndex`] by writing it into an LLVM [`NDIndex`].
    fn write_to_ndindex<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        dst_ndindex_ptr: Instance<'ctx, Ptr<Struct<NDIndex>>>,
    ) {
        // Set `dst_ndindex_ptr->type`
        dst_ndindex_ptr.gep(ctx, |f| f.type_).store(
            ctx,
            Int(NDIndexType::default()).const_int(generator, ctx.ctx, self.get_type_id(), false),
        );
        // Set `dst_ndindex_ptr->data`
        match self {
            RustNDIndex::SingleElement(in_index) => {
                let index_ptr = Int(Int32).alloca(generator, ctx);
                index_ptr.store(ctx, *in_index);
                dst_ndindex_ptr
                    .gep(ctx, |f| f.data)
                    .store(ctx, index_ptr.pointer_cast(generator, ctx, Int(Byte)));
            }
            RustNDIndex::Slice(in_rust_slice) => {
                let user_slice_ptr = Struct(Slice(Int32)).alloca(generator, ctx);
                in_rust_slice.write_to_slice(generator, ctx, user_slice_ptr);
                dst_ndindex_ptr
                    .gep(ctx, |f| f.data)
                    .store(ctx, user_slice_ptr.pointer_cast(generator, ctx, Int(Byte)));
            }
            RustNDIndex::NewAxis | RustNDIndex::Ellipsis => {}
        }
    }
    /// Serialize a list of `RustNDIndex` as a newly allocated LLVM array of `NDIndex`.
    pub fn make_ndindices<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        in_ndindices: &[RustNDIndex<'ctx>],
    ) -> (Instance<'ctx, Int<SizeT>>, Instance<'ctx, Ptr<Struct<NDIndex>>>) {
        let ndindex_model = Struct(NDIndex);
        // Allocate the LLVM ndindices.
        let num_ndindices =
            Int(SizeT).const_int(generator, ctx.ctx, in_ndindices.len() as u64, false);
        let ndindices = ndindex_model.array_alloca(generator, ctx, num_ndindices.value);
        // Initialize all of them.
        for (i, in_ndindex) in in_ndindices.iter().enumerate() {
            let pndindex = ndindices.offset_const(ctx, i64::try_from(i).unwrap());
            in_ndindex.write_to_ndindex(generator, ctx, pndindex);
        }
        (num_ndindices, ndindices)
    }
 }
 impl<'ctx> NDArrayObject<'ctx> {
    /// Get the expected `ndims` after indexing with `indices`.
    #[must_use]
    fn deduce_ndims_after_indexing_with(&self, indices: &[RustNDIndex<'ctx>]) -> u64 {
        let mut ndims = self.ndims;
        for index in indices {
            match index {
                RustNDIndex::SingleElement(_) => {
                    ndims -= 1; // Single elements decrements ndims
                }
                RustNDIndex::NewAxis => {
                    ndims += 1; // `np.newaxis` / `none` adds a new axis
                }
                RustNDIndex::Ellipsis | RustNDIndex::Slice(_) => {}
            }
        }
        ndims
    }
    /// Index into the ndarray, and return a newly-allocated view on this ndarray.
    ///
    /// This function behaves like NumPy's ndarray indexing, but if the indices index
    /// into a single element, an unsized ndarray is returned.
    #[must_use]
    pub fn index<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        indices: &[RustNDIndex<'ctx>],
    ) -> Self {
        let dst_ndims = self.deduce_ndims_after_indexing_with(indices);
        let dst_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, dst_ndims);
        let (num_indices, indices) = RustNDIndex::make_ndindices(generator, ctx, indices);
        call_nac3_ndarray_index(
            generator,
            ctx,
            num_indices,
            indices,
            self.instance,
            dst_ndarray.instance,
        );
        dst_ndarray
    }
 }
 pub mod util {
    use itertools::Itertools;
    use nac3parser::ast::{Expr, ExprKind};
    use crate::{
        codegen::{model::*, object::utils::slice::util::gen_slice, CodeGenContext, CodeGenerator},
        typecheck::typedef::Type,
    };
    use super::RustNDIndex;
    /// Generate LLVM code to transform an ndarray subscript expression to
    /// its list of [`RustNDIndex`]
    ///
    /// i.e.,
    /// ```python
    /// my_ndarray[::3, 1, :2:]
    ///            ^^^^^^^^^^^ Then these into a three `RustNDIndex`es
    /// ```
    pub fn gen_ndarray_subscript_ndindices<'ctx, G: CodeGenerator>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        subscript: &Expr<Option<Type>>,
    ) -> Result<Vec<RustNDIndex<'ctx>>, String> {
        // TODO: Support https://numpy.org/doc/stable/user/basics.indexing.html#dimensional-indexing-tools
        // Annoying notes about `slice`
        //  - `my_array[5]`
        //    - slice is a `Constant`
        //  - `my_array[:5]`
        //    - slice is a `Slice`
        //  - `my_array[:]`
        //    - slice is a `Slice`, but lower upper step would all be `Option::None`
        //  - `my_array[:, :]`
        //    - slice is now a `Tuple` of two `Slice`-s
        //
        // In summary:
        //  - when there is a comma "," within [], `slice` will be a `Tuple` of the entries.
        //  - when there is not comma "," within [] (i.e., just a single entry), `slice` will be that entry itself.
        //
        // So we first "flatten" out the slice expression
        let index_exprs = match &subscript.node {
            ExprKind::Tuple { elts, .. } => elts.iter().collect_vec(),
            _ => vec![subscript],
        };
        // Process all index expressions
        let mut rust_ndindices: Vec<RustNDIndex> = Vec::with_capacity(index_exprs.len()); // Not using iterators here because `?` is used here.
        for index_expr in index_exprs {
            // NOTE: Currently nac3core's slices do not have an object representation,
            // so the code/implementation looks awkward - we have to do pattern matching on the expression
            let ndindex = if let ExprKind::Slice { lower, upper, step } = &index_expr.node {
                // Handle slices
                let slice = gen_slice(generator, ctx, lower, upper, step)?;
                RustNDIndex::Slice(slice)
            } else {
                // Treat and handle everything else as a single element index.
                let index = generator.gen_expr(ctx, index_expr)?.unwrap().to_basic_value_enum(
                    ctx,
                    generator,
                    ctx.primitives.int32, // Must be int32, this checks for illegal values
                )?;
                let index = Int(Int32).check_value(generator, ctx.ctx, index).unwrap();
                RustNDIndex::SingleElement(index)
            };
            rust_ndindices.push(ndindex);
        }
        Ok(rust_ndindices)
    }
 }
--- a/nac3core/src/codegen/object/ndarray/mod.rs
+++ b/nac3core/src/codegen/object/ndarray/mod.rs
@ -1,587 +0,0 @@
 pub mod array;
 pub mod broadcast;
 pub mod factory;
 pub mod indexing;
 pub mod nditer;
 pub mod shape_util;
 pub mod view;
 use inkwell::{
    context::Context,
    types::BasicType,
    values::{BasicValue, BasicValueEnum, PointerValue},
    AddressSpace,
 };
 use crate::{
    codegen::{
        irrt::{
            call_nac3_ndarray_copy_data, call_nac3_ndarray_get_nth_pelement,
            call_nac3_ndarray_get_pelement_by_indices, call_nac3_ndarray_is_c_contiguous,
            call_nac3_ndarray_len, call_nac3_ndarray_nbytes,
            call_nac3_ndarray_set_strides_by_shape, call_nac3_ndarray_size,
        },
        model::*,
        CodeGenContext, CodeGenerator,
    },
    toplevel::{helper::extract_ndims, numpy::unpack_ndarray_var_tys},
    typecheck::typedef::{Type, TypeEnum},
 };
 use super::{any::AnyObject, tuple::TupleObject};
 /// Fields of [`NDArray`]
 pub struct NDArrayFields<'ctx, F: FieldTraversal<'ctx>> {
    pub data: F::Output<Ptr<Int<Byte>>>,
    pub itemsize: F::Output<Int<SizeT>>,
    pub ndims: F::Output<Int<SizeT>>,
    pub shape: F::Output<Ptr<Int<SizeT>>>,
    pub strides: F::Output<Ptr<Int<SizeT>>>,
 }
 /// A strided ndarray in NAC3.
 ///
 /// See IRRT implementation for details about its fields.
 #[derive(Debug, Clone, Copy, Default)]
 pub struct NDArray;
 impl<'ctx> StructKind<'ctx> for NDArray {
    type Fields<F: FieldTraversal<'ctx>> = NDArrayFields<'ctx, F>;
    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
        Self::Fields {
            data: traversal.add_auto("data"),
            itemsize: traversal.add_auto("itemsize"),
            ndims: traversal.add_auto("ndims"),
            shape: traversal.add_auto("shape"),
            strides: traversal.add_auto("strides"),
        }
    }
 }
 /// A NAC3 Python ndarray object.
 #[derive(Debug, Clone, Copy)]
 pub struct NDArrayObject<'ctx> {
    pub dtype: Type,
    pub ndims: u64,
    pub instance: Instance<'ctx, Ptr<Struct<NDArray>>>,
 }
 impl<'ctx> NDArrayObject<'ctx> {
    /// Attempt to convert an [`AnyObject`] into an [`NDArrayObject`].
    pub fn from_object<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        object: AnyObject<'ctx>,
    ) -> NDArrayObject<'ctx> {
        let (dtype, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, object.ty);
        let ndims = extract_ndims(&ctx.unifier, ndims);
        Self::from_value_and_unpacked_types(generator, ctx, object.value, dtype, ndims)
    }
    /// Like [`NDArrayObject::from_object`] but you directly supply the ndarray's
    /// `dtype` and `ndims`.
    pub fn from_value_and_unpacked_types<V: BasicValue<'ctx>, G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        value: V,
        dtype: Type,
        ndims: u64,
    ) -> Self {
        let value = Ptr(Struct(NDArray)).check_value(generator, ctx.ctx, value).unwrap();
        NDArrayObject { dtype, ndims, instance: value }
    }
    /// Get this ndarray's `ndims` as an LLVM constant.
    pub fn ndims_llvm<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &'ctx Context,
    ) -> Instance<'ctx, Int<SizeT>> {
        Int(SizeT).const_int(generator, ctx, self.ndims, false)
    }
    /// Allocate an ndarray on the stack given its `ndims` and `dtype`.
    ///
    /// `shape` and `strides` will be automatically allocated onto the stack.
    ///
    /// The returned ndarray's content will be:
    /// - `data`: uninitialized.
    /// - `itemsize`: set to the `sizeof()` of `dtype`.
    /// - `ndims`: set to the value of  `ndims`.
    /// - `shape`: allocated with an array of length `ndims` with uninitialized values.
    /// - `strides`: allocated with an array of length `ndims` with uninitialized values.
    pub fn alloca<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        dtype: Type,
        ndims: u64,
    ) -> Self {
        let ndarray = Struct(NDArray).alloca(generator, ctx);
        let itemsize = ctx.get_llvm_type(generator, dtype).size_of().unwrap();
        let itemsize = Int(SizeT).z_extend_or_truncate(generator, ctx, itemsize);
        ndarray.set(ctx, |f| f.itemsize, itemsize);
        let ndims_val = Int(SizeT).const_int(generator, ctx.ctx, ndims, false);
        ndarray.set(ctx, |f| f.ndims, ndims_val);
        let shape = Int(SizeT).array_alloca(generator, ctx, ndims_val.value);
        ndarray.set(ctx, |f| f.shape, shape);
        let strides = Int(SizeT).array_alloca(generator, ctx, ndims_val.value);
        ndarray.set(ctx, |f| f.strides, strides);
        NDArrayObject { dtype, ndims, instance: ndarray }
    }
    /// Convenience function. Allocate an [`NDArrayObject`] with a statically known shape.
    ///
    /// The returned [`NDArrayObject`]'s `data` and `strides` are uninitialized.
    pub fn alloca_constant_shape<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        dtype: Type,
        shape: &[u64],
    ) -> Self {
        let ndarray = NDArrayObject::alloca(generator, ctx, dtype, shape.len() as u64);
        // Write shape
        let dst_shape = ndarray.instance.get(generator, ctx, |f| f.shape);
        for (i, dim) in shape.iter().enumerate() {
            let dim = Int(SizeT).const_int(generator, ctx.ctx, *dim, false);
            dst_shape.offset_const(ctx, i64::try_from(i).unwrap()).store(ctx, dim);
        }
        ndarray
    }
    /// Convenience function. Allocate an [`NDArrayObject`] with a dynamically known shape.
    ///
    /// The returned [`NDArrayObject`]'s `data` and `strides` are uninitialized.
    pub fn alloca_dynamic_shape<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        dtype: Type,
        shape: &[Instance<'ctx, Int<SizeT>>],
    ) -> Self {
        let ndarray = NDArrayObject::alloca(generator, ctx, dtype, shape.len() as u64);
        // Write shape
        let dst_shape = ndarray.instance.get(generator, ctx, |f| f.shape);
        for (i, dim) in shape.iter().enumerate() {
            dst_shape.offset_const(ctx, i64::try_from(i).unwrap()).store(ctx, *dim);
        }
        ndarray
    }
    /// Initialize an ndarray's `data` by allocating a buffer on the stack.
    /// The allocated data buffer is considered to be *owned* by the ndarray.
    ///
    /// `strides` of the ndarray will also be updated with `set_strides_by_shape`.
    ///
    /// `shape` and `itemsize` of the ndarray ***must*** be initialized first.
    pub fn create_data<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) {
        let nbytes = self.nbytes(generator, ctx);
        let data = Int(Byte).array_alloca(generator, ctx, nbytes.value);
        self.instance.set(ctx, |f| f.data, data);
        self.set_strides_contiguous(generator, ctx);
    }
    /// Copy shape dimensions from an array.
    pub fn copy_shape_from_array<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        shape: Instance<'ctx, Ptr<Int<SizeT>>>,
    ) {
        let num_items = self.ndims_llvm(generator, ctx.ctx).value;
        self.instance.get(generator, ctx, |f| f.shape).copy_from(generator, ctx, shape, num_items);
    }
    /// Copy shape dimensions from an ndarray.
    /// Panics if `ndims` mismatches.
    pub fn copy_shape_from_ndarray<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        src_ndarray: NDArrayObject<'ctx>,
    ) {
        assert_eq!(self.ndims, src_ndarray.ndims);
        let src_shape = src_ndarray.instance.get(generator, ctx, |f| f.shape);
        self.copy_shape_from_array(generator, ctx, src_shape);
    }
    /// Copy strides dimensions from an array.
    pub fn copy_strides_from_array<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        strides: Instance<'ctx, Ptr<Int<SizeT>>>,
    ) {
        let num_items = self.ndims_llvm(generator, ctx.ctx).value;
        self.instance
            .get(generator, ctx, |f| f.strides)
            .copy_from(generator, ctx, strides, num_items);
    }
    /// Copy strides dimensions from an ndarray.
    /// Panics if `ndims` mismatches.
    pub fn copy_strides_from_ndarray<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        src_ndarray: NDArrayObject<'ctx>,
    ) {
        assert_eq!(self.ndims, src_ndarray.ndims);
        let src_strides = src_ndarray.instance.get(generator, ctx, |f| f.strides);
        self.copy_strides_from_array(generator, ctx, src_strides);
    }
    /// Get the `np.size()` of this ndarray.
    pub fn size<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> Instance<'ctx, Int<SizeT>> {
        call_nac3_ndarray_size(generator, ctx, self.instance)
    }
    /// Get the `ndarray.nbytes` of this ndarray.
    pub fn nbytes<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> Instance<'ctx, Int<SizeT>> {
        call_nac3_ndarray_nbytes(generator, ctx, self.instance)
    }
    /// Get the `len()` of this ndarray.
    pub fn len<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> Instance<'ctx, Int<SizeT>> {
        call_nac3_ndarray_len(generator, ctx, self.instance)
    }
    /// Check if this ndarray is C-contiguous.
    ///
    /// See NumPy's `flags["C_CONTIGUOUS"]`: <https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flags.html#numpy.ndarray.flags>
    pub fn is_c_contiguous<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> Instance<'ctx, Int<Bool>> {
        call_nac3_ndarray_is_c_contiguous(generator, ctx, self.instance)
    }
    /// Get the pointer to the n-th (0-based) element.
    ///
    /// The returned pointer has the element type of the LLVM type of this ndarray's `dtype`.
    pub fn get_nth_pelement<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        nth: Instance<'ctx, Int<SizeT>>,
    ) -> PointerValue<'ctx> {
        let elem_ty = ctx.get_llvm_type(generator, self.dtype);
        let p = call_nac3_ndarray_get_nth_pelement(generator, ctx, self.instance, nth);
        ctx.builder
            .build_pointer_cast(p.value, elem_ty.ptr_type(AddressSpace::default()), "")
            .unwrap()
    }
    /// Get the n-th (0-based) scalar.
    pub fn get_nth_scalar<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        nth: Instance<'ctx, Int<SizeT>>,
    ) -> AnyObject<'ctx> {
        let ptr = self.get_nth_pelement(generator, ctx, nth);
        let value = ctx.builder.build_load(ptr, "").unwrap();
        AnyObject { ty: self.dtype, value }
    }
    /// Get the pointer to the element indexed by `indices`.
    ///
    /// The returned pointer has the element type of the LLVM type of this ndarray's `dtype`.
    pub fn get_pelement_by_indices<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        indices: Instance<'ctx, Ptr<Int<SizeT>>>,
    ) -> PointerValue<'ctx> {
        let elem_ty = ctx.get_llvm_type(generator, self.dtype);
        let p = call_nac3_ndarray_get_pelement_by_indices(generator, ctx, self.instance, indices);
        ctx.builder
            .build_pointer_cast(p.value, elem_ty.ptr_type(AddressSpace::default()), "")
            .unwrap()
    }
    /// Get the scalar indexed by `indices`.
    pub fn get_scalar_by_indices<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        indices: Instance<'ctx, Ptr<Int<SizeT>>>,
    ) -> AnyObject<'ctx> {
        let ptr = self.get_pelement_by_indices(generator, ctx, indices);
        let value = ctx.builder.build_load(ptr, "").unwrap();
        AnyObject { ty: self.dtype, value }
    }
    /// Call [`call_nac3_ndarray_set_strides_by_shape`] on this ndarray to update `strides`.
    ///
    /// Update the ndarray's strides to make the ndarray contiguous.
    pub fn set_strides_contiguous<G: CodeGenerator + ?Sized>(
        self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) {
        call_nac3_ndarray_set_strides_by_shape(generator, ctx, self.instance);
    }
    /// Clone/Copy this ndarray - Allocate a new ndarray with the same shape as this ndarray and copy the contents over.
    ///
    /// The new ndarray will own its data and will be C-contiguous.
    #[must_use]
    pub fn make_copy<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> Self {
        let clone = NDArrayObject::alloca(generator, ctx, self.dtype, self.ndims);
        let shape = self.instance.gep(ctx, |f| f.shape).load(generator, ctx);
        clone.copy_shape_from_array(generator, ctx, shape);
        clone.create_data(generator, ctx);
        clone.copy_data_from(generator, ctx, *self);
        clone
    }
    /// Copy data from another ndarray.
    ///
    /// This ndarray and `src` is that their `np.size()` should be the same. Their shapes
    /// do not matter. The copying order is determined by how their flattened views look.
    ///
    /// Panics if the `dtype`s of ndarrays are different.
    pub fn copy_data_from<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        src: NDArrayObject<'ctx>,
    ) {
        assert!(ctx.unifier.unioned(self.dtype, src.dtype), "self and src dtype should match");
        call_nac3_ndarray_copy_data(generator, ctx, src.instance, self.instance);
    }
    /// Returns true if this ndarray is unsized - `ndims == 0` and only contains a scalar.
    #[must_use]
    pub fn is_unsized(&self) -> bool {
        self.ndims == 0
    }
    /// If this ndarray is unsized, return its sole value as an [`AnyObject`].
    /// Otherwise, do nothing and return the ndarray itself.
    pub fn split_unsized<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> ScalarOrNDArray<'ctx> {
        if self.is_unsized() {
            // NOTE: `np.size(self) == 0` here is never possible.
            let zero = Int(SizeT).const_0(generator, ctx.ctx);
            let value = self.get_nth_scalar(generator, ctx, zero).value;
            ScalarOrNDArray::Scalar(AnyObject { ty: self.dtype, value })
        } else {
            ScalarOrNDArray::NDArray(*self)
        }
    }
    /// Fill the ndarray with a scalar.
    ///
    /// `fill_value` must have the same LLVM type as the `dtype` of this ndarray.
    pub fn fill<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        value: BasicValueEnum<'ctx>,
    ) {
        // TODO: It is possible to optimize this by exploiting contiguous strides with memset.
        // Probably best to implement in IRRT.
        self.foreach(generator, ctx, |generator, ctx, _hooks, nditer| {
            let p = nditer.get_pointer(generator, ctx);
            ctx.builder.build_store(p, value).unwrap();
            Ok(())
        })
        .unwrap();
    }
    /// Create the shape tuple of this ndarray like `np.shape(<ndarray>)`.
    ///
    /// The returned integers in the tuple are in int32.
    pub fn make_shape_tuple<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> TupleObject<'ctx> {
        // TODO: Return a tuple of SizeT
        let mut objects = Vec::with_capacity(self.ndims as usize);
        for i in 0..self.ndims {
            let dim = self
                .instance
                .get(generator, ctx, |f| f.shape)
                .get_index_const(generator, ctx, i64::try_from(i).unwrap())
                .truncate_or_bit_cast(generator, ctx, Int32);
            objects.push(AnyObject {
                ty: ctx.primitives.int32,
                value: dim.value.as_basic_value_enum(),
            });
        }
        TupleObject::from_objects(generator, ctx, objects)
    }
    /// Create the strides tuple of this ndarray like `<ndarray>.strides`.
    ///
    /// The returned integers in the tuple are in int32.
    pub fn make_strides_tuple<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> TupleObject<'ctx> {
        // TODO: Return a tuple of SizeT.
        let mut objects = Vec::with_capacity(self.ndims as usize);
        for i in 0..self.ndims {
            let dim = self
                .instance
                .get(generator, ctx, |f| f.strides)
                .get_index_const(generator, ctx, i64::try_from(i).unwrap())
                .truncate_or_bit_cast(generator, ctx, Int32);
            objects.push(AnyObject {
                ty: ctx.primitives.int32,
                value: dim.value.as_basic_value_enum(),
            });
        }
        TupleObject::from_objects(generator, ctx, objects)
    }
    /// Create an unsized ndarray to contain `object`.
    pub fn make_unsized<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        object: AnyObject<'ctx>,
    ) -> NDArrayObject<'ctx> {
        // We have to put the value on the stack to get a data pointer.
        let data = ctx.builder.build_alloca(object.value.get_type(), "make_unsized").unwrap();
        ctx.builder.build_store(data, object.value).unwrap();
        let data = Ptr(Int(Byte)).pointer_cast(generator, ctx, data);
        let ndarray = NDArrayObject::alloca(generator, ctx, object.ty, 0);
        ndarray.instance.set(ctx, |f| f.data, data);
        ndarray
    }
 }
 /// A convenience enum for implementing functions that acts on scalars or ndarrays or both.
 #[derive(Debug, Clone, Copy)]
 pub enum ScalarOrNDArray<'ctx> {
    Scalar(AnyObject<'ctx>),
    NDArray(NDArrayObject<'ctx>),
 }
 impl<'ctx> TryFrom<&ScalarOrNDArray<'ctx>> for AnyObject<'ctx> {
    type Error = ();
    fn try_from(value: &ScalarOrNDArray<'ctx>) -> Result<Self, Self::Error> {
        match value {
            ScalarOrNDArray::Scalar(scalar) => Ok(*scalar),
            ScalarOrNDArray::NDArray(_ndarray) => Err(()),
        }
    }
 }
 impl<'ctx> TryFrom<&ScalarOrNDArray<'ctx>> for NDArrayObject<'ctx> {
    type Error = ();
    fn try_from(value: &ScalarOrNDArray<'ctx>) -> Result<Self, Self::Error> {
        match value {
            ScalarOrNDArray::Scalar(_scalar) => Err(()),
            ScalarOrNDArray::NDArray(ndarray) => Ok(*ndarray),
        }
    }
 }
 impl<'ctx> ScalarOrNDArray<'ctx> {
    /// Split on `object` either into a scalar or an ndarray.
    ///
    /// If `object` is an ndarray, [`ScalarOrNDArray::NDArray`].
    ///
    /// For everything else, it is wrapped with [`ScalarOrNDArray::Scalar`].
    pub fn split_object<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        object: AnyObject<'ctx>,
    ) -> ScalarOrNDArray<'ctx> {
        match &*ctx.unifier.get_ty(object.ty) {
            TypeEnum::TObj { obj_id, .. }
                if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
            {
                let ndarray = NDArrayObject::from_object(generator, ctx, object);
                ScalarOrNDArray::NDArray(ndarray)
            }
            _ => ScalarOrNDArray::Scalar(object),
        }
    }
    /// Get the underlying [`BasicValueEnum<'ctx>`] of this [`ScalarOrNDArray`].
    #[must_use]
    pub fn to_basic_value_enum(self) -> BasicValueEnum<'ctx> {
        match self {
            ScalarOrNDArray::Scalar(scalar) => scalar.value,
            ScalarOrNDArray::NDArray(ndarray) => ndarray.instance.value.as_basic_value_enum(),
        }
    }
    /// Convert this [`ScalarOrNDArray`] to an ndarray - behaves like `np.asarray`.
    /// - If this is an ndarray, the ndarray is returned.
    /// - If this is a scalar, this function returns new ndarray created with [`NDArrayObject::make_unsized`].
    pub fn to_ndarray<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> NDArrayObject<'ctx> {
        match self {
            ScalarOrNDArray::NDArray(ndarray) => *ndarray,
            ScalarOrNDArray::Scalar(scalar) => NDArrayObject::make_unsized(generator, ctx, *scalar),
        }
    }
    /// Get the dtype of the ndarray created if this were called with [`ScalarOrNDArray::to_ndarray`].
    #[must_use]
    pub fn get_dtype(&self) -> Type {
        match self {
            ScalarOrNDArray::NDArray(ndarray) => ndarray.dtype,
            ScalarOrNDArray::Scalar(scalar) => scalar.ty,
        }
    }
 }
--- a/nac3core/src/codegen/object/ndarray/nditer.rs
+++ b/nac3core/src/codegen/object/ndarray/nditer.rs
@ -1,179 +0,0 @@
 use inkwell::{types::BasicType, values::PointerValue, AddressSpace};
 use crate::codegen::{
    irrt::{call_nac3_nditer_has_element, call_nac3_nditer_initialize, call_nac3_nditer_next},
    model::*,
    object::any::AnyObject,
    stmt::{gen_for_callback, BreakContinueHooks},
    CodeGenContext, CodeGenerator,
 };
 use super::NDArrayObject;
 /// Fields of [`NDIter`]
 pub struct NDIterFields<'ctx, F: FieldTraversal<'ctx>> {
    pub ndims: F::Output<Int<SizeT>>,
    pub shape: F::Output<Ptr<Int<SizeT>>>,
    pub strides: F::Output<Ptr<Int<SizeT>>>,
    pub indices: F::Output<Ptr<Int<SizeT>>>,
    pub nth: F::Output<Int<SizeT>>,
    pub element: F::Output<Ptr<Int<Byte>>>,
    pub size: F::Output<Int<SizeT>>,
 }
 /// An IRRT helper structure used to iterate through an ndarray.
 #[derive(Debug, Clone, Copy, Default)]
 pub struct NDIter;
 impl<'ctx> StructKind<'ctx> for NDIter {
    type Fields<F: FieldTraversal<'ctx>> = NDIterFields<'ctx, F>;
    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
        Self::Fields {
            ndims: traversal.add_auto("ndims"),
            shape: traversal.add_auto("shape"),
            strides: traversal.add_auto("strides"),
            indices: traversal.add_auto("indices"),
            nth: traversal.add_auto("nth"),
            element: traversal.add_auto("element"),
            size: traversal.add_auto("size"),
        }
    }
 }
 /// A helper structure with a convenient interface to interact with [`NDIter`].
 #[derive(Debug, Clone)]
 pub struct NDIterHandle<'ctx> {
    instance: Instance<'ctx, Ptr<Struct<NDIter>>>,
    /// The ndarray this [`NDIter`] to iterating over.
    ndarray: NDArrayObject<'ctx>,
    /// The current indices of [`NDIter`].
    indices: Instance<'ctx, Ptr<Int<SizeT>>>,
 }
 impl<'ctx> NDIterHandle<'ctx> {
    /// Allocate an [`NDIter`] that iterates through an ndarray.
    pub fn new<G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        ndarray: NDArrayObject<'ctx>,
    ) -> Self {
        let nditer = Struct(NDIter).alloca(generator, ctx);
        let ndims = ndarray.ndims_llvm(generator, ctx.ctx);
        // The caller has the responsibility to allocate 'indices' for `NDIter`.
        let indices = Int(SizeT).array_alloca(generator, ctx, ndims.value);
        call_nac3_nditer_initialize(generator, ctx, nditer, ndarray.instance, indices);
        NDIterHandle { ndarray, instance: nditer, indices }
    }
    /// Is the current iteration valid?
    ///
    /// If true, then `element`, `indices` and `nth` contain details about the current element.
    ///
    /// If `ndarray` is unsized, this returns true only for the first iteration.
    /// If `ndarray` is 0-sized, this always returns false.
    #[must_use]
    pub fn has_element<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> Instance<'ctx, Int<Bool>> {
        call_nac3_nditer_has_element(generator, ctx, self.instance)
    }
    /// Go to the next element. If `has_element()` is false, then this has undefined behavior.
    ///
    /// If `ndarray` is unsized, this can only be called once.
    /// If `ndarray` is 0-sized, this can never be called.
    pub fn next<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) {
        call_nac3_nditer_next(generator, ctx, self.instance);
    }
    /// Get pointer to the current element.
    #[must_use]
    pub fn get_pointer<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> PointerValue<'ctx> {
        let elem_ty = ctx.get_llvm_type(generator, self.ndarray.dtype);
        let p = self.instance.get(generator, ctx, |f| f.element);
        ctx.builder
            .build_pointer_cast(p.value, elem_ty.ptr_type(AddressSpace::default()), "element")
            .unwrap()
    }
    /// Get the value of the current element.
    #[must_use]
    pub fn get_scalar<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> AnyObject<'ctx> {
        let p = self.get_pointer(generator, ctx);
        let value = ctx.builder.build_load(p, "value").unwrap();
        AnyObject { ty: self.ndarray.dtype, value }
    }
    /// Get the index of the current element if this ndarray were a flat ndarray.
    #[must_use]
    pub fn get_index<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> Instance<'ctx, Int<SizeT>> {
        self.instance.get(generator, ctx, |f| f.nth)
    }
    /// Get the indices of the current element.
    #[must_use]
    pub fn get_indices(&self) -> Instance<'ctx, Ptr<Int<SizeT>>> {
        self.indices
    }
 }
 impl<'ctx> NDArrayObject<'ctx> {
    /// Iterate through every element in the ndarray.
    ///
    /// `body` has access to [`BreakContinueHooks`] to short-circuit and [`NDIterHandle`] to
    /// get properties of the current iteration (e.g., the current element, indices, etc.)
    pub fn foreach<'a, G, F>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, 'a>,
        body: F,
    ) -> Result<(), String>
    where
        G: CodeGenerator + ?Sized,
        F: FnOnce(
            &mut G,
            &mut CodeGenContext<'ctx, 'a>,
            BreakContinueHooks<'ctx>,
            NDIterHandle<'ctx>,
        ) -> Result<(), String>,
    {
        gen_for_callback(
            generator,
            ctx,
            Some("ndarray_foreach"),
            |generator, ctx| Ok(NDIterHandle::new(generator, ctx, *self)),
            |generator, ctx, nditer| Ok(nditer.has_element(generator, ctx).value),
            |generator, ctx, hooks, nditer| body(generator, ctx, hooks, nditer),
            |generator, ctx, nditer| {
                nditer.next(generator, ctx);
                Ok(())
            },
        )
    }
 }
--- a/nac3core/src/codegen/object/ndarray/shape_util.rs
+++ b/nac3core/src/codegen/object/ndarray/shape_util.rs
@ -1,105 +0,0 @@
 use util::gen_for_model;
 use crate::{
    codegen::{
        model::*,
        object::{any::AnyObject, list::ListObject, tuple::TupleObject},
        CodeGenContext, CodeGenerator,
    },
    typecheck::typedef::TypeEnum,
 };
 /// Parse a NumPy-like "int sequence" input and return the int sequence as an array and its length.
 ///
 /// * `sequence` - The `sequence` parameter.
 /// * `sequence_ty` - The typechecker type of `sequence`
 ///
 /// The `sequence` argument type may only be one of the following:
 ///   1. A list of `int32`;   e.g., `np.empty([600, 800, 3])`
 ///   2. A tuple of `int32`;  e.g., `np.empty((600, 800, 3))`
 ///   3. A scalar `int32`;    e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
 ///
 /// All `int32` values will be sign-extended to `SizeT`.
 pub fn parse_numpy_int_sequence<'ctx, G: CodeGenerator + ?Sized>(
    generator: &mut G,
    ctx: &mut CodeGenContext<'ctx, '_>,
    input_sequence: AnyObject<'ctx>,
 ) -> (Instance<'ctx, Int<SizeT>>, Instance<'ctx, Ptr<Int<SizeT>>>) {
    let zero = Int(SizeT).const_0(generator, ctx.ctx);
    let one = Int(SizeT).const_1(generator, ctx.ctx);
    // The result `list` to return.
    match &*ctx.unifier.get_ty(input_sequence.ty) {
        TypeEnum::TObj { obj_id, .. }
            if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
        {
            // 1. A list of `int32`; e.g., `np.empty([600, 800, 3])`
            // Check `input_sequence`
            let input_sequence = ListObject::from_object(generator, ctx, input_sequence);
            let len = input_sequence.instance.get(generator, ctx, |f| f.len);
            let result = Int(SizeT).array_alloca(generator, ctx, len.value);
            // Load all the `int32`s from the input_sequence, cast them to `SizeT`, and store them into `result`
            gen_for_model(generator, ctx, zero, len, one, |generator, ctx, _hooks, i| {
                // Load the i-th int32 in the input sequence
                let int = input_sequence
                    .instance
                    .get(generator, ctx, |f| f.items)
                    .get_index(generator, ctx, i.value)
                    .value
                    .into_int_value();
                // Cast to SizeT
                let int = Int(SizeT).s_extend_or_bit_cast(generator, ctx, int);
                // Store
                result.set_index(ctx, i.value, int);
                Ok(())
            })
            .unwrap();
            (len, result)
        }
        TypeEnum::TTuple { .. } => {
            // 2. A tuple of ints; e.g., `np.empty((600, 800, 3))`
            let input_sequence = TupleObject::from_object(ctx, input_sequence);
            let len = input_sequence.len(generator, ctx);
            let result = Int(SizeT).array_alloca(generator, ctx, len.value);
            for i in 0..input_sequence.num_elements() {
                // Get the i-th element off of the tuple and load it into `result`.
                let int = input_sequence.index(ctx, i).value.into_int_value();
                let int = Int(SizeT).s_extend_or_bit_cast(generator, ctx, int);
                result.set_index_const(ctx, i64::try_from(i).unwrap(), int);
            }
            (len, result)
        }
        TypeEnum::TObj { obj_id, .. }
            if *obj_id == ctx.primitives.int32.obj_id(&ctx.unifier).unwrap() =>
        {
            // 3. A scalar int; e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
            let input_int = input_sequence.value.into_int_value();
            let len = Int(SizeT).const_1(generator, ctx.ctx);
            let result = Int(SizeT).array_alloca(generator, ctx, len.value);
            let int = Int(SizeT).s_extend_or_bit_cast(generator, ctx, input_int);
            // Storing into result[0]
            result.store(ctx, int);
            (len, result)
        }
        _ => panic!(
            "encountered unknown sequence type: {}",
            ctx.unifier.stringify(input_sequence.ty)
        ),
    }
 }
--- a/nac3core/src/codegen/object/ndarray/view.rs
+++ b/nac3core/src/codegen/object/ndarray/view.rs
@ -1,119 +0,0 @@
 use crate::codegen::{
    irrt::{call_nac3_ndarray_reshape_resolve_and_check_new_shape, call_nac3_ndarray_transpose},
    model::*,
    CodeGenContext, CodeGenerator,
 };
 use super::{indexing::RustNDIndex, NDArrayObject};
 impl<'ctx> NDArrayObject<'ctx> {
    /// Make sure the ndarray is at least `ndmin`-dimensional.
    ///
    /// If this ndarray's `ndims` is less than `ndmin`, a view is created on this with 1s prepended to the shape.
    /// If this ndarray's `ndims` is not less than `ndmin`, this function does nothing and return this ndarray.
    #[must_use]
    pub fn atleast_nd<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        ndmin: u64,
    ) -> Self {
        if self.ndims < ndmin {
            // Extend the dimensions with np.newaxis.
            let mut indices = vec![];
            for _ in self.ndims..ndmin {
                indices.push(RustNDIndex::NewAxis);
            }
            indices.push(RustNDIndex::Ellipsis);
            self.index(generator, ctx, &indices)
        } else {
            *self
        }
    }
    /// Create a reshaped view on this ndarray like `np.reshape()`.
    ///
    /// If there is a `-1` in `new_shape`, it will be resolved; `new_shape` would **NOT** be modified as a result.
    ///
    /// If reshape without copying is impossible, this function will allocate a new ndarray and copy contents.
    ///
    /// * `new_ndims` - The number of dimensions of `new_shape` as a [`Type`].
    /// * `new_shape` - The target shape to do `np.reshape()`.
    #[must_use]
    pub fn reshape_or_copy<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        new_ndims: u64,
        new_shape: Instance<'ctx, Ptr<Int<SizeT>>>,
    ) -> Self {
        // TODO: The current criterion for whether to do a full copy or not is by checking `is_c_contiguous`,
        // but this is not optimal - there are cases when the ndarray is not contiguous but could be reshaped
        // without copying data. Look into how numpy does it.
        let current_bb = ctx.builder.get_insert_block().unwrap();
        let then_bb = ctx.ctx.insert_basic_block_after(current_bb, "then_bb");
        let else_bb = ctx.ctx.insert_basic_block_after(then_bb, "else_bb");
        let end_bb = ctx.ctx.insert_basic_block_after(else_bb, "end_bb");
        let dst_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, new_ndims);
        dst_ndarray.copy_shape_from_array(generator, ctx, new_shape);
        // Reolsve negative indices
        let size = self.size(generator, ctx);
        let dst_ndims = dst_ndarray.ndims_llvm(generator, ctx.ctx);
        let dst_shape = dst_ndarray.instance.get(generator, ctx, |f| f.shape);
        call_nac3_ndarray_reshape_resolve_and_check_new_shape(
            generator, ctx, size, dst_ndims, dst_shape,
        );
        let is_c_contiguous = self.is_c_contiguous(generator, ctx);
        ctx.builder.build_conditional_branch(is_c_contiguous.value, then_bb, else_bb).unwrap();
        // Inserting into then_bb: reshape is possible without copying
        ctx.builder.position_at_end(then_bb);
        dst_ndarray.set_strides_contiguous(generator, ctx);
        dst_ndarray.instance.set(ctx, |f| f.data, self.instance.get(generator, ctx, |f| f.data));
        ctx.builder.build_unconditional_branch(end_bb).unwrap();
        // Inserting into else_bb: reshape is impossible without copying
        ctx.builder.position_at_end(else_bb);
        dst_ndarray.create_data(generator, ctx);
        dst_ndarray.copy_data_from(generator, ctx, *self);
        ctx.builder.build_unconditional_branch(end_bb).unwrap();
        // Reposition for continuation
        ctx.builder.position_at_end(end_bb);
        dst_ndarray
    }
    /// Create a transposed view on this ndarray like `np.transpose(<ndarray>, <axes> = None)`.
    /// * `axes` - If specified, should be an array of the permutation (negative indices are **allowed**).
    #[must_use]
    pub fn transpose<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        axes: Option<Instance<'ctx, Ptr<Int<SizeT>>>>,
    ) -> Self {
        // Define models
        let transposed_ndarray = NDArrayObject::alloca(generator, ctx, self.dtype, self.ndims);
        let num_axes = self.ndims_llvm(generator, ctx.ctx);
        // `axes = nullptr` if `axes` is unspecified.
        let axes = axes.unwrap_or_else(|| Ptr(Int(SizeT)).nullptr(generator, ctx.ctx));
        call_nac3_ndarray_transpose(
            generator,
            ctx,
            self.instance,
            transposed_ndarray.instance,
            num_axes,
            axes,
        );
        transposed_ndarray
    }
 }
--- a/nac3core/src/codegen/object/tuple.rs
+++ b/nac3core/src/codegen/object/tuple.rs
@ -1,99 +0,0 @@
 use inkwell::values::StructValue;
 use itertools::Itertools;
 use crate::{
    codegen::{model::*, CodeGenContext, CodeGenerator},
    typecheck::typedef::{Type, TypeEnum},
 };
 use super::any::AnyObject;
 /// A NAC3 tuple object.
 ///
 /// NOTE: This struct has no copy trait.
 #[derive(Debug, Clone)]
 pub struct TupleObject<'ctx> {
    /// The type of the tuple.
    pub tys: Vec<Type>,
    /// The underlying LLVM struct value of this tuple.
    pub value: StructValue<'ctx>,
 }
 impl<'ctx> TupleObject<'ctx> {
    pub fn from_object(ctx: &mut CodeGenContext<'ctx, '_>, object: AnyObject<'ctx>) -> Self {
        // TODO: Keep `is_vararg_ctx` from TTuple?
        // Sanity check on object type.
        let TypeEnum::TTuple { ty: tys, .. } = &*ctx.unifier.get_ty(object.ty) else {
            panic!(
                "Expected type to be a TypeEnum::TTuple, got {}",
                ctx.unifier.stringify(object.ty)
            );
        };
        // Check number of fields
        let value = object.value.into_struct_value();
        let value_num_fields = value.get_type().count_fields() as usize;
        assert!(
            value_num_fields == tys.len(),
            "Tuple type has {} item(s), but the LLVM struct value has {} field(s)",
            tys.len(),
            value_num_fields
        );
        TupleObject { tys: tys.clone(), value }
    }
    /// Convenience function. Create a [`TupleObject`] from an iterator of objects.
    pub fn from_objects<I, G: CodeGenerator + ?Sized>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        objects: I,
    ) -> Self
    where
        I: IntoIterator<Item = AnyObject<'ctx>>,
    {
        let (values, tys): (Vec<_>, Vec<_>) =
            objects.into_iter().map(|object| (object.value, object.ty)).unzip();
        let llvm_tys = tys.iter().map(|ty| ctx.get_llvm_type(generator, *ty)).collect_vec();
        let llvm_tuple_ty = ctx.ctx.struct_type(&llvm_tys, false);
        let pllvm_tuple = ctx.builder.build_alloca(llvm_tuple_ty, "tuple").unwrap();
        for (i, val) in values.into_iter().enumerate() {
            let pval = ctx.builder.build_struct_gep(pllvm_tuple, i as u32, "value").unwrap();
            ctx.builder.build_store(pval, val).unwrap();
        }
        let value = ctx.builder.build_load(pllvm_tuple, "").unwrap().into_struct_value();
        TupleObject { tys, value }
    }
    #[must_use]
    pub fn num_elements(&self) -> usize {
        self.tys.len()
    }
    /// Get the `len()` of this tuple.
    #[must_use]
    pub fn len<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
    ) -> Instance<'ctx, Int<SizeT>> {
        Int(SizeT).const_int(generator, ctx.ctx, self.num_elements() as u64, false)
    }
    /// Get the `i`-th (0-based) object in this tuple.
    pub fn index(&self, ctx: &mut CodeGenContext<'ctx, '_>, i: usize) -> AnyObject<'ctx> {
        assert!(
            i < self.num_elements(),
            "Tuple object with length {} have index {i}",
            self.num_elements()
        );
        let value = ctx.builder.build_extract_value(self.value, i as u32, "tuple[{i}]").unwrap();
        let ty = self.tys[i];
        AnyObject { ty, value }
    }
 }
--- a/nac3core/src/codegen/object/utils/mod.rs
+++ b/nac3core/src/codegen/object/utils/mod.rs
@ -1 +0,0 @@
 pub mod slice;
--- a/nac3core/src/codegen/object/utils/slice.rs
+++ b/nac3core/src/codegen/object/utils/slice.rs
@ -1,125 +0,0 @@
 use crate::codegen::{model::*, CodeGenContext, CodeGenerator};
 /// Fields of [`Slice`]
 #[derive(Debug, Clone)]
 pub struct SliceFields<'ctx, F: FieldTraversal<'ctx>, N: IntKind<'ctx>> {
    pub start_defined: F::Output<Int<Bool>>,
    pub start: F::Output<Int<N>>,
    pub stop_defined: F::Output<Int<Bool>>,
    pub stop: F::Output<Int<N>>,
    pub step_defined: F::Output<Int<Bool>>,
    pub step: F::Output<Int<N>>,
 }
 /// An IRRT representation of an (unresolved) slice.
 #[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
 pub struct Slice<N>(pub N);
 impl<'ctx, N: IntKind<'ctx>> StructKind<'ctx> for Slice<N> {
    type Fields<F: FieldTraversal<'ctx>> = SliceFields<'ctx, F, N>;
    fn iter_fields<F: FieldTraversal<'ctx>>(&self, traversal: &mut F) -> Self::Fields<F> {
        Self::Fields {
            start_defined: traversal.add_auto("start_defined"),
            start: traversal.add("start", Int(self.0)),
            stop_defined: traversal.add_auto("stop_defined"),
            stop: traversal.add("stop", Int(self.0)),
            step_defined: traversal.add_auto("step_defined"),
            step: traversal.add("step", Int(self.0)),
        }
    }
 }
 /// A Rust structure that has [`Slice`] utilities and looks like a [`Slice`] but
 /// `start`, `stop` and `step` are held by LLVM registers only and possibly
 /// [`Option::None`] if unspecified.
 #[derive(Debug, Clone)]
 pub struct RustSlice<'ctx, N: IntKind<'ctx>> {
    // It is possible that `start`, `stop`, and `step` are all `None`.
    // We need to know the `int_kind` even when that is the case.
    pub int_kind: N,
    pub start: Option<Instance<'ctx, Int<N>>>,
    pub stop: Option<Instance<'ctx, Int<N>>>,
    pub step: Option<Instance<'ctx, Int<N>>>,
 }
 impl<'ctx, N: IntKind<'ctx>> RustSlice<'ctx, N> {
    /// Write the contents to an LLVM [`Slice`].
    pub fn write_to_slice<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &CodeGenContext<'ctx, '_>,
        dst_slice_ptr: Instance<'ctx, Ptr<Struct<Slice<N>>>>,
    ) {
        let false_ = Int(Bool).const_false(generator, ctx.ctx);
        let true_ = Int(Bool).const_true(generator, ctx.ctx);
        match self.start {
            Some(start) => {
                dst_slice_ptr.gep(ctx, |f| f.start_defined).store(ctx, true_);
                dst_slice_ptr.gep(ctx, |f| f.start).store(ctx, start);
            }
            None => dst_slice_ptr.gep(ctx, |f| f.start_defined).store(ctx, false_),
        }
        match self.stop {
            Some(stop) => {
                dst_slice_ptr.gep(ctx, |f| f.stop_defined).store(ctx, true_);
                dst_slice_ptr.gep(ctx, |f| f.stop).store(ctx, stop);
            }
            None => dst_slice_ptr.gep(ctx, |f| f.stop_defined).store(ctx, false_),
        }
        match self.step {
            Some(step) => {
                dst_slice_ptr.gep(ctx, |f| f.step_defined).store(ctx, true_);
                dst_slice_ptr.gep(ctx, |f| f.step).store(ctx, step);
            }
            None => dst_slice_ptr.gep(ctx, |f| f.step_defined).store(ctx, false_),
        }
    }
 }
 pub mod util {
    use nac3parser::ast::Expr;
    use crate::{
        codegen::{model::*, CodeGenContext, CodeGenerator},
        typecheck::typedef::Type,
    };
    use super::RustSlice;
    /// Generate LLVM IR for an [`ExprKind::Slice`] and convert it into a [`RustSlice`].
    #[allow(clippy::type_complexity)]
    pub fn gen_slice<'ctx, G: CodeGenerator>(
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        lower: &Option<Box<Expr<Option<Type>>>>,
        upper: &Option<Box<Expr<Option<Type>>>>,
        step: &Option<Box<Expr<Option<Type>>>>,
    ) -> Result<RustSlice<'ctx, Int32>, String> {
        let mut help = |value_expr: &Option<Box<Expr<Option<Type>>>>| -> Result<_, String> {
            Ok(match value_expr {
                None => None,
                Some(value_expr) => {
                    let value_expr = generator
                        .gen_expr(ctx, value_expr)?
                        .unwrap()
                        .to_basic_value_enum(ctx, generator, ctx.primitives.int32)?;
                    let value_expr =
                        Int(Int32).check_value(generator, ctx.ctx, value_expr).unwrap();
                    Some(value_expr)
                }
            })
        };
        let start = help(lower)?;
        let stop = help(upper)?;
        let step = help(step)?;
        Ok(RustSlice { int_kind: Int32, start, stop, step })
    }
 }
--- a/nac3core/src/codegen/stmt.rs
+++ b/nac3core/src/codegen/stmt.rs
@ -1,15 +1,22 @@
 use inkwell::{
    attributes::{Attribute, AttributeLoc},
    basic_block::BasicBlock,
    types::{BasicType, BasicTypeEnum},
    values::{BasicValue, BasicValueEnum, FunctionValue, IntValue, PointerValue},
    IntPredicate,
 };
 use itertools::{izip, Itertools};
 use nac3parser::ast::{
    Constant, ExcepthandlerKind, Expr, ExprKind, Location, Stmt, StmtKind, StrRef,
 };
 use super::{
    classes::{ArrayLikeIndexer, ArraySliceValue, ListValue, RangeValue},
    expr::{destructure_range, gen_binop_expr},
    gen_in_range_check,
    irrt::{handle_slice_indices, list_slice_assignment},
    macros::codegen_unreachable,
-    object::{
+    values::{ArrayLikeIndexer, ArraySliceValue, ListValue, RangeValue},
        any::AnyObject,
        ndarray::{
            indexing::util::gen_ndarray_subscript_ndindices, NDArrayObject, ScalarOrNDArray,
        },
    },
    CodeGenContext, CodeGenerator,
 };
 use crate::{
@ -20,17 +27,6 @@ use crate::{
        typedef::{iter_type_vars, FunSignature, Type, TypeEnum},
    },
 };
 use inkwell::{
    attributes::{Attribute, AttributeLoc},
    basic_block::BasicBlock,
    types::{BasicType, BasicTypeEnum},
    values::{BasicValue, BasicValueEnum, FunctionValue, IntValue, PointerValue},
    IntPredicate,
 };
 use itertools::{izip, Itertools};
 use nac3parser::ast::{
    Constant, ExcepthandlerKind, Expr, ExprKind, Location, Stmt, StmtKind, StrRef,
 };
 /// See [`CodeGenerator::gen_var_alloc`].
 pub fn gen_var<'ctx>(
@ -314,7 +310,7 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
                .unwrap()
                .to_basic_value_enum(ctx, generator, target_ty)?
                .into_pointer_value();
-            let target = ListValue::from_ptr_val(target, llvm_usize, None);
+            let target = ListValue::from_pointer_value(target, llvm_usize, None);
            if let ExprKind::Slice { .. } = &key.node {
                // Handle assigning to a slice
@ -335,7 +331,7 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
                let value =
                    value.to_basic_value_enum(ctx, generator, value_ty)?.into_pointer_value();
-                let value = ListValue::from_ptr_val(value, llvm_usize, None);
+                let value = ListValue::from_pointer_value(value, llvm_usize, None);
                let target_item_ty = ctx.get_llvm_type(generator, target_item_ty);
                let Some(src_ind) = handle_slice_indices(
@ -415,47 +411,7 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
            if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
        {
            // Handle NDArray item assignment
-            // Process target
+            todo!("ndarray subscript assignment is not yet implemented");
            let target = generator
                .gen_expr(ctx, target)?
                .unwrap()
                .to_basic_value_enum(ctx, generator, target_ty)?;
            let target = AnyObject { value: target, ty: target_ty };
            // Process key
            let key = gen_ndarray_subscript_ndindices(generator, ctx, key)?;
            // Process value
            let value = value.to_basic_value_enum(ctx, generator, value_ty)?;
            let value = AnyObject { value, ty: value_ty };
            /*
                Reference code:
                ```python
                target = target[key]
                value = np.asarray(value)
                shape = np.broadcast_shape((target, value))
                target = np.broadcast_to(target, shape)
                value = np.broadcast_to(value, shape)
                ...and finally copy 1-1 from value to target.
                ```
            */
            let target = NDArrayObject::from_object(generator, ctx, target);
            let target = target.index(generator, ctx, &key);
            let value =
                ScalarOrNDArray::split_object(generator, ctx, value).to_ndarray(generator, ctx);
            let broadcast_result = NDArrayObject::broadcast(generator, ctx, &[target, value]);
            let target = broadcast_result.ndarrays[0];
            let value = broadcast_result.ndarrays[1];
            target.copy_data_from(generator, ctx, value);
        }
        _ => {
            panic!("encountered unknown target type: {}", ctx.unifier.stringify(target_ty));
@ -507,7 +463,8 @@ pub fn gen_for<G: CodeGenerator>(
        TypeEnum::TObj { obj_id, .. }
            if *obj_id == ctx.primitives.range.obj_id(&ctx.unifier).unwrap() =>
        {
-            let iter_val = RangeValue::from_ptr_val(iter_val.into_pointer_value(), Some("range"));
+            let iter_val =
                RangeValue::from_pointer_value(iter_val.into_pointer_value(), Some("range"));
            // Internal variable for loop; Cannot be assigned
            let i = generator.gen_var_alloc(ctx, int32.into(), Some("for.i.addr"))?;
            // Variable declared in "target" expression of the loop; Can be reassigned *or* shadowed
@ -1872,6 +1829,37 @@ pub fn gen_stmt<G: CodeGenerator>(
                stmt.location,
            );
        }
        StmtKind::Global { names, .. } => {
            let registered_globals = ctx
                .top_level
                .definitions
                .read()
                .iter()
                .filter_map(|def| {
                    if let TopLevelDef::Variable { simple_name, ty, .. } = &*def.read() {
                        Some((*simple_name, *ty))
                    } else {
                        None
                    }
                })
                .collect_vec();
            for id in names {
                let Some((_, ty)) = registered_globals.iter().find(|(name, _)| name == id) else {
                    return Err(format!("{id} is not a global at {}", stmt.location));
                };
                let resolver = ctx.resolver.clone();
                let ptr = resolver
                    .get_symbol_value(*id, ctx, generator)
                    .map(|val| val.to_basic_value_enum(ctx, generator, *ty))
                    .transpose()?
                    .map(BasicValueEnum::into_pointer_value)
                    .unwrap();
                ctx.var_assignment.insert(*id, (ptr, None, 0));
            }
        }
        _ => unimplemented!(),
    };
    Ok(())
--- a/nac3core/src/codegen/test.rs
+++ b/nac3core/src/codegen/test.rs
@ -1,34 +1,37 @@
-use crate::{
+use std::{
-    codegen::{
+    collections::{HashMap, HashSet},
-        classes::{ListType, NDArrayType, ProxyType, RangeType},
+    sync::Arc,
        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, 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},
+    ast::{fold::Fold, FileName, StrRef},
    parser::parse_program,
 };
 use parking_lot::RwLock;
-use std::collections::{HashMap, HashSet};
+
-use std::sync::Arc;
+use super::{
    concrete_type::ConcreteTypeStore,
    types::{ListType, NDArrayType, ProxyType, RangeType},
    CodeGenContext, CodeGenLLVMOptions, CodeGenTargetMachineOptions, CodeGenTask, CodeGenerator,
    DefaultCodeGenerator, WithCall, WorkerRegistry,
 };
 use crate::{
    symbol_resolver::{SymbolResolver, ValueEnum},
    toplevel::{
        composer::{ComposerConfig, TopLevelComposer},
        DefinitionId, FunInstance, TopLevelContext, TopLevelDef,
    },
    typecheck::{
        type_inferencer::{FunctionData, IdentifierInfo, Inferencer, PrimitiveStore},
        typedef::{FunSignature, FuncArg, Type, TypeEnum, Unifier, VarMap},
    },
 };
 struct Resolver {
    id_to_type: HashMap<StrRef, Type>,
@ -64,6 +67,7 @@ impl SymbolResolver for Resolver {
        &self,
        _: StrRef,
        _: &mut CodeGenContext<'ctx, '_>,
        _: &mut dyn CodeGenerator,
    ) -> Option<ValueEnum<'ctx>> {
        unimplemented!()
    }
@ -138,7 +142,8 @@ fn test_primitives() {
    };
    let mut virtual_checks = Vec::new();
    let mut calls = HashMap::new();
-    let mut identifiers: HashSet<_> = ["a".into(), "b".into()].into();
+    let mut identifiers: HashMap<_, _> =
        ["a".into(), "b".into()].map(|id| (id, IdentifierInfo::default())).into();
    let mut inferencer = Inferencer {
        top_level: &top_level,
        function_data: &mut function_data,
@ -317,7 +322,8 @@ fn test_simple_call() {
    };
    let mut virtual_checks = Vec::new();
    let mut calls = HashMap::new();
-    let mut identifiers: HashSet<_> = ["a".into(), "foo".into()].into();
+    let mut identifiers: HashMap<_, _> =
        ["a".into(), "foo".into()].map(|id| (id, IdentifierInfo::default())).into();
    let mut inferencer = Inferencer {
        top_level: &top_level,
        function_data: &mut function_data,
@ -446,7 +452,7 @@ fn test_classes_list_type_new() {
    let llvm_usize = generator.get_size_type(&ctx);
    let llvm_list = ListType::new(&generator, &ctx, llvm_i32.into());
-    assert!(ListType::is_type(llvm_list.as_base_type(), llvm_usize).is_ok());
+    assert!(ListType::is_representable(llvm_list.as_base_type(), llvm_usize).is_ok());
 }
 #[test]
@ -454,7 +460,7 @@ fn test_classes_range_type_new() {
    let ctx = inkwell::context::Context::create();
    let llvm_range = RangeType::new(&ctx);
-    assert!(RangeType::is_type(llvm_range.as_base_type()).is_ok());
+    assert!(RangeType::is_representable(llvm_range.as_base_type()).is_ok());
 }
 #[test]
@ -466,5 +472,5 @@ fn test_classes_ndarray_type_new() {
    let llvm_usize = generator.get_size_type(&ctx);
    let llvm_ndarray = NDArrayType::new(&generator, &ctx, llvm_i32.into());
-    assert!(NDArrayType::is_type(llvm_ndarray.as_base_type(), llvm_usize).is_ok());
+    assert!(NDArrayType::is_representable(llvm_ndarray.as_base_type(), llvm_usize).is_ok());
 }
--- a/nac3core/src/codegen/types/list.rs
+++ b/nac3core/src/codegen/types/list.rs
@ -0,0 +1,192 @@
 use inkwell::{
    context::Context,
    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
    values::IntValue,
    AddressSpace,
 };
 use super::ProxyType;
 use crate::codegen::{
    values::{ArraySliceValue, ListValue, ProxyValue},
    CodeGenContext, CodeGenerator,
 };
 /// Proxy type for a `list` type in LLVM.
 #[derive(Debug, PartialEq, Eq, Clone, Copy)]
 pub struct ListType<'ctx> {
    ty: PointerType<'ctx>,
    llvm_usize: IntType<'ctx>,
 }
 impl<'ctx> ListType<'ctx> {
    /// Checks whether `llvm_ty` represents a `list` type, returning [Err] if it does not.
    pub fn is_representable(
        llvm_ty: PointerType<'ctx>,
        llvm_usize: IntType<'ctx>,
    ) -> Result<(), String> {
        let llvm_list_ty = llvm_ty.get_element_type();
        let AnyTypeEnum::StructType(llvm_list_ty) = llvm_list_ty else {
            return Err(format!("Expected struct type for `list` type, got {llvm_list_ty}"));
        };
        if llvm_list_ty.count_fields() != 2 {
            return Err(format!(
                "Expected 2 fields in `list`, got {}",
                llvm_list_ty.count_fields()
            ));
        }
        let list_size_ty = llvm_list_ty.get_field_type_at_index(0).unwrap();
        let Ok(_) = PointerType::try_from(list_size_ty) else {
            return Err(format!("Expected pointer type for `list.0`, got {list_size_ty}"));
        };
        let list_data_ty = llvm_list_ty.get_field_type_at_index(1).unwrap();
        let Ok(list_data_ty) = IntType::try_from(list_data_ty) else {
            return Err(format!("Expected int type for `list.1`, got {list_data_ty}"));
        };
        if list_data_ty.get_bit_width() != llvm_usize.get_bit_width() {
            return Err(format!(
                "Expected {}-bit int type for `list.1`, got {}-bit int",
                llvm_usize.get_bit_width(),
                list_data_ty.get_bit_width()
            ));
        }
        Ok(())
    }
    /// Creates an LLVM type corresponding to the expected structure of a `List`.
    #[must_use]
    fn llvm_type(
        ctx: &'ctx Context,
        element_type: BasicTypeEnum<'ctx>,
        llvm_usize: IntType<'ctx>,
    ) -> PointerType<'ctx> {
        // struct List { data: T*, size: size_t }
        let field_tys = [element_type.ptr_type(AddressSpace::default()).into(), llvm_usize.into()];
        ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
    }
    /// Creates an instance of [`ListType`].
    #[must_use]
    pub fn new<G: CodeGenerator + ?Sized>(
        generator: &G,
        ctx: &'ctx Context,
        element_type: BasicTypeEnum<'ctx>,
    ) -> Self {
        let llvm_usize = generator.get_size_type(ctx);
        let llvm_list = Self::llvm_type(ctx, element_type, llvm_usize);
        ListType::from_type(llvm_list, llvm_usize)
    }
    /// Creates an [`ListType`] from a [`PointerType`].
    #[must_use]
    pub fn from_type(ptr_ty: PointerType<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
        debug_assert!(Self::is_representable(ptr_ty, llvm_usize).is_ok());
        ListType { ty: ptr_ty, llvm_usize }
    }
    /// Returns the type of the `size` field of this `list` type.
    #[must_use]
    pub fn size_type(&self) -> IntType<'ctx> {
        self.as_base_type()
            .get_element_type()
            .into_struct_type()
            .get_field_type_at_index(1)
            .map(BasicTypeEnum::into_int_type)
            .unwrap()
    }
    /// Returns the element type of this `list` type.
    #[must_use]
    pub fn element_type(&self) -> AnyTypeEnum<'ctx> {
        self.as_base_type()
            .get_element_type()
            .into_struct_type()
            .get_field_type_at_index(0)
            .map(BasicTypeEnum::into_pointer_type)
            .map(PointerType::get_element_type)
            .unwrap()
    }
 }
 impl<'ctx> ProxyType<'ctx> for ListType<'ctx> {
    type Base = PointerType<'ctx>;
    type Value = ListValue<'ctx>;
    fn is_type<G: CodeGenerator + ?Sized>(
        generator: &G,
        ctx: &'ctx Context,
        llvm_ty: impl BasicType<'ctx>,
    ) -> Result<(), String> {
        if let BasicTypeEnum::PointerType(ty) = llvm_ty.as_basic_type_enum() {
            <Self as ProxyType<'ctx>>::is_representable(generator, ctx, ty)
        } else {
            Err(format!("Expected pointer type, got {llvm_ty:?}"))
        }
    }
    fn is_representable<G: CodeGenerator + ?Sized>(
        generator: &G,
        ctx: &'ctx Context,
        llvm_ty: Self::Base,
    ) -> Result<(), String> {
        Self::is_representable(llvm_ty, generator.get_size_type(ctx))
    }
    fn new_value<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        name: Option<&'ctx str>,
    ) -> Self::Value {
        self.map_value(
            generator
                .gen_var_alloc(
                    ctx,
                    self.as_base_type().get_element_type().into_struct_type().into(),
                    name,
                )
                .unwrap(),
            name,
        )
    }
    fn new_array_value<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        size: IntValue<'ctx>,
        name: Option<&'ctx str>,
    ) -> ArraySliceValue<'ctx> {
        generator
            .gen_array_var_alloc(
                ctx,
                self.as_base_type().get_element_type().into_struct_type().into(),
                size,
                name,
            )
            .unwrap()
    }
    fn map_value(
        &self,
        value: <Self::Value as ProxyValue<'ctx>>::Base,
        name: Option<&'ctx str>,
    ) -> Self::Value {
        Self::Value::from_pointer_value(value, self.llvm_usize, name)
    }
    fn as_base_type(&self) -> Self::Base {
        self.ty
    }
 }
 impl<'ctx> From<ListType<'ctx>> for PointerType<'ctx> {
    fn from(value: ListType<'ctx>) -> Self {
        value.as_base_type()
    }
 }
--- a/nac3core/src/codegen/types/mod.rs
+++ b/nac3core/src/codegen/types/mod.rs
@ -0,0 +1,64 @@
 use inkwell::{context::Context, types::BasicType, values::IntValue};
 use super::{
    values::{ArraySliceValue, ProxyValue},
    {CodeGenContext, CodeGenerator},
 };
 pub use list::*;
 pub use ndarray::*;
 pub use range::*;
 mod list;
 mod ndarray;
 mod range;
 pub mod structure;
 /// A LLVM type that is used to represent a corresponding type in NAC3.
 pub trait ProxyType<'ctx>: Into<Self::Base> {
    /// The LLVM type of which values of this type possess. This is usually a
    /// [LLVM pointer type][PointerType] for any non-primitive types.
    type Base: BasicType<'ctx>;
    /// The type of values represented by this type.
    type Value: ProxyValue<'ctx, Type = Self>;
    fn is_type<G: CodeGenerator + ?Sized>(
        generator: &G,
        ctx: &'ctx Context,
        llvm_ty: impl BasicType<'ctx>,
    ) -> Result<(), String>;
    /// Checks whether `llvm_ty` can be represented by this [`ProxyType`].
    fn is_representable<G: CodeGenerator + ?Sized>(
        generator: &G,
        ctx: &'ctx Context,
        llvm_ty: Self::Base,
    ) -> Result<(), String>;
    /// Creates a new value of this type.
    fn new_value<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        name: Option<&'ctx str>,
    ) -> Self::Value;
    /// Creates a new array value of this type.
    fn new_array_value<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        size: IntValue<'ctx>,
        name: Option<&'ctx str>,
    ) -> ArraySliceValue<'ctx>;
    /// Converts an existing value into a [`ProxyValue`] of this type.
    fn map_value(
        &self,
        value: <Self::Value as ProxyValue<'ctx>>::Base,
        name: Option<&'ctx str>,
    ) -> Self::Value;
    /// Returns the [base type][Self::Base] of this proxy.
    fn as_base_type(&self) -> Self::Base;
 }
--- a/nac3core/src/codegen/types/ndarray.rs
+++ b/nac3core/src/codegen/types/ndarray.rs
@ -0,0 +1,258 @@
 use inkwell::{
    context::Context,
    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
    values::{IntValue, PointerValue},
    AddressSpace,
 };
 use itertools::Itertools;
 use nac3core_derive::StructFields;
 use super::{
    structure::{StructField, StructFields},
    ProxyType,
 };
 use crate::codegen::{
    values::{ArraySliceValue, NDArrayValue, ProxyValue},
    {CodeGenContext, CodeGenerator},
 };
 /// Proxy type for a `ndarray` type in LLVM.
 #[derive(Debug, PartialEq, Eq, Clone, Copy)]
 pub struct NDArrayType<'ctx> {
    ty: PointerType<'ctx>,
    dtype: BasicTypeEnum<'ctx>,
    llvm_usize: IntType<'ctx>,
 }
 #[derive(PartialEq, Eq, Clone, Copy, StructFields)]
 pub struct NDArrayStructFields<'ctx> {
    #[value_type(usize)]
    pub ndims: StructField<'ctx, IntValue<'ctx>>,
    #[value_type(usize.ptr_type(AddressSpace::default()))]
    pub shape: StructField<'ctx, PointerValue<'ctx>>,
    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
    pub data: StructField<'ctx, PointerValue<'ctx>>,
 }
 impl<'ctx> NDArrayType<'ctx> {
    /// Checks whether `llvm_ty` represents a `ndarray` type, returning [Err] if it does not.
    pub fn is_representable(
        llvm_ty: PointerType<'ctx>,
        llvm_usize: IntType<'ctx>,
    ) -> Result<(), String> {
        let llvm_ndarray_ty = llvm_ty.get_element_type();
        let AnyTypeEnum::StructType(llvm_ndarray_ty) = llvm_ndarray_ty else {
            return Err(format!("Expected struct type for `NDArray` type, got {llvm_ndarray_ty}"));
        };
        if llvm_ndarray_ty.count_fields() != 3 {
            return Err(format!(
                "Expected 3 fields in `NDArray`, got {}",
                llvm_ndarray_ty.count_fields()
            ));
        }
        let ndarray_ndims_ty = llvm_ndarray_ty.get_field_type_at_index(0).unwrap();
        let Ok(ndarray_ndims_ty) = IntType::try_from(ndarray_ndims_ty) else {
            return Err(format!("Expected int type for `ndarray.0`, got {ndarray_ndims_ty}"));
        };
        if ndarray_ndims_ty.get_bit_width() != llvm_usize.get_bit_width() {
            return Err(format!(
                "Expected {}-bit int type for `ndarray.0`, got {}-bit int",
                llvm_usize.get_bit_width(),
                ndarray_ndims_ty.get_bit_width()
            ));
        }
        let ndarray_dims_ty = llvm_ndarray_ty.get_field_type_at_index(1).unwrap();
        let Ok(ndarray_pdims) = PointerType::try_from(ndarray_dims_ty) else {
            return Err(format!("Expected pointer type for `ndarray.1`, got {ndarray_dims_ty}"));
        };
        let ndarray_dims = ndarray_pdims.get_element_type();
        let Ok(ndarray_dims) = IntType::try_from(ndarray_dims) else {
            return Err(format!(
                "Expected pointer-to-int type for `ndarray.1`, got pointer-to-{ndarray_dims}"
            ));
        };
        if ndarray_dims.get_bit_width() != llvm_usize.get_bit_width() {
            return Err(format!(
                "Expected pointer-to-{}-bit int type for `ndarray.1`, got pointer-to-{}-bit int",
                llvm_usize.get_bit_width(),
                ndarray_dims.get_bit_width()
            ));
        }
        let ndarray_data_ty = llvm_ndarray_ty.get_field_type_at_index(2).unwrap();
        let Ok(ndarray_pdata) = PointerType::try_from(ndarray_data_ty) else {
            return Err(format!("Expected pointer type for `ndarray.2`, got {ndarray_data_ty}"));
        };
        let ndarray_data = ndarray_pdata.get_element_type();
        let Ok(ndarray_data) = IntType::try_from(ndarray_data) else {
            return Err(format!(
                "Expected pointer-to-int type for `ndarray.2`, got pointer-to-{ndarray_data}"
            ));
        };
        if ndarray_data.get_bit_width() != 8 {
            return Err(format!(
                "Expected pointer-to-8-bit int type for `ndarray.1`, got pointer-to-{}-bit int",
                ndarray_data.get_bit_width()
            ));
        }
        Ok(())
    }
    // TODO: Move this into e.g. StructProxyType
    #[must_use]
    fn fields(ctx: &'ctx Context, llvm_usize: IntType<'ctx>) -> NDArrayStructFields<'ctx> {
        NDArrayStructFields::new(ctx, llvm_usize)
    }
    // TODO: Move this into e.g. StructProxyType
    #[must_use]
    pub fn get_fields(
        &self,
        ctx: &'ctx Context,
        llvm_usize: IntType<'ctx>,
    ) -> NDArrayStructFields<'ctx> {
        Self::fields(ctx, llvm_usize)
    }
    /// Creates an LLVM type corresponding to the expected structure of an `NDArray`.
    #[must_use]
    fn llvm_type(ctx: &'ctx Context, llvm_usize: IntType<'ctx>) -> PointerType<'ctx> {
        // struct NDArray { num_dims: size_t, dims: size_t*, data: i8* }
        //
        // * data    : Pointer to an array containing the array data
        // * itemsize: The size of each NDArray elements in bytes
        // * ndims   : Number of dimensions in the array
        // * shape   : Pointer to an array containing the shape of the NDArray
        // * strides : Pointer to an array indicating the number of bytes between each element at a dimension
        let field_tys =
            Self::fields(ctx, llvm_usize).into_iter().map(|field| field.1).collect_vec();
        ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
    }
    /// Creates an instance of [`NDArrayType`].
    #[must_use]
    pub fn new<G: CodeGenerator + ?Sized>(
        generator: &G,
        ctx: &'ctx Context,
        dtype: BasicTypeEnum<'ctx>,
    ) -> Self {
        let llvm_usize = generator.get_size_type(ctx);
        let llvm_ndarray = Self::llvm_type(ctx, llvm_usize);
        NDArrayType { ty: llvm_ndarray, dtype, llvm_usize }
    }
    /// Creates an [`NDArrayType`] from a [`PointerType`] representing an `NDArray`.
    #[must_use]
    pub fn from_type(
        ptr_ty: PointerType<'ctx>,
        dtype: BasicTypeEnum<'ctx>,
        llvm_usize: IntType<'ctx>,
    ) -> Self {
        debug_assert!(Self::is_representable(ptr_ty, llvm_usize).is_ok());
        NDArrayType { ty: ptr_ty, dtype, llvm_usize }
    }
    /// Returns the type of the `size` field of this `ndarray` type.
    #[must_use]
    pub fn size_type(&self) -> IntType<'ctx> {
        self.as_base_type()
            .get_element_type()
            .into_struct_type()
            .get_field_type_at_index(0)
            .map(BasicTypeEnum::into_int_type)
            .unwrap()
    }
    /// Returns the element type of this `ndarray` type.
    #[must_use]
    pub fn element_type(&self) -> BasicTypeEnum<'ctx> {
        self.dtype
    }
 }
 impl<'ctx> ProxyType<'ctx> for NDArrayType<'ctx> {
    type Base = PointerType<'ctx>;
    type Value = NDArrayValue<'ctx>;
    fn is_type<G: CodeGenerator + ?Sized>(
        generator: &G,
        ctx: &'ctx Context,
        llvm_ty: impl BasicType<'ctx>,
    ) -> Result<(), String> {
        if let BasicTypeEnum::PointerType(ty) = llvm_ty.as_basic_type_enum() {
            <Self as ProxyType<'ctx>>::is_representable(generator, ctx, ty)
        } else {
            Err(format!("Expected pointer type, got {llvm_ty:?}"))
        }
    }
    fn is_representable<G: CodeGenerator + ?Sized>(
        generator: &G,
        ctx: &'ctx Context,
        llvm_ty: Self::Base,
    ) -> Result<(), String> {
        Self::is_representable(llvm_ty, generator.get_size_type(ctx))
    }
    fn new_value<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        name: Option<&'ctx str>,
    ) -> Self::Value {
        self.map_value(
            generator
                .gen_var_alloc(
                    ctx,
                    self.as_base_type().get_element_type().into_struct_type().into(),
                    name,
                )
                .unwrap(),
            name,
        )
    }
    fn new_array_value<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        size: IntValue<'ctx>,
        name: Option<&'ctx str>,
    ) -> ArraySliceValue<'ctx> {
        generator
            .gen_array_var_alloc(
                ctx,
                self.as_base_type().get_element_type().into_struct_type().into(),
                size,
                name,
            )
            .unwrap()
    }
    fn map_value(
        &self,
        value: <Self::Value as ProxyValue<'ctx>>::Base,
        name: Option<&'ctx str>,
    ) -> Self::Value {
        debug_assert_eq!(value.get_type(), self.as_base_type());
        NDArrayValue::from_pointer_value(value, self.dtype, self.llvm_usize, name)
    }
    fn as_base_type(&self) -> Self::Base {
        self.ty
    }
 }
 impl<'ctx> From<NDArrayType<'ctx>> for PointerType<'ctx> {
    fn from(value: NDArrayType<'ctx>) -> Self {
        value.as_base_type()
    }
 }
--- a/nac3core/src/codegen/types/range.rs
+++ b/nac3core/src/codegen/types/range.rs
@ -0,0 +1,159 @@
 use inkwell::{
    context::Context,
    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
    values::IntValue,
    AddressSpace,
 };
 use super::ProxyType;
 use crate::codegen::{
    values::{ArraySliceValue, ProxyValue, RangeValue},
    {CodeGenContext, CodeGenerator},
 };
 /// Proxy type for a `range` type in LLVM.
 #[derive(Debug, PartialEq, Eq, Clone, Copy)]
 pub struct RangeType<'ctx> {
    ty: PointerType<'ctx>,
 }
 impl<'ctx> RangeType<'ctx> {
    /// Checks whether `llvm_ty` represents a `range` type, returning [Err] if it does not.
    pub fn is_representable(llvm_ty: PointerType<'ctx>) -> Result<(), String> {
        let llvm_range_ty = llvm_ty.get_element_type();
        let AnyTypeEnum::ArrayType(llvm_range_ty) = llvm_range_ty else {
            return Err(format!("Expected array type for `range` type, got {llvm_range_ty}"));
        };
        if llvm_range_ty.len() != 3 {
            return Err(format!(
                "Expected 3 elements for `range` type, got {}",
                llvm_range_ty.len()
            ));
        }
        let llvm_range_elem_ty = llvm_range_ty.get_element_type();
        let Ok(llvm_range_elem_ty) = IntType::try_from(llvm_range_elem_ty) else {
            return Err(format!(
                "Expected int type for `range` element type, got {llvm_range_elem_ty}"
            ));
        };
        if llvm_range_elem_ty.get_bit_width() != 32 {
            return Err(format!(
                "Expected 32-bit int type for `range` element type, got {}",
                llvm_range_elem_ty.get_bit_width()
            ));
        }
        Ok(())
    }
    /// Creates an LLVM type corresponding to the expected structure of a `Range`.
    #[must_use]
    fn llvm_type(ctx: &'ctx Context) -> PointerType<'ctx> {
        // typedef int32_t Range[3];
        let llvm_i32 = ctx.i32_type();
        llvm_i32.array_type(3).ptr_type(AddressSpace::default())
    }
    /// Creates an instance of [`RangeType`].
    #[must_use]
    pub fn new(ctx: &'ctx Context) -> Self {
        let llvm_range = Self::llvm_type(ctx);
        RangeType::from_type(llvm_range)
    }
    /// Creates an [`RangeType`] from a [`PointerType`].
    #[must_use]
    pub fn from_type(ptr_ty: PointerType<'ctx>) -> Self {
        debug_assert!(Self::is_representable(ptr_ty).is_ok());
        RangeType { ty: ptr_ty }
    }
    /// Returns the type of all fields of this `range` type.
    #[must_use]
    pub fn value_type(&self) -> IntType<'ctx> {
        self.as_base_type().get_element_type().into_array_type().get_element_type().into_int_type()
    }
 }
 impl<'ctx> ProxyType<'ctx> for RangeType<'ctx> {
    type Base = PointerType<'ctx>;
    type Value = RangeValue<'ctx>;
    fn is_type<G: CodeGenerator + ?Sized>(
        generator: &G,
        ctx: &'ctx Context,
        llvm_ty: impl BasicType<'ctx>,
    ) -> Result<(), String> {
        if let BasicTypeEnum::PointerType(ty) = llvm_ty.as_basic_type_enum() {
            <Self as ProxyType<'ctx>>::is_representable(generator, ctx, ty)
        } else {
            Err(format!("Expected pointer type, got {llvm_ty:?}"))
        }
    }
    fn is_representable<G: CodeGenerator + ?Sized>(
        _: &G,
        _: &'ctx Context,
        llvm_ty: Self::Base,
    ) -> Result<(), String> {
        Self::is_representable(llvm_ty)
    }
    fn new_value<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        name: Option<&'ctx str>,
    ) -> Self::Value {
        self.map_value(
            generator
                .gen_var_alloc(
                    ctx,
                    self.as_base_type().get_element_type().into_struct_type().into(),
                    name,
                )
                .unwrap(),
            name,
        )
    }
    fn new_array_value<G: CodeGenerator + ?Sized>(
        &self,
        generator: &mut G,
        ctx: &mut CodeGenContext<'ctx, '_>,
        size: IntValue<'ctx>,
        name: Option<&'ctx str>,
    ) -> ArraySliceValue<'ctx> {
        generator
            .gen_array_var_alloc(
                ctx,
                self.as_base_type().get_element_type().into_struct_type().into(),
                size,
                name,
            )
            .unwrap()
    }
    fn map_value(
        &self,
        value: <Self::Value as ProxyValue<'ctx>>::Base,
        name: Option<&'ctx str>,
    ) -> Self::Value {
        debug_assert_eq!(value.get_type(), self.as_base_type());
        RangeValue::from_pointer_value(value, name)
    }
    fn as_base_type(&self) -> Self::Base {
        self.ty
    }
 }
 impl<'ctx> From<RangeType<'ctx>> for PointerType<'ctx> {
    fn from(value: RangeType<'ctx>) -> Self {
        value.as_base_type()
    }
 }
--- a/nac3core/src/codegen/types/structure.rs
+++ b/nac3core/src/codegen/types/structure.rs
@ -0,0 +1,203 @@
 use std::marker::PhantomData;
 use inkwell::{
    context::AsContextRef,
    types::{BasicTypeEnum, IntType},
    values::{BasicValue, BasicValueEnum, IntValue, PointerValue, StructValue},
 };
 use crate::codegen::CodeGenContext;
 /// Trait indicating that the structure is a field-wise representation of an LLVM structure.
 ///
 /// # Usage
 ///
 /// For example, for a simple C-slice LLVM structure:
 ///
 /// ```ignore
 /// struct CSliceFields<'ctx> {
 ///     ptr: StructField<'ctx, PointerValue<'ctx>>,
 ///     len: StructField<'ctx, IntValue<'ctx>>
 /// }
 /// ```
 pub trait StructFields<'ctx>: Eq + Copy {
    /// Creates an instance of [`StructFields`] using the given `ctx` and `size_t` types.
    fn new(ctx: impl AsContextRef<'ctx>, llvm_usize: IntType<'ctx>) -> Self;
    /// Returns a [`Vec`] that contains the fields of the structure in the order as they appear in
    /// the type definition.
    #[must_use]
    fn to_vec(&self) -> Vec<(&'static str, BasicTypeEnum<'ctx>)>;
    /// Returns a [`Iterator`] that contains the fields of the structure in the order as they appear
    /// in the type definition.
    #[must_use]
    fn iter(&self) -> impl Iterator<Item = (&'static str, BasicTypeEnum<'ctx>)> {
        self.to_vec().into_iter()
    }
    /// Returns a [`Vec`] that contains the fields of the structure in the order as they appear in
    /// the type definition.
    #[must_use]
    fn into_vec(self) -> Vec<(&'static str, BasicTypeEnum<'ctx>)>
    where
        Self: Sized,
    {
        self.to_vec()
    }
    /// Returns a [`Iterator`] that contains the fields of the structure in the order as they appear
    /// in the type definition.
    #[must_use]
    fn into_iter(self) -> impl Iterator<Item = (&'static str, BasicTypeEnum<'ctx>)>
    where
        Self: Sized,
    {
        self.into_vec().into_iter()
    }
 }
 /// A single field of an LLVM structure.
 #[derive(Debug, PartialEq, Eq, Clone, Copy)]
 pub struct StructField<'ctx, Value>
 where
    Value: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>, Error = ()>,
 {
    /// The index of this field within the structure.
    index: u32,
    /// The name of this field.
    name: &'static str,
    /// The type of this field.
    ty: BasicTypeEnum<'ctx>,
    /// Instance of [`PhantomData`] containing [`Value`], used to implement automatic downcasts.
    _value_ty: PhantomData<Value>,
 }
 impl<'ctx, Value> StructField<'ctx, Value>
 where
    Value: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>, Error = ()>,
 {
    /// Creates an instance of [`StructField`].
    ///
    /// * `idx_counter` - The instance of [`FieldIndexCounter`] used to track the current field
    ///   index.
    /// * `name` - Name of the field.
    /// * `ty` - The type of this field.
    pub fn create(
        idx_counter: &mut FieldIndexCounter,
        name: &'static str,
        ty: impl Into<BasicTypeEnum<'ctx>>,
    ) -> Self {
        StructField { index: idx_counter.increment(), name, ty: ty.into(), _value_ty: PhantomData }
    }
    /// Creates an instance of [`StructField`] with a given index.
    ///
    /// * `index` - The index of this field within its enclosing structure.
    /// * `name` - Name of the field.
    /// * `ty` - The type of this field.
    pub fn create_at(index: u32, name: &'static str, ty: impl Into<BasicTypeEnum<'ctx>>) -> Self {
        StructField { index, name, ty: ty.into(), _value_ty: PhantomData }
    }
    /// Creates a pointer to this field in an arbitrary structure by performing a `getelementptr i32
    /// {idx...}, i32 {self.index}`.
    pub fn ptr_by_array_gep(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        pobj: PointerValue<'ctx>,
        idx: &[IntValue<'ctx>],
    ) -> PointerValue<'ctx> {
        unsafe {
            ctx.builder.build_in_bounds_gep(
                pobj,
                &[idx, &[ctx.ctx.i32_type().const_int(u64::from(self.index), false)]].concat(),
                "",
            )
        }
        .unwrap()
    }
    /// Creates a pointer to this field in an arbitrary structure by performing the equivalent of
    /// `getelementptr i32 0, i32 {self.index}`.
    pub fn ptr_by_gep(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        pobj: PointerValue<'ctx>,
        obj_name: Option<&'ctx str>,
    ) -> PointerValue<'ctx> {
        ctx.builder
            .build_struct_gep(
                pobj,
                self.index,
                &obj_name.map(|name| format!("{name}.{}.addr", self.name)).unwrap_or_default(),
            )
            .unwrap()
    }
    /// Gets the value of this field for a given `obj`.
    #[must_use]
    pub fn get_from_value(&self, obj: StructValue<'ctx>) -> Value {
        obj.get_field_at_index(self.index).and_then(|value| Value::try_from(value).ok()).unwrap()
    }
    /// Sets the value of this field for a given `obj`.
    pub fn set_from_value(&self, obj: StructValue<'ctx>, value: Value) {
        obj.set_field_at_index(self.index, value);
    }
    /// Gets the value of this field for a pointer-to-structure.
    pub fn get(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        pobj: PointerValue<'ctx>,
        obj_name: Option<&'ctx str>,
    ) -> Value {
        ctx.builder
            .build_load(
                self.ptr_by_gep(ctx, pobj, obj_name),
                &obj_name.map(|name| format!("{name}.{}", self.name)).unwrap_or_default(),
            )
            .map_err(|_| ())
            .and_then(|value| Value::try_from(value))
            .unwrap()
    }
    /// Sets the value of this field for a pointer-to-structure.
    pub fn set(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        pobj: PointerValue<'ctx>,
        value: Value,
        obj_name: Option<&'ctx str>,
    ) {
        ctx.builder.build_store(self.ptr_by_gep(ctx, pobj, obj_name), value).unwrap();
    }
 }
 impl<'ctx, Value> From<StructField<'ctx, Value>> for (&'static str, BasicTypeEnum<'ctx>)
 where
    Value: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>, Error = ()>,
 {
    fn from(value: StructField<'ctx, Value>) -> Self {
        (value.name, value.ty)
    }
 }
 /// A counter that tracks the next index of a field using a monotonically increasing counter.
 #[derive(Default, Debug, PartialEq, Eq, Clone, Copy)]
 pub struct FieldIndexCounter(u32);
 impl FieldIndexCounter {
    /// Increments the number stored by this counter, returning the previous value.
    ///
    /// Functionally equivalent to `i++` in C-based languages.
    pub fn increment(&mut self) -> u32 {
        let v = self.0;
        self.0 += 1;
        v
    }
 }
--- a/nac3core/src/codegen/values/array.rs
+++ b/nac3core/src/codegen/values/array.rs
@ -0,0 +1,426 @@
 use inkwell::{
    types::AnyTypeEnum,
    values::{BasicValueEnum, IntValue, PointerValue},
    IntPredicate,
 };
 use crate::codegen::{CodeGenContext, CodeGenerator};
 /// An LLVM value that is array-like, i.e. it contains a contiguous, sequenced collection of
 /// elements.
 pub trait ArrayLikeValue<'ctx> {
    /// Returns the element type of this array-like value.
    fn element_type<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        generator: &G,
    ) -> AnyTypeEnum<'ctx>;
    /// Returns the base pointer to the array.
    fn base_ptr<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        generator: &G,
    ) -> PointerValue<'ctx>;
    /// Returns the size of this array-like value.
    fn size<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        generator: &G,
    ) -> IntValue<'ctx>;
    /// Returns a [`ArraySliceValue`] representing this value.
    fn as_slice_value<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        generator: &G,
    ) -> ArraySliceValue<'ctx> {
        ArraySliceValue::from_ptr_val(
            self.base_ptr(ctx, generator),
            self.size(ctx, generator),
            None,
        )
    }
 }
 /// An array-like value that can be indexed by memory offset.
 pub trait ArrayLikeIndexer<'ctx, Index = IntValue<'ctx>>: ArrayLikeValue<'ctx> {
    /// # Safety
    ///
    /// This function should be called with a valid index.
    unsafe fn ptr_offset_unchecked<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &Index,
        name: Option<&str>,
    ) -> PointerValue<'ctx>;
    /// Returns the pointer to the data at the `idx`-th index.
    fn ptr_offset<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &Index,
        name: Option<&str>,
    ) -> PointerValue<'ctx>;
 }
 /// An array-like value that can have its array elements accessed as a [`BasicValueEnum`].
 pub trait UntypedArrayLikeAccessor<'ctx, Index = IntValue<'ctx>>:
    ArrayLikeIndexer<'ctx, Index>
 {
    /// # Safety
    ///
    /// This function should be called with a valid index.
    unsafe fn get_unchecked<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &Index,
        name: Option<&str>,
    ) -> BasicValueEnum<'ctx> {
        let ptr = unsafe { self.ptr_offset_unchecked(ctx, generator, idx, name) };
        ctx.builder.build_load(ptr, name.unwrap_or_default()).unwrap()
    }
    /// Returns the data at the `idx`-th index.
    fn get<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &Index,
        name: Option<&str>,
    ) -> BasicValueEnum<'ctx> {
        let ptr = self.ptr_offset(ctx, generator, idx, name);
        ctx.builder.build_load(ptr, name.unwrap_or_default()).unwrap()
    }
 }
 /// An array-like value that can have its array elements mutated as a [`BasicValueEnum`].
 pub trait UntypedArrayLikeMutator<'ctx, Index = IntValue<'ctx>>:
    ArrayLikeIndexer<'ctx, Index>
 {
    /// # Safety
    ///
    /// This function should be called with a valid index.
    unsafe fn set_unchecked<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &Index,
        value: BasicValueEnum<'ctx>,
    ) {
        let ptr = unsafe { self.ptr_offset_unchecked(ctx, generator, idx, None) };
        ctx.builder.build_store(ptr, value).unwrap();
    }
    /// Sets the data at the `idx`-th index.
    fn set<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &Index,
        value: BasicValueEnum<'ctx>,
    ) {
        let ptr = self.ptr_offset(ctx, generator, idx, None);
        ctx.builder.build_store(ptr, value).unwrap();
    }
 }
 /// An array-like value that can have its array elements accessed as an arbitrary type `T`.
 pub trait TypedArrayLikeAccessor<'ctx, T, Index = IntValue<'ctx>>:
    UntypedArrayLikeAccessor<'ctx, Index>
 {
    /// Casts an element from [`BasicValueEnum`] into `T`.
    fn downcast_to_type(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        value: BasicValueEnum<'ctx>,
    ) -> T;
    /// # Safety
    ///
    /// This function should be called with a valid index.
    unsafe fn get_typed_unchecked<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &Index,
        name: Option<&str>,
    ) -> T {
        let value = unsafe { self.get_unchecked(ctx, generator, idx, name) };
        self.downcast_to_type(ctx, value)
    }
    /// Returns the data at the `idx`-th index.
    fn get_typed<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &Index,
        name: Option<&str>,
    ) -> T {
        let value = self.get(ctx, generator, idx, name);
        self.downcast_to_type(ctx, value)
    }
 }
 /// An array-like value that can have its array elements mutated as an arbitrary type `T`.
 pub trait TypedArrayLikeMutator<'ctx, T, Index = IntValue<'ctx>>:
    UntypedArrayLikeMutator<'ctx, Index>
 {
    /// Casts an element from T into [`BasicValueEnum`].
    fn upcast_from_type(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        value: T,
    ) -> BasicValueEnum<'ctx>;
    /// # Safety
    ///
    /// This function should be called with a valid index.
    unsafe fn set_typed_unchecked<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &Index,
        value: T,
    ) {
        let value = self.upcast_from_type(ctx, value);
        unsafe { self.set_unchecked(ctx, generator, idx, value) }
    }
    /// Sets the data at the `idx`-th index.
    fn set_typed<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &Index,
        value: T,
    ) {
        let value = self.upcast_from_type(ctx, value);
        self.set(ctx, generator, idx, value);
    }
 }
 /// Type alias for a function that casts a [`BasicValueEnum`] into a `T`.
 type ValueDowncastFn<'ctx, T> =
    Box<dyn Fn(&mut CodeGenContext<'ctx, '_>, BasicValueEnum<'ctx>) -> T>;
 /// Type alias for a function that casts a `T` into a [`BasicValueEnum`].
 type ValueUpcastFn<'ctx, T> = Box<dyn Fn(&mut CodeGenContext<'ctx, '_>, T) -> BasicValueEnum<'ctx>>;
 /// An adapter for constraining untyped array values as typed values.
 pub struct TypedArrayLikeAdapter<'ctx, T, Adapted: ArrayLikeValue<'ctx> = ArraySliceValue<'ctx>> {
    adapted: Adapted,
    downcast_fn: ValueDowncastFn<'ctx, T>,
    upcast_fn: ValueUpcastFn<'ctx, T>,
 }
 impl<'ctx, T, Adapted> TypedArrayLikeAdapter<'ctx, T, Adapted>
 where
    Adapted: ArrayLikeValue<'ctx>,
 {
    /// Creates a [`TypedArrayLikeAdapter`].
    ///
    /// * `adapted` - The value to be adapted.
    /// * `downcast_fn` - The function converting a [`BasicValueEnum`] into a `T`.
    /// * `upcast_fn` - The function converting a T into a [`BasicValueEnum`].
    pub fn from(
        adapted: Adapted,
        downcast_fn: ValueDowncastFn<'ctx, T>,
        upcast_fn: ValueUpcastFn<'ctx, T>,
    ) -> Self {
        TypedArrayLikeAdapter { adapted, downcast_fn, upcast_fn }
    }
 }
 impl<'ctx, T, Adapted> ArrayLikeValue<'ctx> for TypedArrayLikeAdapter<'ctx, T, Adapted>
 where
    Adapted: ArrayLikeValue<'ctx>,
 {
    fn element_type<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        generator: &G,
    ) -> AnyTypeEnum<'ctx> {
        self.adapted.element_type(ctx, generator)
    }
    fn base_ptr<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        generator: &G,
    ) -> PointerValue<'ctx> {
        self.adapted.base_ptr(ctx, generator)
    }
    fn size<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        generator: &G,
    ) -> IntValue<'ctx> {
        self.adapted.size(ctx, generator)
    }
 }
 impl<'ctx, T, Index, Adapted> ArrayLikeIndexer<'ctx, Index>
    for TypedArrayLikeAdapter<'ctx, T, Adapted>
 where
    Adapted: ArrayLikeIndexer<'ctx, Index>,
 {
    unsafe fn ptr_offset_unchecked<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &Index,
        name: Option<&str>,
    ) -> PointerValue<'ctx> {
        unsafe { self.adapted.ptr_offset_unchecked(ctx, generator, idx, name) }
    }
    fn ptr_offset<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &Index,
        name: Option<&str>,
    ) -> PointerValue<'ctx> {
        self.adapted.ptr_offset(ctx, generator, idx, name)
    }
 }
 impl<'ctx, T, Index, Adapted> UntypedArrayLikeAccessor<'ctx, Index>
    for TypedArrayLikeAdapter<'ctx, T, Adapted>
 where
    Adapted: UntypedArrayLikeAccessor<'ctx, Index>,
 {
 }
 impl<'ctx, T, Index, Adapted> UntypedArrayLikeMutator<'ctx, Index>
    for TypedArrayLikeAdapter<'ctx, T, Adapted>
 where
    Adapted: UntypedArrayLikeMutator<'ctx, Index>,
 {
 }
 impl<'ctx, T, Index, Adapted> TypedArrayLikeAccessor<'ctx, T, Index>
    for TypedArrayLikeAdapter<'ctx, T, Adapted>
 where
    Adapted: UntypedArrayLikeAccessor<'ctx, Index>,
 {
    fn downcast_to_type(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        value: BasicValueEnum<'ctx>,
    ) -> T {
        (self.downcast_fn)(ctx, value)
    }
 }
 impl<'ctx, T, Index, Adapted> TypedArrayLikeMutator<'ctx, T, Index>
    for TypedArrayLikeAdapter<'ctx, T, Adapted>
 where
    Adapted: UntypedArrayLikeMutator<'ctx, Index>,
 {
    fn upcast_from_type(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        value: T,
    ) -> BasicValueEnum<'ctx> {
        (self.upcast_fn)(ctx, value)
    }
 }
 /// An LLVM value representing an array slice, consisting of a pointer to the data and the size of
 /// the slice.
 #[derive(Copy, Clone)]
 pub struct ArraySliceValue<'ctx>(PointerValue<'ctx>, IntValue<'ctx>, Option<&'ctx str>);
 impl<'ctx> ArraySliceValue<'ctx> {
    /// Creates an [`ArraySliceValue`] from a [`PointerValue`] and its size.
    #[must_use]
    pub fn from_ptr_val(
        ptr: PointerValue<'ctx>,
        size: IntValue<'ctx>,
        name: Option<&'ctx str>,
    ) -> Self {
        ArraySliceValue(ptr, size, name)
    }
 }
 impl<'ctx> From<ArraySliceValue<'ctx>> for PointerValue<'ctx> {
    fn from(value: ArraySliceValue<'ctx>) -> Self {
        value.0
    }
 }
 impl<'ctx> ArrayLikeValue<'ctx> for ArraySliceValue<'ctx> {
    fn element_type<G: CodeGenerator + ?Sized>(
        &self,
        _: &CodeGenContext<'ctx, '_>,
        _: &G,
    ) -> AnyTypeEnum<'ctx> {
        self.0.get_type().get_element_type()
    }
    fn base_ptr<G: CodeGenerator + ?Sized>(
        &self,
        _: &CodeGenContext<'ctx, '_>,
        _: &G,
    ) -> PointerValue<'ctx> {
        self.0
    }
    fn size<G: CodeGenerator + ?Sized>(
        &self,
        _: &CodeGenContext<'ctx, '_>,
        _: &G,
    ) -> IntValue<'ctx> {
        self.1
    }
 }
 impl<'ctx> ArrayLikeIndexer<'ctx> for ArraySliceValue<'ctx> {
    unsafe fn ptr_offset_unchecked<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &IntValue<'ctx>,
        name: Option<&str>,
    ) -> PointerValue<'ctx> {
        let var_name = name.map(|v| format!("{v}.addr")).unwrap_or_default();
        unsafe {
            ctx.builder
                .build_in_bounds_gep(self.base_ptr(ctx, generator), &[*idx], var_name.as_str())
                .unwrap()
        }
    }
    fn ptr_offset<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &IntValue<'ctx>,
        name: Option<&str>,
    ) -> PointerValue<'ctx> {
        debug_assert_eq!(idx.get_type(), generator.get_size_type(ctx.ctx));
        let size = self.size(ctx, generator);
        let in_range = ctx.builder.build_int_compare(IntPredicate::ULT, *idx, size, "").unwrap();
        ctx.make_assert(
            generator,
            in_range,
            "0:IndexError",
            "list index out of range",
            [None, None, None],
            ctx.current_loc,
        );
        unsafe { self.ptr_offset_unchecked(ctx, generator, idx, name) }
    }
 }
 impl<'ctx> UntypedArrayLikeAccessor<'ctx> for ArraySliceValue<'ctx> {}
 impl<'ctx> UntypedArrayLikeMutator<'ctx> for ArraySliceValue<'ctx> {}
--- a/nac3core/src/codegen/values/list.rs
+++ b/nac3core/src/codegen/values/list.rs
@ -0,0 +1,241 @@
 use inkwell::{
    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType},
    values::{BasicValueEnum, IntValue, PointerValue},
    AddressSpace, IntPredicate,
 };
 use super::{
    ArrayLikeIndexer, ArrayLikeValue, ProxyValue, UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
 };
 use crate::codegen::{
    types::ListType,
    {CodeGenContext, CodeGenerator},
 };
 /// Proxy type for accessing a `list` value in LLVM.
 #[derive(Copy, Clone)]
 pub struct ListValue<'ctx> {
    value: PointerValue<'ctx>,
    llvm_usize: IntType<'ctx>,
    name: Option<&'ctx str>,
 }
 impl<'ctx> ListValue<'ctx> {
    /// Checks whether `value` is an instance of `list`, returning [Err] if `value` is not an
    /// instance.
    pub fn is_representable(
        value: PointerValue<'ctx>,
        llvm_usize: IntType<'ctx>,
    ) -> Result<(), String> {
        ListType::is_representable(value.get_type(), llvm_usize)
    }
    /// Creates an [`ListValue`] from a [`PointerValue`].
    #[must_use]
    pub fn from_pointer_value(
        ptr: PointerValue<'ctx>,
        llvm_usize: IntType<'ctx>,
        name: Option<&'ctx str>,
    ) -> Self {
        debug_assert!(Self::is_representable(ptr, llvm_usize).is_ok());
        ListValue { value: ptr, llvm_usize, name }
    }
    /// Returns the double-indirection pointer to the `data` array, as if by calling `getelementptr`
    /// on the field.
    fn pptr_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();
        unsafe {
            ctx.builder
                .build_in_bounds_gep(
                    self.as_base_value(),
                    &[llvm_i32.const_zero(), llvm_i32.const_zero()],
                    var_name.as_str(),
                )
                .unwrap()
        }
    }
    /// Returns the pointer to the field storing the size of this `list`.
    fn ptr_to_size(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
        let llvm_i32 = ctx.ctx.i32_type();
        let var_name = self.name.map(|v| format!("{v}.size.addr")).unwrap_or_default();
        unsafe {
            ctx.builder
                .build_in_bounds_gep(
                    self.as_base_value(),
                    &[llvm_i32.const_zero(), llvm_i32.const_int(1, true)],
                    var_name.as_str(),
                )
                .unwrap()
        }
    }
    /// Stores the array of data elements `data` into this instance.
    fn store_data(&self, ctx: &CodeGenContext<'ctx, '_>, data: PointerValue<'ctx>) {
        ctx.builder.build_store(self.pptr_to_data(ctx), data).unwrap();
    }
    /// Convenience method for creating a new array storing data elements with the given element
    /// type `elem_ty` and `size`.
    ///
    /// If `size` is [None], the size stored in the field of this instance is used instead.
    pub fn create_data(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        elem_ty: BasicTypeEnum<'ctx>,
        size: Option<IntValue<'ctx>>,
    ) {
        let size = size.unwrap_or_else(|| self.load_size(ctx, None));
        let data = ctx
            .builder
            .build_select(
                ctx.builder
                    .build_int_compare(IntPredicate::NE, size, self.llvm_usize.const_zero(), "")
                    .unwrap(),
                ctx.builder.build_array_alloca(elem_ty, size, "").unwrap(),
                elem_ty.ptr_type(AddressSpace::default()).const_zero(),
                "",
            )
            .map(BasicValueEnum::into_pointer_value)
            .unwrap();
        self.store_data(ctx, data);
    }
    /// Returns the double-indirection pointer to the `data` array, as if by calling `getelementptr`
    /// on the field.
    #[must_use]
    pub fn data(&self) -> ListDataProxy<'ctx, '_> {
        ListDataProxy(self)
    }
    /// Stores the `size` of this `list` into this instance.
    pub fn store_size<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        generator: &G,
        size: IntValue<'ctx>,
    ) {
        debug_assert_eq!(size.get_type(), generator.get_size_type(ctx.ctx));
        let psize = self.ptr_to_size(ctx);
        ctx.builder.build_store(psize, size).unwrap();
    }
    /// Returns the size of this `list` as a value.
    pub fn load_size(&self, ctx: &CodeGenContext<'ctx, '_>, name: Option<&str>) -> IntValue<'ctx> {
        let psize = self.ptr_to_size(ctx);
        let var_name = name
            .map(ToString::to_string)
            .or_else(|| self.name.map(|v| format!("{v}.size")))
            .unwrap_or_default();
        ctx.builder
            .build_load(psize, var_name.as_str())
            .map(BasicValueEnum::into_int_value)
            .unwrap()
    }
 }
 impl<'ctx> ProxyValue<'ctx> for ListValue<'ctx> {
    type Base = PointerValue<'ctx>;
    type Type = ListType<'ctx>;
    fn get_type(&self) -> Self::Type {
        ListType::from_type(self.as_base_value().get_type(), self.llvm_usize)
    }
    fn as_base_value(&self) -> Self::Base {
        self.value
    }
 }
 impl<'ctx> From<ListValue<'ctx>> for PointerValue<'ctx> {
    fn from(value: ListValue<'ctx>) -> Self {
        value.as_base_value()
    }
 }
 /// Proxy type for accessing the `data` array of an `list` instance in LLVM.
 #[derive(Copy, Clone)]
 pub struct ListDataProxy<'ctx, 'a>(&'a ListValue<'ctx>);
 impl<'ctx> ArrayLikeValue<'ctx> for ListDataProxy<'ctx, '_> {
    fn element_type<G: CodeGenerator + ?Sized>(
        &self,
        _: &CodeGenContext<'ctx, '_>,
        _: &G,
    ) -> AnyTypeEnum<'ctx> {
        self.0.value.get_type().get_element_type()
    }
    fn base_ptr<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        _: &G,
    ) -> PointerValue<'ctx> {
        let var_name = self.0.name.map(|v| format!("{v}.data")).unwrap_or_default();
        ctx.builder
            .build_load(self.0.pptr_to_data(ctx), var_name.as_str())
            .map(BasicValueEnum::into_pointer_value)
            .unwrap()
    }
    fn size<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        _: &G,
    ) -> IntValue<'ctx> {
        self.0.load_size(ctx, None)
    }
 }
 impl<'ctx> ArrayLikeIndexer<'ctx> for ListDataProxy<'ctx, '_> {
    unsafe fn ptr_offset_unchecked<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &IntValue<'ctx>,
        name: Option<&str>,
    ) -> PointerValue<'ctx> {
        let var_name = name.map(|v| format!("{v}.addr")).unwrap_or_default();
        unsafe {
            ctx.builder
                .build_in_bounds_gep(self.base_ptr(ctx, generator), &[*idx], var_name.as_str())
                .unwrap()
        }
    }
    fn ptr_offset<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &IntValue<'ctx>,
        name: Option<&str>,
    ) -> PointerValue<'ctx> {
        debug_assert_eq!(idx.get_type(), generator.get_size_type(ctx.ctx));
        let size = self.size(ctx, generator);
        let in_range = ctx.builder.build_int_compare(IntPredicate::ULT, *idx, size, "").unwrap();
        ctx.make_assert(
            generator,
            in_range,
            "0:IndexError",
            "list index out of range",
            [None, None, None],
            ctx.current_loc,
        );
        unsafe { self.ptr_offset_unchecked(ctx, generator, idx, name) }
    }
 }
 impl<'ctx> UntypedArrayLikeAccessor<'ctx> for ListDataProxy<'ctx, '_> {}
 impl<'ctx> UntypedArrayLikeMutator<'ctx> for ListDataProxy<'ctx, '_> {}
--- a/nac3core/src/codegen/values/mod.rs
+++ b/nac3core/src/codegen/values/mod.rs
@ -0,0 +1,47 @@
 use inkwell::{context::Context, values::BasicValue};
 use super::types::ProxyType;
 use crate::codegen::CodeGenerator;
 pub use array::*;
 pub use list::*;
 pub use ndarray::*;
 pub use range::*;
 mod array;
 mod list;
 mod ndarray;
 mod range;
 /// A LLVM type that is used to represent a non-primitive value in NAC3.
 pub trait ProxyValue<'ctx>: Into<Self::Base> {
    /// The type of LLVM values represented by this instance. This is usually the
    /// [LLVM pointer type][PointerValue].
    type Base: BasicValue<'ctx>;
    /// The type of this value.
    type Type: ProxyType<'ctx, Value = Self>;
    /// Checks whether `value` can be represented by this [`ProxyValue`].
    fn is_instance<G: CodeGenerator + ?Sized>(
        generator: &G,
        ctx: &'ctx Context,
        value: impl BasicValue<'ctx>,
    ) -> Result<(), String> {
        Self::Type::is_type(generator, ctx, value.as_basic_value_enum().get_type())
    }
    /// Checks whether `value` can be represented by this [`ProxyValue`].
    fn is_representable<G: CodeGenerator + ?Sized>(
        generator: &G,
        ctx: &'ctx Context,
        value: Self::Base,
    ) -> Result<(), String> {
        Self::is_instance(generator, ctx, value.as_basic_value_enum())
    }
    /// Returns the [type][ProxyType] of this value.
    fn get_type(&self) -> Self::Type;
    /// Returns the [base value][Self::Base] of this proxy.
    fn as_base_value(&self) -> Self::Base;
 }
--- a/nac3core/src/codegen/values/ndarray.rs
+++ b/nac3core/src/codegen/values/ndarray.rs
@ -0,0 +1,523 @@
 use inkwell::{
    types::{AnyType, AnyTypeEnum, BasicType, BasicTypeEnum, IntType},
    values::{BasicValueEnum, IntValue, PointerValue},
    AddressSpace, IntPredicate,
 };
 use super::{
    ArrayLikeIndexer, ArrayLikeValue, ProxyValue, TypedArrayLikeAccessor, TypedArrayLikeMutator,
    UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
 };
 use crate::codegen::{
    irrt::{call_ndarray_calc_size, call_ndarray_flatten_index},
    llvm_intrinsics::call_int_umin,
    stmt::gen_for_callback_incrementing,
    types::NDArrayType,
    CodeGenContext, CodeGenerator,
 };
 /// Proxy type for accessing an `NDArray` value in LLVM.
 #[derive(Copy, Clone)]
 pub struct NDArrayValue<'ctx> {
    value: PointerValue<'ctx>,
    dtype: BasicTypeEnum<'ctx>,
    llvm_usize: IntType<'ctx>,
    name: Option<&'ctx str>,
 }
 impl<'ctx> NDArrayValue<'ctx> {
    /// Checks whether `value` is an instance of `NDArray`, returning [Err] if `value` is not an
    /// instance.
    pub fn is_representable(
        value: PointerValue<'ctx>,
        llvm_usize: IntType<'ctx>,
    ) -> Result<(), String> {
        NDArrayType::is_representable(value.get_type(), llvm_usize)
    }
    /// Creates an [`NDArrayValue`] from a [`PointerValue`].
    #[must_use]
    pub fn from_pointer_value(
        ptr: PointerValue<'ctx>,
        dtype: BasicTypeEnum<'ctx>,
        llvm_usize: IntType<'ctx>,
        name: Option<&'ctx str>,
    ) -> Self {
        debug_assert!(Self::is_representable(ptr, llvm_usize).is_ok());
        NDArrayValue { value: ptr, dtype, llvm_usize, name }
    }
    /// Returns the pointer to the field storing the number of dimensions of this `NDArray`.
    fn ptr_to_ndims(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
        self.get_type()
            .get_fields(ctx.ctx, self.llvm_usize)
            .ndims
            .ptr_by_gep(ctx, self.value, self.name)
    }
    /// Stores the number of dimensions `ndims` into this instance.
    pub fn store_ndims<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        generator: &G,
        ndims: IntValue<'ctx>,
    ) {
        debug_assert_eq!(ndims.get_type(), generator.get_size_type(ctx.ctx));
        let pndims = self.ptr_to_ndims(ctx);
        ctx.builder.build_store(pndims, ndims).unwrap();
    }
    /// Returns the number of dimensions of this `NDArray` as a value.
    pub fn load_ndims(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
        let pndims = self.ptr_to_ndims(ctx);
        ctx.builder.build_load(pndims, "").map(BasicValueEnum::into_int_value).unwrap()
    }
    /// Returns the double-indirection pointer to the `shape` array, as if by calling
    /// `getelementptr` on the field.
    fn ptr_to_shape(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
        self.get_type()
            .get_fields(ctx.ctx, self.llvm_usize)
            .shape
            .ptr_by_gep(ctx, self.value, self.name)
    }
    /// Stores the array of dimension sizes `dims` into this instance.
    fn store_shape(&self, ctx: &CodeGenContext<'ctx, '_>, dims: PointerValue<'ctx>) {
        ctx.builder.build_store(self.ptr_to_shape(ctx), dims).unwrap();
    }
    /// Convenience method for creating a new array storing dimension sizes with the given `size`.
    pub fn create_shape(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        llvm_usize: IntType<'ctx>,
        size: IntValue<'ctx>,
    ) {
        self.store_shape(ctx, ctx.builder.build_array_alloca(llvm_usize, size, "").unwrap());
    }
    /// Returns a proxy object to the field storing the size of each dimension of this `NDArray`.
    #[must_use]
    pub fn shape(&self) -> NDArrayShapeProxy<'ctx, '_> {
        NDArrayShapeProxy(self)
    }
    /// 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> {
        self.get_type()
            .get_fields(ctx.ctx, self.llvm_usize)
            .data
            .ptr_by_gep(ctx, self.value, self.name)
    }
    /// Stores the array of data elements `data` into this instance.
    fn store_data(&self, ctx: &CodeGenContext<'ctx, '_>, data: PointerValue<'ctx>) {
        let data = ctx
            .builder
            .build_bit_cast(data, ctx.ctx.i8_type().ptr_type(AddressSpace::default()), "")
            .unwrap();
        ctx.builder.build_store(self.ptr_to_data(ctx), data).unwrap();
    }
    /// Convenience method for creating a new array storing data elements with the given element
    /// type `elem_ty` and `size`.
    pub fn create_data(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        elem_ty: BasicTypeEnum<'ctx>,
        size: IntValue<'ctx>,
    ) {
        let itemsize =
            ctx.builder.build_int_cast(elem_ty.size_of().unwrap(), size.get_type(), "").unwrap();
        let nbytes = ctx.builder.build_int_mul(size, itemsize, "").unwrap();
        // TODO: What about alignment?
        self.store_data(
            ctx,
            ctx.builder.build_array_alloca(ctx.ctx.i8_type(), nbytes, "").unwrap(),
        );
    }
    /// Returns a proxy object to the field storing the data of this `NDArray`.
    #[must_use]
    pub fn data(&self) -> NDArrayDataProxy<'ctx, '_> {
        NDArrayDataProxy(self)
    }
 }
 impl<'ctx> ProxyValue<'ctx> for NDArrayValue<'ctx> {
    type Base = PointerValue<'ctx>;
    type Type = NDArrayType<'ctx>;
    fn get_type(&self) -> Self::Type {
        NDArrayType::from_type(self.as_base_value().get_type(), self.dtype, self.llvm_usize)
    }
    fn as_base_value(&self) -> Self::Base {
        self.value
    }
 }
 impl<'ctx> From<NDArrayValue<'ctx>> for PointerValue<'ctx> {
    fn from(value: NDArrayValue<'ctx>) -> Self {
        value.as_base_value()
    }
 }
 /// Proxy type for accessing the `dims` array of an `NDArray` instance in LLVM.
 #[derive(Copy, Clone)]
 pub struct NDArrayShapeProxy<'ctx, 'a>(&'a NDArrayValue<'ctx>);
 impl<'ctx> ArrayLikeValue<'ctx> for NDArrayShapeProxy<'ctx, '_> {
    fn element_type<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        generator: &G,
    ) -> AnyTypeEnum<'ctx> {
        self.0.shape().base_ptr(ctx, generator).get_type().get_element_type()
    }
    fn base_ptr<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        _: &G,
    ) -> PointerValue<'ctx> {
        let var_name = self.0.name.map(|v| format!("{v}.data")).unwrap_or_default();
        ctx.builder
            .build_load(self.0.ptr_to_shape(ctx), var_name.as_str())
            .map(BasicValueEnum::into_pointer_value)
            .unwrap()
    }
    fn size<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        _: &G,
    ) -> IntValue<'ctx> {
        self.0.load_ndims(ctx)
    }
 }
 impl<'ctx> ArrayLikeIndexer<'ctx, IntValue<'ctx>> for NDArrayShapeProxy<'ctx, '_> {
    unsafe fn ptr_offset_unchecked<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &IntValue<'ctx>,
        name: Option<&str>,
    ) -> PointerValue<'ctx> {
        let var_name = name.map(|v| format!("{v}.addr")).unwrap_or_default();
        unsafe {
            ctx.builder
                .build_in_bounds_gep(self.base_ptr(ctx, generator), &[*idx], var_name.as_str())
                .unwrap()
        }
    }
    fn ptr_offset<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &IntValue<'ctx>,
        name: Option<&str>,
    ) -> PointerValue<'ctx> {
        let size = self.size(ctx, generator);
        let in_range = ctx.builder.build_int_compare(IntPredicate::ULT, *idx, size, "").unwrap();
        ctx.make_assert(
            generator,
            in_range,
            "0:IndexError",
            "index {0} is out of bounds for axis 0 with size {1}",
            [Some(*idx), Some(self.0.load_ndims(ctx)), None],
            ctx.current_loc,
        );
        unsafe { self.ptr_offset_unchecked(ctx, generator, idx, name) }
    }
 }
 impl<'ctx> UntypedArrayLikeAccessor<'ctx, IntValue<'ctx>> for NDArrayShapeProxy<'ctx, '_> {}
 impl<'ctx> UntypedArrayLikeMutator<'ctx, IntValue<'ctx>> for NDArrayShapeProxy<'ctx, '_> {}
 impl<'ctx> TypedArrayLikeAccessor<'ctx, IntValue<'ctx>> for NDArrayShapeProxy<'ctx, '_> {
    fn downcast_to_type(
        &self,
        _: &mut CodeGenContext<'ctx, '_>,
        value: BasicValueEnum<'ctx>,
    ) -> IntValue<'ctx> {
        value.into_int_value()
    }
 }
 impl<'ctx> TypedArrayLikeMutator<'ctx, IntValue<'ctx>> for NDArrayShapeProxy<'ctx, '_> {
    fn upcast_from_type(
        &self,
        _: &mut CodeGenContext<'ctx, '_>,
        value: IntValue<'ctx>,
    ) -> BasicValueEnum<'ctx> {
        value.into()
    }
 }
 /// Proxy type for accessing the `data` array of an `NDArray` instance in LLVM.
 #[derive(Copy, Clone)]
 pub struct NDArrayDataProxy<'ctx, 'a>(&'a NDArrayValue<'ctx>);
 impl<'ctx> ArrayLikeValue<'ctx> for NDArrayDataProxy<'ctx, '_> {
    fn element_type<G: CodeGenerator + ?Sized>(
        &self,
        _: &CodeGenContext<'ctx, '_>,
        _: &G,
    ) -> AnyTypeEnum<'ctx> {
        self.0.dtype.as_any_type_enum()
    }
    fn base_ptr<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        _: &G,
    ) -> PointerValue<'ctx> {
        let var_name = self.0.name.map(|v| format!("{v}.data")).unwrap_or_default();
        ctx.builder
            .build_load(self.0.ptr_to_data(ctx), var_name.as_str())
            .map(BasicValueEnum::into_pointer_value)
            .unwrap()
    }
    fn size<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &CodeGenContext<'ctx, '_>,
        generator: &G,
    ) -> IntValue<'ctx> {
        call_ndarray_calc_size(generator, ctx, &self.as_slice_value(ctx, generator), (None, None))
    }
 }
 impl<'ctx> ArrayLikeIndexer<'ctx> for NDArrayDataProxy<'ctx, '_> {
    unsafe fn ptr_offset_unchecked<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &IntValue<'ctx>,
        name: Option<&str>,
    ) -> PointerValue<'ctx> {
        let sizeof_elem = ctx
            .builder
            .build_int_truncate_or_bit_cast(
                self.element_type(ctx, generator).size_of().unwrap(),
                idx.get_type(),
                "",
            )
            .unwrap();
        let idx = ctx.builder.build_int_mul(*idx, sizeof_elem, "").unwrap();
        let ptr = unsafe {
            ctx.builder
                .build_in_bounds_gep(
                    self.base_ptr(ctx, generator),
                    &[idx],
                    name.unwrap_or_default(),
                )
                .unwrap()
        };
        // Current implementation is transparent - The returned pointer type is
        // already cast into the expected type, allowing for immediately
        // load/store.
        ctx.builder
            .build_pointer_cast(
                ptr,
                BasicTypeEnum::try_from(self.element_type(ctx, generator))
                    .unwrap()
                    .ptr_type(AddressSpace::default()),
                "",
            )
            .unwrap()
    }
    fn ptr_offset<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        idx: &IntValue<'ctx>,
        name: Option<&str>,
    ) -> PointerValue<'ctx> {
        let data_sz = self.size(ctx, generator);
        let in_range = ctx.builder.build_int_compare(IntPredicate::ULT, *idx, data_sz, "").unwrap();
        ctx.make_assert(
            generator,
            in_range,
            "0:IndexError",
            "index {0} is out of bounds with size {1}",
            [Some(*idx), Some(self.0.load_ndims(ctx)), None],
            ctx.current_loc,
        );
        let ptr = unsafe { self.ptr_offset_unchecked(ctx, generator, idx, name) };
        // Current implementation is transparent - The returned pointer type is
        // already cast into the expected type, allowing for immediately
        // load/store.
        ctx.builder
            .build_pointer_cast(
                ptr,
                BasicTypeEnum::try_from(self.element_type(ctx, generator))
                    .unwrap()
                    .ptr_type(AddressSpace::default()),
                "",
            )
            .unwrap()
    }
 }
 impl<'ctx> UntypedArrayLikeAccessor<'ctx, IntValue<'ctx>> for NDArrayDataProxy<'ctx, '_> {}
 impl<'ctx> UntypedArrayLikeMutator<'ctx, IntValue<'ctx>> for NDArrayDataProxy<'ctx, '_> {}
 impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
    for NDArrayDataProxy<'ctx, '_>
 {
    unsafe fn ptr_offset_unchecked<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        indices: &Index,
        name: Option<&str>,
    ) -> PointerValue<'ctx> {
        let llvm_usize = generator.get_size_type(ctx.ctx);
        let indices_elem_ty = indices
            .ptr_offset(ctx, generator, &llvm_usize.const_zero(), None)
            .get_type()
            .get_element_type();
        let Ok(indices_elem_ty) = IntType::try_from(indices_elem_ty) else {
            panic!("Expected list[int32] but got {indices_elem_ty}")
        };
        assert_eq!(
            indices_elem_ty.get_bit_width(),
            32,
            "Expected list[int32] but got list[int{}]",
            indices_elem_ty.get_bit_width()
        );
        let index = call_ndarray_flatten_index(generator, ctx, *self.0, indices);
        let sizeof_elem = ctx
            .builder
            .build_int_truncate_or_bit_cast(
                self.element_type(ctx, generator).size_of().unwrap(),
                index.get_type(),
                "",
            )
            .unwrap();
        let index = ctx.builder.build_int_mul(index, sizeof_elem, "").unwrap();
        let ptr = unsafe {
            ctx.builder
                .build_in_bounds_gep(
                    self.base_ptr(ctx, generator),
                    &[index],
                    name.unwrap_or_default(),
                )
                .unwrap()
        };
        // TODO: Current implementation is transparent
        ctx.builder
            .build_pointer_cast(
                ptr,
                BasicTypeEnum::try_from(self.element_type(ctx, generator))
                    .unwrap()
                    .ptr_type(AddressSpace::default()),
                "",
            )
            .unwrap()
    }
    fn ptr_offset<G: CodeGenerator + ?Sized>(
        &self,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut G,
        indices: &Index,
        name: Option<&str>,
    ) -> PointerValue<'ctx> {
        let llvm_usize = generator.get_size_type(ctx.ctx);
        let indices_size = indices.size(ctx, generator);
        let nidx_leq_ndims = ctx
            .builder
            .build_int_compare(IntPredicate::SLE, indices_size, self.0.load_ndims(ctx), "")
            .unwrap();
        ctx.make_assert(
            generator,
            nidx_leq_ndims,
            "0:IndexError",
            "invalid index to scalar variable",
            [None, None, None],
            ctx.current_loc,
        );
        let indices_len = indices.size(ctx, generator);
        let ndarray_len = self.0.load_ndims(ctx);
        let len = call_int_umin(ctx, indices_len, ndarray_len, None);
        gen_for_callback_incrementing(
            generator,
            ctx,
            None,
            llvm_usize.const_zero(),
            (len, false),
            |generator, ctx, _, i| {
                let (dim_idx, dim_sz) = unsafe {
                    (
                        indices.get_unchecked(ctx, generator, &i, None).into_int_value(),
                        self.0.shape().get_typed_unchecked(ctx, generator, &i, None),
                    )
                };
                let dim_idx = ctx
                    .builder
                    .build_int_z_extend_or_bit_cast(dim_idx, dim_sz.get_type(), "")
                    .unwrap();
                let dim_lt =
                    ctx.builder.build_int_compare(IntPredicate::SLT, dim_idx, dim_sz, "").unwrap();
                ctx.make_assert(
                    generator,
                    dim_lt,
                    "0:IndexError",
                    "index {0} is out of bounds for axis 0 with size {1}",
                    [Some(dim_idx), Some(dim_sz), None],
                    ctx.current_loc,
                );
                Ok(())
            },
            llvm_usize.const_int(1, false),
        )
        .unwrap();
        let ptr = unsafe { self.ptr_offset_unchecked(ctx, generator, indices, name) };
        // TODO: Current implementation is transparent
        ctx.builder
            .build_pointer_cast(
                ptr,
                BasicTypeEnum::try_from(self.element_type(ctx, generator))
                    .unwrap()
                    .ptr_type(AddressSpace::default()),
                "",
            )
            .unwrap()
    }
 }
 impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> UntypedArrayLikeAccessor<'ctx, Index>
    for NDArrayDataProxy<'ctx, '_>
 {
 }
 impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> UntypedArrayLikeMutator<'ctx, Index>
    for NDArrayDataProxy<'ctx, '_>
 {
 }
--- a/nac3core/src/codegen/values/range.rs
+++ b/nac3core/src/codegen/values/range.rs
@ -0,0 +1,153 @@
 use inkwell::values::{BasicValueEnum, IntValue, PointerValue};
 use super::ProxyValue;
 use crate::codegen::{types::RangeType, CodeGenContext};
 /// Proxy type for accessing a `range` value in LLVM.
 #[derive(Copy, Clone)]
 pub struct RangeValue<'ctx> {
    value: PointerValue<'ctx>,
    name: Option<&'ctx str>,
 }
 impl<'ctx> RangeValue<'ctx> {
    /// Checks whether `value` is an instance of `range`, returning [Err] if `value` is not an instance.
    pub fn is_representable(value: PointerValue<'ctx>) -> Result<(), String> {
        RangeType::is_representable(value.get_type())
    }
    /// Creates an [`RangeValue`] from a [`PointerValue`].
    #[must_use]
    pub fn from_pointer_value(ptr: PointerValue<'ctx>, name: Option<&'ctx str>) -> Self {
        debug_assert!(Self::is_representable(ptr).is_ok());
        RangeValue { value: ptr, name }
    }
    fn ptr_to_start(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
        let llvm_i32 = ctx.ctx.i32_type();
        let var_name = self.name.map(|v| format!("{v}.start.addr")).unwrap_or_default();
        unsafe {
            ctx.builder
                .build_in_bounds_gep(
                    self.as_base_value(),
                    &[llvm_i32.const_zero(), llvm_i32.const_int(0, false)],
                    var_name.as_str(),
                )
                .unwrap()
        }
    }
    fn ptr_to_end(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
        let llvm_i32 = ctx.ctx.i32_type();
        let var_name = self.name.map(|v| format!("{v}.end.addr")).unwrap_or_default();
        unsafe {
            ctx.builder
                .build_in_bounds_gep(
                    self.as_base_value(),
                    &[llvm_i32.const_zero(), llvm_i32.const_int(1, false)],
                    var_name.as_str(),
                )
                .unwrap()
        }
    }
    fn ptr_to_step(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
        let llvm_i32 = ctx.ctx.i32_type();
        let var_name = self.name.map(|v| format!("{v}.step.addr")).unwrap_or_default();
        unsafe {
            ctx.builder
                .build_in_bounds_gep(
                    self.as_base_value(),
                    &[llvm_i32.const_zero(), llvm_i32.const_int(2, false)],
                    var_name.as_str(),
                )
                .unwrap()
        }
    }
    /// Stores the `start` value into this instance.
    pub fn store_start(&self, ctx: &CodeGenContext<'ctx, '_>, start: IntValue<'ctx>) {
        debug_assert_eq!(start.get_type().get_bit_width(), 32);
        let pstart = self.ptr_to_start(ctx);
        ctx.builder.build_store(pstart, start).unwrap();
    }
    /// Returns the `start` value of this `range`.
    pub fn load_start(&self, ctx: &CodeGenContext<'ctx, '_>, name: Option<&str>) -> IntValue<'ctx> {
        let pstart = self.ptr_to_start(ctx);
        let var_name = name
            .map(ToString::to_string)
            .or_else(|| self.name.map(|v| format!("{v}.start")))
            .unwrap_or_default();
        ctx.builder
            .build_load(pstart, var_name.as_str())
            .map(BasicValueEnum::into_int_value)
            .unwrap()
    }
    /// Stores the `end` value into this instance.
    pub fn store_end(&self, ctx: &CodeGenContext<'ctx, '_>, end: IntValue<'ctx>) {
        debug_assert_eq!(end.get_type().get_bit_width(), 32);
        let pend = self.ptr_to_end(ctx);
        ctx.builder.build_store(pend, end).unwrap();
    }
    /// Returns the `end` value of this `range`.
    pub fn load_end(&self, ctx: &CodeGenContext<'ctx, '_>, name: Option<&str>) -> IntValue<'ctx> {
        let pend = self.ptr_to_end(ctx);
        let var_name = name
            .map(ToString::to_string)
            .or_else(|| self.name.map(|v| format!("{v}.end")))
            .unwrap_or_default();
        ctx.builder.build_load(pend, var_name.as_str()).map(BasicValueEnum::into_int_value).unwrap()
    }
    /// Stores the `step` value into this instance.
    pub fn store_step(&self, ctx: &CodeGenContext<'ctx, '_>, step: IntValue<'ctx>) {
        debug_assert_eq!(step.get_type().get_bit_width(), 32);
        let pstep = self.ptr_to_step(ctx);
        ctx.builder.build_store(pstep, step).unwrap();
    }
    /// Returns the `step` value of this `range`.
    pub fn load_step(&self, ctx: &CodeGenContext<'ctx, '_>, name: Option<&str>) -> IntValue<'ctx> {
        let pstep = self.ptr_to_step(ctx);
        let var_name = name
            .map(ToString::to_string)
            .or_else(|| self.name.map(|v| format!("{v}.step")))
            .unwrap_or_default();
        ctx.builder
            .build_load(pstep, var_name.as_str())
            .map(BasicValueEnum::into_int_value)
            .unwrap()
    }
 }
 impl<'ctx> ProxyValue<'ctx> for RangeValue<'ctx> {
    type Base = PointerValue<'ctx>;
    type Type = RangeType<'ctx>;
    fn get_type(&self) -> Self::Type {
        RangeType::from_type(self.value.get_type())
    }
    fn as_base_value(&self) -> Self::Base {
        self.value
    }
 }
 impl<'ctx> From<RangeValue<'ctx>> for PointerValue<'ctx> {
    fn from(value: RangeValue<'ctx>) -> Self {
        value.as_base_value()
    }
 }
--- a/nac3core/src/lib.rs
+++ b/nac3core/src/lib.rs
@ -1,10 +1,4 @@
-#![deny(
+#![deny(future_incompatible, let_underscore, nonstandard_style, clippy::all)]
    future_incompatible,
    let_underscore,
    nonstandard_style,
    rust_2024_compatibility,
    clippy::all
 )]
 #![warn(clippy::pedantic)]
 #![allow(
    dead_code,
@ -19,7 +13,13 @@
    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;
 pub mod typecheck;
 extern crate self as nac3core;
--- a/nac3core/src/symbol_resolver.rs
+++ b/nac3core/src/symbol_resolver.rs
@ -1,7 +1,15 @@
-use std::fmt::Debug;
+use std::{
-use std::rc::Rc;
+    collections::{HashMap, HashSet},
-use std::sync::Arc;
+    fmt::{Debug, Display},
-use std::{collections::HashMap, collections::HashSet, fmt::Display};
+    rc::Rc,
    sync::Arc,
 };
 use inkwell::values::{BasicValueEnum, FloatValue, IntValue, PointerValue, StructValue};
 use itertools::{chain, izip, Itertools};
 use parking_lot::RwLock;
 use nac3parser::ast::{Constant, Expr, Location, StrRef};
 use crate::{
    codegen::{CodeGenContext, CodeGenerator},
@ -11,10 +19,6 @@ 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 {
@ -365,6 +369,7 @@ pub trait SymbolResolver {
        &self,
        str: StrRef,
        ctx: &mut CodeGenContext<'ctx, '_>,
        generator: &mut dyn CodeGenerator,
    ) -> Option<ValueEnum<'ctx>>;
    fn get_default_param_value(&self, expr: &Expr) -> Option<SymbolValue>;
--- a/nac3core/src/toplevel/builtins.rs
+++ b/nac3core/src/toplevel/builtins.rs
@ -1,6 +1,5 @@
 use std::iter::once;
 use helper::{debug_assert_prim_is_allowed, extract_ndims, make_exception_fields, PrimDefDetails};
 use indexmap::IndexMap;
 use inkwell::{
    attributes::{Attribute, AttributeLoc},
@ -9,28 +8,24 @@ use inkwell::{
    IntPredicate,
 };
 use itertools::Either;
 use numpy::unpack_ndarray_var_tys;
 use strum::IntoEnumIterator;
 use super::{
    helper::{debug_assert_prim_is_allowed, make_exception_fields, PrimDef, PrimDefDetails},
    numpy::make_ndarray_ty,
    *,
 };
 use crate::{
    codegen::{
        builtin_fns,
        classes::{ProxyValue, RangeValue},
        model::*,
        numpy::*,
        object::{
            any::AnyObject,
            ndarray::{shape_util::parse_numpy_int_sequence, NDArrayObject},
        },
        stmt::exn_constructor,
        values::{ProxyValue, RangeValue},
    },
    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(
@ -517,14 +512,6 @@ impl<'a> BuiltinBuilder<'a> {
            | PrimDef::FunNpEye
            | PrimDef::FunNpIdentity => self.build_ndarray_other_factory_function(prim),
            PrimDef::FunNpSize | PrimDef::FunNpShape | PrimDef::FunNpStrides => {
                self.build_ndarray_property_getter_function(prim)
            }
            PrimDef::FunNpBroadcastTo | PrimDef::FunNpTranspose | PrimDef::FunNpReshape => {
                self.build_ndarray_view_function(prim)
            }
            PrimDef::FunStr => self.build_str_function(),
            PrimDef::FunFloor | PrimDef::FunFloor64 | PrimDef::FunCeil | PrimDef::FunCeil64 => {
@ -590,6 +577,10 @@ impl<'a> BuiltinBuilder<'a> {
            | PrimDef::FunNpHypot
            | PrimDef::FunNpNextAfter => self.build_np_2ary_function(prim),
            PrimDef::FunNpTranspose | PrimDef::FunNpReshape => {
                self.build_np_sp_ndarray_function(prim)
            }
            PrimDef::FunNpDot
            | PrimDef::FunNpLinalgCholesky
            | PrimDef::FunNpLinalgQr
@ -719,7 +710,7 @@ impl<'a> BuiltinBuilder<'a> {
                        let (zelf_ty, zelf) = obj.unwrap();
                        let zelf =
                            zelf.to_basic_value_enum(ctx, generator, zelf_ty)?.into_pointer_value();
-                        let zelf = RangeValue::from_ptr_val(zelf, Some("range"));
+                        let zelf = RangeValue::from_pointer_value(zelf, Some("range"));
                        let mut start = None;
                        let mut stop = None;
@ -1395,171 +1386,6 @@ impl<'a> BuiltinBuilder<'a> {
        }
    }
    fn build_ndarray_property_getter_function(&mut self, prim: PrimDef) -> TopLevelDef {
        debug_assert_prim_is_allowed(
            prim,
            &[PrimDef::FunNpSize, PrimDef::FunNpShape, PrimDef::FunNpStrides],
        );
        let in_ndarray_ty = self.unifier.get_fresh_var_with_range(
            &[self.primitives.ndarray],
            Some("T".into()),
            None,
        );
        match prim {
            PrimDef::FunNpSize => create_fn_by_codegen(
                self.unifier,
                &into_var_map([in_ndarray_ty]),
                prim.name(),
                self.primitives.int32,
                &[(in_ndarray_ty.ty, "a")],
                Box::new(|ctx, obj, fun, args, generator| {
                    assert!(obj.is_none());
                    assert_eq!(args.len(), 1);
                    let ndarray_ty = fun.0.args[0].ty;
                    let ndarray =
                        args[0].1.clone().to_basic_value_enum(ctx, generator, ndarray_ty)?;
                    let ndarray = AnyObject { ty: ndarray_ty, value: ndarray };
                    let ndarray = NDArrayObject::from_object(generator, ctx, ndarray);
                    let size =
                        ndarray.size(generator, ctx).truncate_or_bit_cast(generator, ctx, Int32);
                    Ok(Some(size.value.as_basic_value_enum()))
                }),
            ),
            PrimDef::FunNpShape | PrimDef::FunNpStrides => {
                // The function signatures of `np_shape` an `np_size` are the same.
                // Mixed together for convenience.
                // The return type is a tuple of variable length depending on the ndims of the input ndarray.
                let ret_ty = self.unifier.get_dummy_var().ty; // Handled by special folding
                create_fn_by_codegen(
                    self.unifier,
                    &into_var_map([in_ndarray_ty]),
                    prim.name(),
                    ret_ty,
                    &[(in_ndarray_ty.ty, "a")],
                    Box::new(move |ctx, obj, fun, args, generator| {
                        assert!(obj.is_none());
                        assert_eq!(args.len(), 1);
                        let ndarray_ty = fun.0.args[0].ty;
                        let ndarray =
                            args[0].1.clone().to_basic_value_enum(ctx, generator, ndarray_ty)?;
                        let ndarray = AnyObject { ty: ndarray_ty, value: ndarray };
                        let ndarray = NDArrayObject::from_object(generator, ctx, ndarray);
                        let result_tuple = match prim {
                            PrimDef::FunNpShape => ndarray.make_shape_tuple(generator, ctx),
                            PrimDef::FunNpStrides => ndarray.make_strides_tuple(generator, ctx),
                            _ => unreachable!(),
                        };
                        Ok(Some(result_tuple.value.as_basic_value_enum()))
                    }),
                )
            }
            _ => unreachable!(),
        }
    }
    /// Build np/sp functions that take as input `NDArray` only
    fn build_ndarray_view_function(&mut self, prim: PrimDef) -> TopLevelDef {
        debug_assert_prim_is_allowed(
            prim,
            &[PrimDef::FunNpBroadcastTo, PrimDef::FunNpTranspose, PrimDef::FunNpReshape],
        );
        let in_ndarray_ty = self.unifier.get_fresh_var_with_range(
            &[self.primitives.ndarray],
            Some("T".into()),
            None,
        );
        match prim {
            PrimDef::FunNpTranspose => {
                create_fn_by_codegen(
                    self.unifier,
                    &into_var_map([in_ndarray_ty]),
                    prim.name(),
                    in_ndarray_ty.ty,
                    &[(in_ndarray_ty.ty, "x")],
                    Box::new(move |ctx, _, fun, args, generator| {
                        let arg_ty = fun.0.args[0].ty;
                        let arg_val =
                            args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
                        let arg = AnyObject { ty: arg_ty, value: arg_val };
                        let ndarray = NDArrayObject::from_object(generator, ctx, arg);
                        let ndarray = ndarray.transpose(generator, ctx, None); // TODO: Add axes argument
                        Ok(Some(ndarray.instance.value.as_basic_value_enum()))
                    }),
                )
            }
            // NOTE: on `ndarray_factory_fn_shape_arg_tvar` and
            // the `param_ty` for `create_fn_by_codegen`.
            //
            // Similar to `build_ndarray_from_shape_factory_function` we delegate the responsibility of typechecking
            // to [`typecheck::type_inferencer::Inferencer::fold_numpy_function_call_shape_argument`],
            // and use a dummy [`TypeVar`] `ndarray_factory_fn_shape_arg_tvar` as a placeholder for `param_ty`.
            PrimDef::FunNpBroadcastTo | PrimDef::FunNpReshape => {
                // These two functions have the same function signature.
                // Mixed together for convenience.
                let ret_ty = self.unifier.get_dummy_var().ty; // Handled by special holding
                create_fn_by_codegen(
                    self.unifier,
                    &VarMap::new(),
                    prim.name(),
                    ret_ty,
                    &[
                        (in_ndarray_ty.ty, "x"),
                        (self.ndarray_factory_fn_shape_arg_tvar.ty, "shape"), // Handled by special folding
                    ],
                    Box::new(move |ctx, _, fun, args, generator| {
                        let ndarray_ty = fun.0.args[0].ty;
                        let ndarray_val =
                            args[0].1.clone().to_basic_value_enum(ctx, generator, ndarray_ty)?;
                        let shape_ty = fun.0.args[1].ty;
                        let shape_val =
                            args[1].1.clone().to_basic_value_enum(ctx, generator, shape_ty)?;
                        let ndarray = AnyObject { value: ndarray_val, ty: ndarray_ty };
                        let ndarray = NDArrayObject::from_object(generator, ctx, ndarray);
                        let shape = AnyObject { value: shape_val, ty: shape_ty };
                        let (_, shape) = parse_numpy_int_sequence(generator, ctx, shape);
                        // The ndims after reshaping is gotten from the return type of the call.
                        let (_, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, fun.0.ret);
                        let ndims = extract_ndims(&ctx.unifier, ndims);
                        let new_ndarray = match prim {
                            PrimDef::FunNpBroadcastTo => {
                                ndarray.broadcast_to(generator, ctx, ndims, shape)
                            }
                            PrimDef::FunNpReshape => {
                                ndarray.reshape_or_copy(generator, ctx, ndims, shape)
                            }
                            _ => unreachable!(),
                        };
                        Ok(Some(new_ndarray.instance.value.as_basic_value_enum()))
                    }),
                )
            }
            _ => unreachable!(),
        }
    }
    /// Build the `str()` function.
    fn build_str_function(&mut self) -> TopLevelDef {
        let prim = PrimDef::FunStr;
@ -2047,6 +1873,57 @@ 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`
--- a/nac3core/src/toplevel/composer.rs
+++ b/nac3core/src/toplevel/composer.rs
--- a/nac3core/src/toplevel/helper.rs
+++ b/nac3core/src/toplevel/helper.rs
@ -1,14 +1,15 @@
 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 ast::ExprKind;
 use nac3parser::ast::{Constant, Location};
 use strum::IntoEnumIterator;
 use strum_macros::EnumIter;
-use super::*;
+use nac3parser::ast::{Constant, ExprKind, Location};
 use super::{numpy::unpack_ndarray_var_tys, *};
 use crate::{
    symbol_resolver::SymbolValue,
    typecheck::typedef::{into_var_map, iter_type_vars, Mapping, TypeVarId, VarMap},
 };
 /// All primitive types and functions in nac3core.
 #[derive(Clone, Copy, Debug, EnumIter, PartialEq, Eq)]
@ -53,16 +54,6 @@ pub enum PrimDef {
    FunNpEye,
    FunNpIdentity,
    // NumPy ndarray property getters
    FunNpSize,
    FunNpShape,
    FunNpStrides,
    // NumPy ndarray view functions
    FunNpBroadcastTo,
    FunNpTranspose,
    FunNpReshape,
    // Miscellaneous NumPy & SciPy functions
    FunNpRound,
    FunNpFloor,
@ -110,6 +101,8 @@ pub enum PrimDef {
    FunNpLdExp,
    FunNpHypot,
    FunNpNextAfter,
    FunNpTranspose,
    FunNpReshape,
    // Linalg functions
    FunNpDot,
@ -247,16 +240,6 @@ impl PrimDef {
            PrimDef::FunNpEye => fun("np_eye", None),
            PrimDef::FunNpIdentity => fun("np_identity", None),
            // NumPy NDArray property getters,
            PrimDef::FunNpSize => fun("np_size", None),
            PrimDef::FunNpShape => fun("np_shape", None),
            PrimDef::FunNpStrides => fun("np_strides", None),
            // NumPy NDArray view functions
            PrimDef::FunNpBroadcastTo => fun("np_broadcast_to", None),
            PrimDef::FunNpTranspose => fun("np_transpose", None),
            PrimDef::FunNpReshape => fun("np_reshape", None),
            // Miscellaneous NumPy & SciPy functions
            PrimDef::FunNpRound => fun("np_round", None),
            PrimDef::FunNpFloor => fun("np_floor", None),
@ -304,6 +287,8 @@ 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),
@ -404,6 +389,9 @@ impl TopLevelDef {
                    r
                }
            ),
            TopLevelDef::Variable { name, ty, .. } => {
                format!("Variable {{ name: {name:?}, ty: {:?} }}", unifier.stringify(*ty),)
            }
        }
    }
 }
@ -605,6 +593,18 @@ 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('.');
@ -624,64 +624,6 @@ impl TopLevelComposer {
        Err(HashSet::from([format!("no method {method_name} in the current class")]))
    }
    /// get all base class def id of a class, excluding itself. \
    /// this function should called only after the direct parent is set
    /// and before all the ancestors are set
    /// and when we allow single inheritance \
    /// the order of the returned list is from the child to the deepest ancestor
    pub fn get_all_ancestors_helper(
        child: &TypeAnnotation,
        temp_def_list: &[Arc<RwLock<TopLevelDef>>],
    ) -> Result<Vec<TypeAnnotation>, HashSet<String>> {
        let mut result: Vec<TypeAnnotation> = Vec::new();
        let mut parent = Self::get_parent(child, temp_def_list);
        while let Some(p) = parent {
            parent = Self::get_parent(&p, temp_def_list);
            let p_id = if let TypeAnnotation::CustomClass { id, .. } = &p {
                *id
            } else {
                unreachable!("must be class kind annotation")
            };
            // check cycle
            let no_cycle = result.iter().all(|x| {
                let TypeAnnotation::CustomClass { id, .. } = x else {
                    unreachable!("must be class kind annotation")
                };
                id.0 != p_id.0
            });
            if no_cycle {
                result.push(p);
            } else {
                return Err(HashSet::from(["cyclic inheritance detected".into()]));
            }
        }
        Ok(result)
    }
    /// should only be called when finding all ancestors, so panic when wrong
    fn get_parent(
        child: &TypeAnnotation,
        temp_def_list: &[Arc<RwLock<TopLevelDef>>],
    ) -> Option<TypeAnnotation> {
        let child_id = if let TypeAnnotation::CustomClass { id, .. } = child {
            *id
        } else {
            unreachable!("should be class type annotation")
        };
        let child_def = temp_def_list.get(child_id.0).unwrap();
        let child_def = child_def.read();
        let TopLevelDef::Class { ancestors, .. } = &*child_def else {
            unreachable!("child must be top level class def")
        };
        if ancestors.is_empty() {
            None
        } else {
            Some(ancestors[0].clone())
        }
    }
    /// get the `var_id` of a given `TVar` type
    pub fn get_var_id(var_ty: Type, unifier: &mut Unifier) -> Result<TypeVarId, HashSet<String>> {
        if let TypeEnum::TVar { id, .. } = unifier.get_ty(var_ty).as_ref() {
@ -991,6 +933,139 @@ impl TopLevelComposer {
            ))
        }
    }
    /// Parses the class type variables and direct parents
    /// we only allow single inheritance
    pub fn analyze_class_bases(
        class_def: &Arc<RwLock<TopLevelDef>>,
        class_ast: &Option<Stmt>,
        temp_def_list: &[Arc<RwLock<TopLevelDef>>],
        unifier: &mut Unifier,
        primitives_store: &PrimitiveStore,
    ) -> Result<(), HashSet<String>> {
        let mut class_def = class_def.write();
        let (class_def_id, class_ancestors, class_bases_ast, class_type_vars, class_resolver) = {
            let TopLevelDef::Class { object_id, ancestors, type_vars, resolver, .. } =
                &mut *class_def
            else {
                unreachable!()
            };
            let Some(ast::Located { node: ast::StmtKind::ClassDef { bases, .. }, .. }) = class_ast
            else {
                unreachable!()
            };
            (object_id, ancestors, bases, type_vars, resolver.as_ref().unwrap().as_ref())
        };
        let mut is_generic = false;
        let mut has_base = false;
        // Check class bases for typevars
        for b in class_bases_ast {
            match &b.node {
                // analyze typevars bounded to the class,
                // only support things like `class A(Generic[T, V])`,
                // things like `class A(Generic[T, V, ImportedModule.T])` is not supported
                // i.e. only simple names are allowed in the subscript
                // should update the TopLevelDef::Class.typevars and the TypeEnum::TObj.params
                ast::ExprKind::Subscript { value, slice, .. } if matches!(&value.node, ast::ExprKind::Name { id, .. } if id == &"Generic".into()) =>
                {
                    if is_generic {
                        return Err(HashSet::from([format!(
                            "only single Generic[...] is allowed (at {})",
                            b.location
                        )]));
                    }
                    is_generic = true;
                    let type_var_list: Vec<&ast::Expr<()>>;
                    // if `class A(Generic[T, V, G])`
                    if let ast::ExprKind::Tuple { elts, .. } = &slice.node {
                        type_var_list = elts.iter().collect_vec();
                    // `class A(Generic[T])`
                    } else {
                        type_var_list = vec![&**slice];
                    }
                    let type_vars = type_var_list
                        .into_iter()
                        .map(|e| {
                            class_resolver.parse_type_annotation(
                                temp_def_list,
                                unifier,
                                primitives_store,
                                e,
                            )
                        })
                        .collect::<Result<Vec<_>, _>>()?;
                    class_type_vars.extend(type_vars);
                }
                ast::ExprKind::Name { .. } | ast::ExprKind::Subscript { .. } => {
                    if has_base {
                        return Err(HashSet::from([format!("a class definition can only have at most one base class declaration and one generic declaration (at {})", b.location )]));
                    }
                    has_base = true;
                    // the function parse_ast_to make sure that no type var occurred in
                    // bast_ty if it is a CustomClassKind
                    let base_ty = parse_ast_to_type_annotation_kinds(
                        class_resolver,
                        temp_def_list,
                        unifier,
                        primitives_store,
                        b,
                        vec![(*class_def_id, class_type_vars.clone())]
                            .into_iter()
                            .collect::<HashMap<_, _>>(),
                    )?;
                    if let TypeAnnotation::CustomClass { .. } = &base_ty {
                        class_ancestors.push(base_ty);
                    } else {
                        return Err(HashSet::from([format!(
                            "class base declaration can only be custom class (at {})",
                            b.location
                        )]));
                    }
                }
                _ => {
                    return Err(HashSet::from([format!(
                        "unsupported statement in class defintion (at {})",
                        b.location
                    )]));
                }
            }
        }
        Ok(())
    }
    /// gets all ancestors of a class
    pub fn analyze_class_ancestors(
        class_def: &Arc<RwLock<TopLevelDef>>,
        temp_def_list: &[Arc<RwLock<TopLevelDef>>],
    ) {
        // Check if class has a direct parent
        let mut class_def = class_def.write();
        let TopLevelDef::Class { ancestors, type_vars, object_id, .. } = &mut *class_def else {
            unreachable!()
        };
        let mut anc_set = HashMap::new();
        if let Some(ancestor) = ancestors.first() {
            let TypeAnnotation::CustomClass { id, .. } = ancestor else { unreachable!() };
            let TopLevelDef::Class { ancestors: parent_ancestors, .. } =
                &*temp_def_list[id.0].read()
            else {
                unreachable!()
            };
            for anc in parent_ancestors.iter().skip(1) {
                let TypeAnnotation::CustomClass { id, .. } = anc else { unreachable!() };
                anc_set.insert(id, anc.clone());
            }
            ancestors.extend(anc_set.into_values());
        }
        // push `self` as first ancestor of class
        ancestors.insert(0, make_self_type_annotation(type_vars.as_slice(), *object_id));
    }
 }
 pub fn parse_parameter_default_value(
--- a/nac3core/src/toplevel/mod.rs
+++ b/nac3core/src/toplevel/mod.rs
@ -6,36 +6,36 @@ use std::{
    sync::Arc,
 };
 use super::codegen::CodeGenContext;
 use super::typecheck::type_inferencer::PrimitiveStore;
 use super::typecheck::typedef::{
    FunSignature, FuncArg, SharedUnifier, Type, TypeEnum, Unifier, VarMap,
 };
 use crate::{
    codegen::CodeGenerator,
    symbol_resolver::{SymbolResolver, ValueEnum},
    typecheck::{
        type_inferencer::CodeLocation,
        typedef::{CallId, TypeVarId},
    },
 };
 use inkwell::values::BasicValueEnum;
 use itertools::Itertools;
 use nac3parser::ast::{self, Location, Stmt, StrRef};
 use parking_lot::RwLock;
-#[derive(PartialEq, Eq, PartialOrd, Ord, Clone, Copy, Hash, Debug)]
+use nac3parser::ast::{self, Expr, Location, Stmt, StrRef};
-pub struct DefinitionId(pub usize);
+
 use crate::{
    codegen::{CodeGenContext, CodeGenerator},
    symbol_resolver::{SymbolResolver, ValueEnum},
    typecheck::{
        type_inferencer::{CodeLocation, PrimitiveStore},
        typedef::{
            CallId, FunSignature, FuncArg, SharedUnifier, Type, TypeEnum, TypeVarId, Unifier,
            VarMap,
        },
    },
 };
 use composer::*;
 use type_annotation::*;
 pub mod builtins;
 pub mod composer;
 pub mod helper;
 pub mod numpy;
 pub mod type_annotation;
 use composer::*;
 use type_annotation::*;
 #[cfg(test)]
 mod test;
 pub mod type_annotation;
 #[derive(PartialEq, Eq, PartialOrd, Ord, Clone, Copy, Hash, Debug)]
 pub struct DefinitionId(pub usize);
 type GenCallCallback = dyn for<'ctx, 'a> Fn(
        &mut CodeGenContext<'ctx, 'a>,
@ -148,6 +148,25 @@ pub enum TopLevelDef {
        /// Definition location.
        loc: Option<Location>,
    },
    Variable {
        /// Qualified name of the global variable, should be unique globally.
        name: String,
        /// Simple name, the same as in method/function definition.
        simple_name: StrRef,
        /// Type of the global variable.
        ty: Type,
        /// The declared type of the global variable, or [`None`] if no type annotation is provided.
        ty_decl: Option<Expr>,
        /// Symbol resolver of the module defined the class.
        resolver: Option<Arc<dyn SymbolResolver + Send + Sync>>,
        /// Definition location.
        loc: Option<Location>,
    },
 }
 pub struct TopLevelContext {
--- a/nac3core/src/toplevel/numpy.rs
+++ b/nac3core/src/toplevel/numpy.rs
@ -1,11 +1,10 @@
-use crate::{
+use itertools::Itertools;
-    toplevel::helper::PrimDef,
+
-    typecheck::{
+use super::helper::PrimDef;
 use crate::typecheck::{
    type_inferencer::PrimitiveStore,
    typedef::{Type, TypeEnum, TypeVarId, Unifier, VarMap},
    },
 };
 use itertools::Itertools;
 /// Creates a `ndarray` [`Type`] with the given type arguments.
 ///
--- a/nac3core/src/toplevel/snapshots/nac3coretopleveltest__test_analyze__generic_class.snap
+++ b/nac3core/src/toplevel/snapshots/nac3coretopleveltest__test_analyze__generic_class.snap
@ -3,10 +3,10 @@ source: nac3core/src/toplevel/test.rs
 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",
    "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",
    "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(246)]\n}\n",
 ]
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
David Mak	01edd5af67	[meta] Apply rustfmt changes	2024-11-29 15:43:34 +08:00
occheung	015714eee1	copy constructor -> clone	2024-11-28 18:52:53 +08:00
occheung	71dec251e3	ld/dwarf: remove reader resets DWARF reader never had to reverse. Readers are already copied to achieve this effect. Plus the position that it reverses to might be questionable.	2024-11-28 18:52:53 +08:00
occheung	fce61f7b8c	ld: fix dwarf sections offset calculations	2024-11-28 18:52:53 +08:00
abdul124	babc081dbd	core/toplevel: update tests	2024-11-27 14:31:57 +08:00
abdul124	5337dbe23b	core/toplevel: add python-like error messages for class definition	2024-11-27 14:31:57 +08:00
abdul124	f862c01412	core/toplevel: refactor composer	2024-11-27 14:31:53 +08:00
David Mak	0c9705f5f1	[meta] Apply clippy changes	2024-11-25 16:05:12 +08:00
David Mak	5f940f86d9	[artiq] Fix obtaining ndarray struct from NDArrayType	2024-11-25 15:01:39 +08:00
Sebastien Bourdeauducq	5651e00688	flake: add platformdirs artiq dependency	2024-11-22 20:30:30 +08:00
Sebastien Bourdeauducq	f6745b987f	bump sipyco and artiq used for profiling	2024-11-22 19:43:03 +08:00
mwojcik	e0dedc6580	nac3artiq: support kernels sent by content	2024-11-22 19:38:52 +08:00
David Mak	28f574282c	[core_derive] Ignore doctest in example Causes linker errors for unknown reasons.	2024-11-22 00:00:05 +08:00
David Mak	144f0922db	[core] coregen/types: Implement StructFields for NDArray Also rename some fields to better align with their naming in numpy.	2024-11-21 14:27:00 +08:00
David Mak	c58ce9c3a9	[core] codegen/types: Implement NDArray in terms of i8* Better aligns with the future implementation of ndstrides.	2024-11-21 14:27:00 +08:00
David Mak	f7e296da53	[core] irrt: Break IRRT into several impl files Each IRRT file is now mapped to one Rust file.	2024-11-21 14:27:00 +08:00
David Mak	b58c99369e	[core] irrt: Update some IRRT implementation - Change CSlice to use `void` for better pointer compatibility - Only include impl .hpp files in irrt.cpp - Refactor typedef to using declaration - Add missing ``// namespace`	2024-11-21 14:26:58 +08:00
David Mak	1a535db558	[core] codegen: Add dtype to NDArrayType We won't have this once NDArray is refactored to strided impl.	2024-11-20 15:35:57 +08:00
David Mak	1ba2e287a6	[core] codegen: Add Self::llvm_type to all type abstractions	2024-11-20 15:35:57 +08:00
lyken	f95f979ad3	core/irrt: fix exception.hpp C++ castings	2024-11-20 15:35:57 +08:00
lyken	48e2148c0f	core/toplevel/helper: add {extract,create}_ndims	2024-11-20 15:35:57 +08:00
David Mak	88e57f7120	[core_derive] Initial implementation	2024-11-20 15:35:55 +08:00
David Mak	d7633c42bc	[core] codegen/types: Implement StructField{,s} Loosely based on FieldTraversal by lyken.	2024-11-19 13:46:25 +08:00
David Mak	a4f53b6e6b	[core] codegen: Refactor ProxyType and ProxyValue Accepts generator+context object for generic type checking. Also implements more default trait impl for easier delegation.	2024-11-19 13:46:25 +08:00
David Mak	9d9ead211e	[core] Move Proxies to their own modules	2024-11-19 13:46:23 +08:00
David Mak	26a1b85206	[core] codegen/classes: Remove Underlying type This is confusing and we want a better abstraction than this.	2024-11-19 13:45:55 +08:00
David Mak	2822074b2d	[meta] Cleanup from upgrading Rust version - Remove rust_2024_edition warnings, since it wouldn't be released for another 3 months - Fix new clippy warnings	2024-11-19 13:43:57 +08:00
David Mak	fe67ed076c	[meta] Update pre-commit configuration	2024-11-19 13:20:27 +08:00
David Mak	94e2414df0	[meta] Update cargo dependencies	2024-11-19 13:20:26 +08:00
Sebastien Bourdeauducq	2cee760404	turn rust_2024_compatibility lints into warnings	2024-11-16 13:41:49 +08:00
Sebastien Bourdeauducq	230982dc84	update dependencies	2024-11-16 12:40:11 +08:00
occheung	2bd3f63991	boolop: terminate both branches with *_end_bb	2024-11-16 12:06:20 +08:00
occheung	b53266e9e6	artiq: use async RPC for attributes writeback	2024-11-12 12:04:01 +08:00
occheung	86eb22bbf3	artiq: main is always the last module	2024-11-12 12:03:38 +08:00
occheung	beaa38047d	artiq: suppress main module debug warning	2024-11-12 12:03:08 +08:00
occheung	705dc4ff1c	artiq: lump return value into attributes writeback RPC	2024-11-12 12:02:35 +08:00
occheung	979209a526	binop: expand `not` operator as loglcal not	2024-11-08 17:12:01 +08:00
David Mak	c3927d0ef6	[ast] Refactor lazy_static to LazyLock It is available in Rust 1.80 and reduces a dependency.	2024-10-30 12:29:51 +08:00
David Mak	202a902cd0	[meta] Update dependencies	2024-10-30 12:29:51 +08:00
David Mak	b6e2644391	[meta] Update cargo dependencies	2024-10-18 14:17:16 +08:00
David Mak	45cd01556b	[meta] Apply cargo fmt	2024-10-18 14:16:42 +08:00
David Mak	b6cd2a6993	[meta] Reorganize order of use declarations - Phase 3	2024-10-17 16:25:52 +08:00
David Mak	a98f33e6d1	[meta] Reorganize order of use declarations - Phase 2 Some more rules: - For module-level imports, prefer no prefix > super > crate. - Use crate instead of super if super refers to the crate-level module	2024-10-17 15:57:33 +08:00
David Mak	5839badadd	[standalone] Update globals.py with type-inferred global var	2024-10-07 20:44:08 +08:00
David Mak	56c845aac4	[standalone] Add support for registering globals without type decl	2024-10-07 20:44:06 +08:00
David Mak	65a12d9ab3	[core] Refactor registration of top-level variables	2024-10-07 17:05:48 +08:00
David Mak	9c6685fa8f	[core] typecheck/function_check: Fix lookup of defined ids in scope	2024-10-07 16:51:37 +08:00
David Mak	2bb788e4bb	[core] codegen/expr: Materialize implicit globals Required for when globals are read without the use of a global declaration.	2024-10-07 13:13:20 +08:00
David Mak	42a2f243b5	[core] typecheck: Disallow redeclaration of var shadowing global	2024-10-07 13:11:00 +08:00
David Mak	3ce2eddcdc	[core] typecheck/type_inferencer: Infer whether variables are global	2024-10-07 13:10:46 +08:00
David Mak	51bf126a32	[core] typecheck/type_inferencer: Differentiate global symbols Required for analyzing use of global symbols before global declaration.	2024-10-07 12:25:00 +08:00
David Mak	1a197c67f6	[core] toplevel/composer: Reduce lock scope while analyzing function	2024-10-05 15:53:20 +08:00
David Mak	581b2f7bb2	[standalone] Add demo for global variables	2024-10-04 13:24:30 +08:00
David Mak	746329ec5d	[standalone] Implement symbol resolution for globals	2024-10-04 13:24:30 +08:00
David Mak	e60e8e837f	[core] Add support for global statements	2024-10-04 13:24:27 +08:00
David Mak	9fdbe9695d	[core] Add generator to SymbolResolver::get_symbol_value Needed in a future commit.	2024-10-04 13:20:29 +08:00
David Mak	8065e73598	[core] toplevel/composer: Add type analysis for global variables	2024-10-04 13:20:29 +08:00
David Mak	192290889b	[core] Add IdentifierInfo Keeps track of whether an identifier refers to a global or local variable.	2024-10-04 13:20:24 +08:00
David Mak	1407553a2f	[core] Implement parsing of global variables Globals are now parsed into symbol resolver and top level definitions.	2024-10-04 13:18:29 +08:00
David Mak	c7697606e1	[core] Add TopLevelDef::Variable	2024-10-04 13:09:25 +08:00
David Mak	88d0ccbf69	[standalone] Explicit panic when encountering a compilation error Otherwise scripts will continue to execute.	2024-10-04 13:00:16 +08:00
David Mak	a43b59539c	[meta] Move variables declarations closer to where they are first used	2024-10-04 13:00:16 +08:00
David Mak	fe06b2806f	[meta] Reorganize order of use declarations Use declarations are now grouped into 4 groups: - Declarations from the standard library - Declarations from external crates - Declarations from other crates in this project - Declarations from within this module Furthermore, all use declarations are grouped together to enhance readability. super::super is also replaced by an equivalent crate:: declaration.	2024-10-04 12:52:01 +08:00
David Mak	7f6c9a25ac	[meta] Update Cargo dependencies	2024-10-04 12:52:01 +08:00
Sébastien Bourdeauducq	6c8382219f	msys2: get python via numpy dependencies	2024-09-30 14:27:30 +08:00
Sebastien Bourdeauducq	9274a7b96b	flake: update nixpkgs	2024-09-30 14:22:40 +08:00
Sébastien Bourdeauducq	d1c0fe2900	cargo: update dependencies	2024-09-30 14:14:43 +08:00
mwojcik	f2c047ba57	artiq: support async rpcs Co-authored-by: mwojcik <mw@m-labs.hk> Co-committed-by: mwojcik <mw@m-labs.hk>	2024-09-13 12:12:13 +08:00
David Mak	5e2e77a500	[meta] Bump inkwell to v0.5	2024-09-13 11:11:14 +08:00
David Mak	f3cc4702b9	[meta] Update dependencies	2024-09-13 11:11:14 +08:00
David Mak	3e92c491f5	[standalone] Add tests creating ndarrays with tuple dims	2024-09-11 15:52:43 +08:00
lyken	7f629f1579	core: fix comment in unify_call	2024-09-11 15:46:19 +08:00
lyken	5640a793e2	core: allow np_full to take tuple shapes	2024-09-11 15:46:19 +08:00
David Mak	abbaa506ad	[standalone] Remove redundant recreation of TargetMachine	2024-09-09 14:27:10 +08:00
David Mak	f3dc02d646	[meta] Apply cargo fmt	2024-09-09 14:24:52 +08:00
David Mak	ea217eaea1	[meta] Update pre-commit config Directly invoke cargo using nix develop to avoid using the system cargo.	2024-09-09 14:24:38 +08:00
Sébastien Bourdeauducq	5a34551905	allow the use of the LLVM shared library Which in turns allows working around the incompatibility of the LLVM static library with Rust link-args=-rdynamic, which produces binaries that either fail to link (OpenBSD) or segfault on startup (Linux). The year is 2024 and compiler toolchains are still a trash fire like this.	2024-09-09 11:17:31 +08:00
Sebastien Bourdeauducq	6098b1b853	fix previous commit	2024-09-06 11:32:08 +08:00
Sebastien Bourdeauducq	668ccb1c95	nac3core: expose inkwell and nac3parser	2024-09-06 11:06:26 +08:00
Sebastien Bourdeauducq	a3c624d69d	update all dependencies	2024-09-06 10:21:58 +08:00
Sébastien Bourdeauducq	bd06155f34	irrt: compatibility with pre-C23 compilers	2024-09-05 18:54:55 +08:00
David Mak	9c33c4209c	[core] Fix type of ndarray.element_type Should be the element type of the NDArray itself, not the pointer to its type.	2024-08-30 22:47:38 +08:00
Sebastien Bourdeauducq	122983f11c	flake: update dependencies	2024-08-30 14:45:38 +08:00