standalone/demo: numpy2 compatibility

update dependencies
[core] codegen/ndarray: Make ndims non-optional
2025-01-04 15:30:24 +08:00 · 2025-01-04 10:28:41 +08:00 · 2025-01-03 15:43:08 +08:00 · 2025-01-03 15:43:08 +08:00 · 2025-01-03 15:43:06 +08:00 · 2025-01-03 15:15:13 +08:00
124 changed files with 13802 additions and 8470 deletions
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@ -1,7 +1,7 @@
 # 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
--- 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",
@ -41,36 +41,36 @@ dependencies = [

 [[package]]
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-version = "1.0.8"
+version = "1.0.10"
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-checksum = "1bec1de6f59aedf83baf9ff929c98f2ad654b97c9510f4e70cf6f661d49fd5b1"
+checksum = "55cc3b69f167a1ef2e161439aa98aed94e6028e5f9a59be9a6ffb47aef1651f9"

 [[package]]
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-checksum = "eb47de1e80c2b463c735db5b217a0ddc39d612e7ac9e2e96a5aed1f57616c1cb"
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 dependencies = [
 "utf8parse",
 ]

 [[package]]
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-version = "1.1.1"
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 dependencies = [
- "windows-sys 0.52.0",
+ "windows-sys 0.59.0",
 ]

 [[package]]
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-version = "3.0.4"
+version = "3.0.6"
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-checksum = "5bf74e1b6e971609db8ca7a9ce79fd5768ab6ae46441c572e46cf596f59e57f8"
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 dependencies = [
 "anstyle",
- "windows-sys 0.52.0",
+ "windows-sys 0.59.0",
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 [[package]]
@ -126,9 +126,9 @@ checksum = "1fd0f2584146f6f2ef48085050886acf353beff7305ebd1ae69500e27c67f64b"

 [[package]]
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-checksum = "b16803a61b81d9eabb7eae2588776c4c1e584b738ede45fdbb4c972cec1e9945"
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 dependencies = [
 "shlex",
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@ -141,9 +141,9 @@ checksum = "baf1de4339761588bc0619e3cbc0120ee582ebb74b53b4efbf79117bd2da40fd"

 [[package]]
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+version = "4.5.23"
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-checksum = "b97f376d85a664d5837dbae44bf546e6477a679ff6610010f17276f686d867e8"
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 dependencies = [
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 "clap_derive",
@ -151,9 +151,9 @@ dependencies = [

 [[package]]
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-version = "4.5.20"
+version = "4.5.23"
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 dependencies = [
 "anstream",
 "anstyle",
@ -170,38 +170,38 @@ dependencies = [
 "heck 0.5.0",
 "proc-macro2",
 "quote",
- "syn 2.0.79",
+ "syn 2.0.94",
 ]

 [[package]]
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 dependencies = [
 "encode_unicode",
- "lazy_static",
 "libc",
- "windows-sys 0.52.0",
+ "once_cell",
+ "windows-sys 0.59.0",
 ]

 [[package]]
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 dependencies = [
 "libc",
 ]
@ -221,18 +221,18 @@ dependencies = [

 [[package]]
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+version = "0.5.14"
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 "crossbeam-utils",
@ -249,18 +249,18 @@ dependencies = [

 [[package]]
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+version = "0.3.12"
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 [[package]]
 name = "crypto-common"
@ -282,6 +282,12 @@ dependencies = [
 "crypto-common",
 ]

+[[package]]
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+source = "registry+https://github.com/rust-lang/crates.io-index"
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+
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@ -299,9 +305,9 @@ dependencies = [

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@ -311,19 +317,19 @@ checksum = "5443807d6dff69373d433ab9ef5378ad8df50ca6298caf15de6e52e24aaf54d5"

 [[package]]
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- "windows-sys 0.52.0",
+ "windows-sys 0.59.0",
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 [[package]]
 name = "fixedbitset"
@ -370,6 +376,12 @@ dependencies = [
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 ]

+[[package]]
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+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "a8d1add55171497b4705a648c6b583acafb01d58050a51727785f0b2c8e0a2b2"
+
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@ -387,9 +399,9 @@ dependencies = [

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@ -405,11 +417,11 @@ checksum = "2304e00983f87ffb38b55b444b5e3b60a884b5d30c0fca7d82fe33449bbe55ea"

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+ "windows-sys 0.59.0",
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 [[package]]
@ -424,12 +436,12 @@ dependencies = [

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-version = "2.6.0"
+version = "2.7.0"
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- "hashbrown 0.15.0",
+ "hashbrown 0.15.2",
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@ -460,7 +472,7 @@ checksum = "9dd28cfd4cfba665d47d31c08a6ba637eed16770abca2eccbbc3ca831fef1e44"
 dependencies = [
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+ "syn 2.0.94",
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 [[package]]
@ -494,9 +506,9 @@ dependencies = [

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@ -547,15 +559,15 @@ checksum = "bbd2bcb4c963f2ddae06a2efc7e9f3591312473c50c6685e1f298068316e66fe"

 [[package]]
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@ -634,7 +646,6 @@ name = "nac3ast"
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 dependencies = [
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- "lazy_static",
 "parking_lot",
 "string-interner",
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@ -644,11 +655,12 @@ name = "nac3core"
 version = "0.1.0"
 dependencies = [
 "crossbeam",
- "indexmap 2.6.0",
+ "indexmap 2.7.0",
 "indoc",
 "inkwell",
 "insta",
 "itertools",
+ "nac3core_derive",
 "nac3parser",
 "parking_lot",
 "rayon",
@ -658,6 +670,18 @@ dependencies = [
 "test-case",
 ]

+[[package]]
+name = "nac3core_derive"
+version = "0.1.0"
+dependencies = [
+ "nac3core",
+ "proc-macro-error",
+ "proc-macro2",
+ "quote",
+ "syn 2.0.94",
+ "trybuild",
+]
+
 [[package]]
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@ -732,7 +756,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
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 dependencies = [
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- "indexmap 2.6.0",
+ "indexmap 2.7.0",
 ]

 [[package]]
@ -775,7 +799,7 @@ dependencies = [
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 "proc-macro2",
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- "syn 2.0.79",
+ "syn 2.0.94",
 ]

 [[package]]
@ -804,9 +828,9 @@ checksum = "5be167a7af36ee22fe3115051bc51f6e6c7054c9348e28deb4f49bd6f705a315"

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@ -824,10 +848,34 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
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+ "proc-macro2",
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+ "syn 1.0.109",
+ "version_check",
+]
+
+[[package]]
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@ -879,7 +927,7 @@ dependencies = [
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 "pyo3-macros-backend",
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- "syn 2.0.79",
+ "syn 2.0.94",
 ]

 [[package]]
@ -892,14 +940,14 @@ dependencies = [
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- "syn 2.0.79",
+ "syn 2.0.94",
 ]

 [[package]]
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@ -956,18 +1004,18 @@ dependencies = [

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@ -977,9 +1025,9 @@ dependencies = [

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@ -1001,22 +1049,22 @@ dependencies = [

 [[package]]
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+ "windows-sys 0.59.0",
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@ -1041,35 +1089,35 @@ checksum = "94143f37725109f92c262ed2cf5e59bce7498c01bcc1502d7b9afe439a4e9f49"

 [[package]]
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-version = "1.0.23"
+version = "1.0.24"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "61697e0a1c7e512e84a621326239844a24d8207b4669b41bc18b32ea5cbf988b"
+checksum = "3cb6eb87a131f756572d7fb904f6e7b68633f09cca868c5df1c4b8d1a694bbba"

 [[package]]
 name = "serde"
-version = "1.0.210"
+version = "1.0.217"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c8e3592472072e6e22e0a54d5904d9febf8508f65fb8552499a1abc7d1078c3a"
+checksum = "02fc4265df13d6fa1d00ecff087228cc0a2b5f3c0e87e258d8b94a156e984c70"
 dependencies = [
 "serde_derive",
 ]

 [[package]]
 name = "serde_derive"
-version = "1.0.210"
+version = "1.0.217"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "243902eda00fad750862fc144cea25caca5e20d615af0a81bee94ca738f1df1f"
+checksum = "5a9bf7cf98d04a2b28aead066b7496853d4779c9cc183c440dbac457641e19a0"
 dependencies = [
 "proc-macro2",
 "quote",
- "syn 2.0.79",
+ "syn 2.0.94",
 ]

 [[package]]
 name = "serde_json"
-version = "1.0.129"
+version = "1.0.134"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "6dbcf9b78a125ee667ae19388837dd12294b858d101fdd393cb9d5501ef09eb2"
+checksum = "d00f4175c42ee48b15416f6193a959ba3a0d67fc699a0db9ad12df9f83991c7d"
 dependencies = [
 "itoa",
 "memchr",
@ -1077,6 +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"
@ -1169,7 +1226,7 @@ dependencies = [
 "proc-macro2",
 "quote",
 "rustversion",
- "syn 2.0.79",
+ "syn 2.0.94",
 ]

 [[package]]
@ -1185,9 +1242,9 @@ dependencies = [

 [[package]]
 name = "syn"
-version = "2.0.79"
+version = "2.0.94"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "89132cd0bf050864e1d38dc3bbc07a0eb8e7530af26344d3d2bbbef83499f590"
+checksum = "987bc0be1cdea8b10216bd06e2ca407d40b9543468fafd3ddfb02f36e77f71f3"
 dependencies = [
 "proc-macro2",
 "quote",
@ -1201,13 +1258,20 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "61c41af27dd6d1e27b1b16b489db798443478cef1f06a660c96db617ba5de3b1"

 [[package]]
-name = "tempfile"
-version = "3.13.0"
+name = "target-triple"
+version = "0.1.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "f0f2c9fc62d0beef6951ccffd757e241266a2c833136efbe35af6cd2567dca5b"
+checksum = "42a4d50cdb458045afc8131fd91b64904da29548bcb63c7236e0844936c13078"
+
+[[package]]
+name = "tempfile"
+version = "3.15.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "9a8a559c81686f576e8cd0290cd2a24a2a9ad80c98b3478856500fcbd7acd704"
 dependencies = [
 "cfg-if",
 "fastrand",
+ "getrandom",
 "once_cell",
 "rustix",
 "windows-sys 0.59.0",
@ -1215,14 +1279,23 @@ dependencies = [

 [[package]]
 name = "term"
-version = "1.0.0"
+version = "1.0.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4df4175de05129f31b80458c6df371a15e7fc3fd367272e6bf938e5c351c7ea0"
+checksum = "a3bb6001afcea98122260987f8b7b5da969ecad46dbf0b5453702f776b491a41"
 dependencies = [
 "home",
 "windows-sys 0.52.0",
 ]

+[[package]]
+name = "termcolor"
+version = "1.4.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "06794f8f6c5c898b3275aebefa6b8a1cb24cd2c6c79397ab15774837a0bc5755"
+dependencies = [
+ "winapi-util",
+]
+
 [[package]]
 name = "test-case"
 version = "1.2.3"
@ -1238,22 +1311,72 @@ dependencies = [

 [[package]]
 name = "thiserror"
-version = "1.0.64"
+version = "1.0.69"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "d50af8abc119fb8bb6dbabcfa89656f46f84aa0ac7688088608076ad2b459a84"
+checksum = "b6aaf5339b578ea85b50e080feb250a3e8ae8cfcdff9a461c9ec2904bc923f52"
 dependencies = [
 "thiserror-impl",
 ]

 [[package]]
 name = "thiserror-impl"
-version = "1.0.64"
+version = "1.0.69"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "08904e7672f5eb876eaaf87e0ce17857500934f4981c4a0ab2b4aa98baac7fc3"
+checksum = "4fee6c4efc90059e10f81e6d42c60a18f76588c3d74cb83a0b242a2b6c7504c1"
 dependencies = [
 "proc-macro2",
 "quote",
- "syn 2.0.79",
+ "syn 2.0.94",
+]
+
+[[package]]
+name = "toml"
+version = "0.8.19"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "a1ed1f98e3fdc28d6d910e6737ae6ab1a93bf1985935a1193e68f93eeb68d24e"
+dependencies = [
+ "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 2.7.0",
+ "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]]
@ -1316,9 +1439,9 @@ dependencies = [

 [[package]]
 name = "unicode-ident"
-version = "1.0.13"
+version = "1.0.14"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "e91b56cd4cadaeb79bbf1a5645f6b4f8dc5bde8834ad5894a8db35fda9efa1fe"
+checksum = "adb9e6ca4f869e1180728b7950e35922a7fc6397f7b641499e8f3ef06e50dc83"

 [[package]]
 name = "unicode-width"
@ -1479,6 +1602,15 @@ version = "0.52.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "589f6da84c646204747d1270a2a5661ea66ed1cced2631d546fdfb155959f9ec"

+[[package]]
+name = "winnow"
+version = "0.6.22"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "39281189af81c07ec09db316b302a3e67bf9bd7cbf6c820b50e35fee9c2fa980"
+dependencies = [
+ "memchr",
+]
+
 [[package]]
 name = "yaml-rust"
 version = "0.4.5"
@ -1506,5 +1638,5 @@ checksum = "fa4f8080344d4671fb4e831a13ad1e68092748387dfc4f55e356242fae12ce3e"
 dependencies = [
 "proc-macro2",
 "quote",
- "syn 2.0.79",
+ "syn 2.0.94",
 ]
--- 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": 1727348695,
-        "narHash": "sha256-J+PeFKSDV+pHL7ukkfpVzCOO7mBSrrpJ3svwBFABbhI=",
+        "lastModified": 1735834308,
+        "narHash": "sha256-dklw3AXr3OGO4/XT1Tu3Xz9n/we8GctZZ75ZWVqAVhk=",
        "owner": "NixOS",
        "repo": "nixpkgs",
-        "rev": "1925c603f17fc89f4c8f6bf6f631a802ad85d784",
+        "rev": "6df24922a1400241dae323af55f30e4318a6ca65",
        "type": "github"
      },
      "original": {
--- a/flake.nix
+++ b/flake.nix
@ -107,18 +107,18 @@
            (pkgs.fetchFromGitHub {
              owner = "m-labs";
              repo = "sipyco";
-              rev = "939f84f9b5eef7efbf7423c735d1834783b6140e";
-              sha256 = "sha256-15Nun4EY35j+6SPZkjzZtyH/ncxLS60KuGJjFh5kSTc=";
+              rev = "094a6cd63ffa980ef63698920170e50dc9ba77fd";
+              sha256 = "sha256-PPnAyDedUQ7Og/Cby9x5OT9wMkNGTP8GS53V6N/dk4w=";
            })
            (pkgs.fetchFromGitHub {
              owner = "m-labs";
              repo = "artiq";
-              rev = "923ca3377d42c815f979983134ec549dc39d3ca0";
-              sha256 = "sha256-oJoEeNEeNFSUyh6jXG8Tzp6qHVikeHS0CzfE+mODPgw=";
+              rev = "28c9de3e251daa89a8c9fd79d5ab64a3ec03bac6";
+              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/demo/embedding_map.py
+++ b/nac3artiq/demo/embedding_map.py
@ -7,33 +7,6 @@ class EmbeddingMap:
        self.function_map = {}
        self.attributes_writeback = []

-        # preallocate exception names
-        self.preallocate_runtime_exception_names(["RuntimeError",
-                                          "RTIOUnderflow",
-                                          "RTIOOverflow",
-                                          "RTIODestinationUnreachable",
-                                          "DMAError",
-                                          "I2CError",
-                                          "CacheError",
-                                          "SPIError",
-                                          "0:ZeroDivisionError",
-                                          "0:IndexError",
-                                          "0:ValueError",
-                                          "0:RuntimeError",
-                                          "0:AssertionError",
-                                          "0:KeyError",
-                                          "0:NotImplementedError",
-                                          "0:OverflowError",
-                                          "0:IOError",
-                                          "0:UnwrapNoneError"])
-
-    def preallocate_runtime_exception_names(self, names):
-        for i, name in enumerate(names):
-            if ":" not in name:
-                name = "0:artiq.coredevice.exceptions." + name
-            exn_id = self.store_str(name)
-            assert exn_id == i
-
    def store_function(self, key, fun):
        self.function_map[key] = fun
        return key
--- a/nac3artiq/demo/min_artiq.py
+++ b/nac3artiq/demo/min_artiq.py
@ -206,7 +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
@ -12,16 +12,18 @@ use pyo3::{
    PyObject, PyResult, Python,
 };

+use super::{symbol_resolver::InnerResolver, timeline::TimeFns};
 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},
+        llvm_intrinsics::{call_int_smax, call_memcpy, call_stackrestore, call_stacksave},
        stmt::{gen_block, gen_for_callback_incrementing, gen_if_callback, gen_with},
+        type_aligned_alloca,
+        types::ndarray::NDArrayType,
+        values::{
+            ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, ProxyValue, RangeValue,
+            UntypedArrayLikeAccessor,
+        },
        CodeGenContext, CodeGenerator,
    },
    inkwell::{
@ -33,12 +35,14 @@ use nac3core::{
    },
    nac3parser::ast::{Expr, ExprKind, Located, Stmt, StmtKind, StrRef},
    symbol_resolver::ValueEnum,
-    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId, GenCall},
+    toplevel::{
+        helper::{extract_ndims, 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 {
@ -457,52 +461,49 @@ fn format_rpc_arg<'ctx>(
            let llvm_i1 = ctx.ctx.bool_type();
            let llvm_usize = generator.get_size_type(ctx.ctx);

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

-            let llvm_usize_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(llvm_arg_ty.size_type().size_of(), llvm_usize, "")
-                .unwrap();
-            let llvm_pdata_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(
-                    llvm_elem_ty.ptr_type(AddressSpace::default()).size_of(),
-                    llvm_usize,
-                    "",
-                )
-                .unwrap();
+            let ndims = llvm_usize.const_int(ndims, false);

-            let dims_buf_sz =
-                ctx.builder.build_int_mul(llvm_arg.load_ndims(ctx), llvm_usize_sizeof, "").unwrap();
+            // `ndarray.data` is possibly not contiguous, and we need it to be contiguous for
+            // the reader.
+            // Turning it into a ContiguousNDArray to get a `data` that is contiguous.
+            let carray = ndarray.make_contiguous_ndarray(generator, ctx);

-            let buffer_size =
-                ctx.builder.build_int_add(dims_buf_sz, llvm_pdata_sizeof, "").unwrap();
+            let sizeof_usize = llvm_usize.size_of();
+            let sizeof_usize =
+                ctx.builder.build_int_z_extend_or_bit_cast(sizeof_usize, llvm_usize, "").unwrap();

-            let buffer = ctx.builder.build_array_alloca(llvm_i8, buffer_size, "rpc.arg").unwrap();
-            let buffer = ArraySliceValue::from_ptr_val(buffer, buffer_size, Some("rpc.arg"));
+            let sizeof_pdata = dtype.ptr_type(AddressSpace::default()).size_of();
+            let sizeof_pdata =
+                ctx.builder.build_int_z_extend_or_bit_cast(sizeof_pdata, llvm_usize, "").unwrap();

-            call_memcpy_generic(
-                ctx,
-                buffer.base_ptr(ctx, generator),
-                llvm_arg.ptr_to_data(ctx),
-                llvm_pdata_sizeof,
-                llvm_i1.const_zero(),
-            );
+            let sizeof_buf_shape = ctx.builder.build_int_mul(sizeof_usize, ndims, "").unwrap();
+            let sizeof_buf = ctx.builder.build_int_add(sizeof_buf_shape, sizeof_pdata, "").unwrap();

-            let pbuffer_dims_begin =
-                unsafe { buffer.ptr_offset_unchecked(ctx, generator, &llvm_pdata_sizeof, None) };
-            call_memcpy_generic(
-                ctx,
-                pbuffer_dims_begin,
-                llvm_arg.dim_sizes().base_ptr(ctx, generator),
-                dims_buf_sz,
-                llvm_i1.const_zero(),
-            );
+            // buf = { data: void*, shape: [size_t; ndims]; }
+            let buf = ctx.builder.build_array_alloca(llvm_i8, sizeof_buf, "rpc.arg").unwrap();
+            let buf = ArraySliceValue::from_ptr_val(buf, sizeof_buf, Some("rpc.arg"));
+            let buf_data = buf.base_ptr(ctx, generator);
+            let buf_shape =
+                unsafe { buf.ptr_offset_unchecked(ctx, generator, &sizeof_pdata, None) };

-            buffer.base_ptr(ctx, generator)
+            // Write to `buf->data`
+            let carray_data = carray.load_data(ctx);
+            let carray_data = ctx.builder.build_pointer_cast(carray_data, llvm_pi8, "").unwrap();
+            call_memcpy(ctx, buf_data, carray_data, sizeof_pdata, llvm_i1.const_zero());
+
+            // Write to `buf->shape`
+            let carray_shape = ndarray.shape().base_ptr(ctx, generator);
+            let carray_shape_i8 =
+                ctx.builder.build_pointer_cast(carray_shape, llvm_pi8, "").unwrap();
+            call_memcpy(ctx, buf_shape, carray_shape_i8, sizeof_buf_shape, llvm_i1.const_zero());
+
+            buf.base_ptr(ctx, generator)
        }

        _ => {
@ -543,6 +544,8 @@ fn format_rpc_ret<'ctx>(
    let llvm_i32 = ctx.ctx.i32_type();
    let llvm_i8_8 = ctx.ctx.struct_type(&[llvm_i8.array_type(8).into()], false);
    let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());

    let rpc_recv = ctx.module.get_function("rpc_recv").unwrap_or_else(|| {
        ctx.module.add_function("rpc_recv", llvm_i32.fn_type(&[llvm_pi8.into()], false), None)
@ -563,8 +566,7 @@ fn format_rpc_ret<'ctx>(

    let result = match &*ctx.unifier.get_ty_immutable(ret_ty) {
        TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-            let llvm_i1 = ctx.ctx.bool_type();
-            let llvm_usize = generator.get_size_type(ctx.ctx);
+            let num_0 = llvm_usize.const_zero();

            // Round `val` up to its modulo `power_of_two`
            let round_up = |ctx: &mut CodeGenContext<'ctx, '_>,
@ -590,79 +592,49 @@ fn format_rpc_ret<'ctx>(
                    .unwrap()
            };

-            // Setup types
-            let (elem_ty, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, ret_ty);
-            let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
-            let llvm_ret_ty = NDArrayType::new(generator, ctx.ctx, llvm_elem_ty);
-
            // Allocate the resulting ndarray
            // A condition after format_rpc_ret ensures this will not be popped this off.
-            let ndarray = llvm_ret_ty.new_value(generator, ctx, Some("rpc.result"));
+            let (dtype, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, ret_ty);
+            let dtype_llvm = ctx.get_llvm_type(generator, dtype);
+            let ndims = extract_ndims(&ctx.unifier, ndims);
+            let ndarray = NDArrayType::new(generator, ctx.ctx, dtype_llvm, ndims)
+                .construct_uninitialized(generator, ctx, None);

-            // Setup ndims
-            let ndims =
-                if let TypeEnum::TLiteral { values, .. } = &*ctx.unifier.get_ty_immutable(ndims) {
-                    assert_eq!(values.len(), 1);
+            // NOTE: Current content of `ndarray`:
+            //   - * `data` - **NOT YET** allocated.
+            //   - * `itemsize` - initialized to be size_of(dtype).
+            //   - * `ndims` - initialized.
+            //   - * `shape` - allocated; has uninitialized values.
+            //   - * `strides` - allocated; has uninitialized values.

-                    u64::try_from(values[0].clone()).unwrap()
-                } else {
-                    unreachable!();
-                };
-            // Set `ndarray.ndims`
-            ndarray.store_ndims(ctx, generator, llvm_usize.const_int(ndims, false));
-            // Allocate `ndarray.shape` [size_t; ndims]
-            ndarray.create_dim_sizes(ctx, llvm_usize, ndarray.load_ndims(ctx));
-
-            /*
-                ndarray now:
-                  - .ndims: initialized
-                  - .shape: allocated but uninitialized .shape
-                  - .data: uninitialized
-            */
-
-            let llvm_usize_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(llvm_usize.size_of(), llvm_usize, "")
-                .unwrap();
-            let llvm_pdata_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(
-                    llvm_elem_ty.ptr_type(AddressSpace::default()).size_of(),
-                    llvm_usize,
-                    "",
-                )
-                .unwrap();
-            let llvm_elem_sizeof = ctx
-                .builder
-                .build_int_truncate_or_bit_cast(llvm_elem_ty.size_of().unwrap(), llvm_usize, "")
-                .unwrap();
+            let itemsize = ndarray.load_itemsize(ctx); // Same as doing a `ctx.get_llvm_type` on `dtype` and get its `size_of()`.

            // Allocates a buffer for the initial RPC'ed object, which is guaranteed to be
            // (4 + 4 * ndims) bytes with 8-byte alignment
-            let sizeof_dims =
-                ctx.builder.build_int_mul(ndarray.load_ndims(ctx), llvm_usize_sizeof, "").unwrap();
+            let sizeof_usize = llvm_usize.size_of();
+            let sizeof_usize =
+                ctx.builder.build_int_truncate_or_bit_cast(sizeof_usize, llvm_usize, "").unwrap();
+
+            let sizeof_ptr = llvm_i8.ptr_type(AddressSpace::default()).size_of();
+            let sizeof_ptr =
+                ctx.builder.build_int_z_extend_or_bit_cast(sizeof_ptr, llvm_usize, "").unwrap();
+
+            let sizeof_shape =
+                ctx.builder.build_int_mul(ndarray.load_ndims(ctx), sizeof_usize, "").unwrap();
+
+            // Size of the buffer for the initial `rpc_recv()`.
            let unaligned_buffer_size =
-                ctx.builder.build_int_add(sizeof_dims, llvm_pdata_sizeof, "").unwrap();
-            let buffer_size = round_up(ctx, unaligned_buffer_size, llvm_usize.const_int(8, false));
+                ctx.builder.build_int_add(sizeof_ptr, sizeof_shape, "").unwrap();

            let stackptr = call_stacksave(ctx, None);
-            // Just to be absolutely sure, alloca in [i8 x 8] slices to force 8-byte alignment
-            let buffer = ctx
-                .builder
-                .build_array_alloca(
+            let buffer = type_aligned_alloca(
+                generator,
+                ctx,
                llvm_i8_8,
-                    ctx.builder
-                        .build_int_unsigned_div(buffer_size, llvm_usize.const_int(8, false), "")
-                        .unwrap(),
-                    "rpc.buffer",
-                )
-                .unwrap();
-            let buffer = ctx
-                .builder
-                .build_bit_cast(buffer, llvm_pi8, "")
-                .map(BasicValueEnum::into_pointer_value)
-                .unwrap();
-            let buffer = ArraySliceValue::from_ptr_val(buffer, buffer_size, None);
+                unaligned_buffer_size,
+                Some("rpc.buffer"),
+            );
+            let buffer = ArraySliceValue::from_ptr_val(buffer, unaligned_buffer_size, None);

            // The first call to `rpc_recv` reads the top-level ndarray object: [pdata, shape]
            //
@ -670,7 +642,7 @@ fn format_rpc_ret<'ctx>(
            let ndarray_nbytes = ctx
                .build_call_or_invoke(
                    rpc_recv,
-                    &[buffer.base_ptr(ctx, generator).into()], // Reads [usize; ndims]. NOTE: We are allocated [size_t; ndims].
+                    &[buffer.base_ptr(ctx, generator).into()], // Reads [usize; ndims]
                    "rpc.size.next",
                )
                .map(BasicValueEnum::into_int_value)
@ -678,16 +650,14 @@ fn format_rpc_ret<'ctx>(

            // debug_assert(ndarray_nbytes > 0)
            if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
+                let cmp = ctx
+                    .builder
+                    .build_int_compare(IntPredicate::UGT, ndarray_nbytes, num_0, "")
+                    .unwrap();
+
                ctx.make_assert(
                    generator,
-                    ctx.builder
-                        .build_int_compare(
-                            IntPredicate::UGT,
-                            ndarray_nbytes,
-                            ndarray_nbytes.get_type().const_zero(),
-                            "",
-                        )
-                        .unwrap(),
+                    cmp,
                    "0:AssertionError",
                    "Unexpected RPC termination for ndarray - Expected data buffer next",
                    [None, None, None],
@ -696,49 +666,50 @@ fn format_rpc_ret<'ctx>(
            }

            // Copy shape from the buffer to `ndarray.shape`.
-            let pbuffer_dims =
-                unsafe { buffer.ptr_offset_unchecked(ctx, generator, &llvm_pdata_sizeof, None) };
+            // We need to skip the first `sizeof(uint8_t*)` bytes to skip the `pdata` in `[pdata, shape]`.
+            let pbuffer_shape =
+                unsafe { buffer.ptr_offset_unchecked(ctx, generator, &sizeof_ptr, None) };
+            let pbuffer_shape =
+                ctx.builder.build_pointer_cast(pbuffer_shape, llvm_pusize, "").unwrap();
+
+            // Copy shape from buffer to `ndarray.shape`
+            ndarray.copy_shape_from_array(generator, ctx, pbuffer_shape);

-            call_memcpy_generic(
-                ctx,
-                ndarray.dim_sizes().base_ptr(ctx, generator),
-                pbuffer_dims,
-                sizeof_dims,
-                llvm_i1.const_zero(),
-            );
            // Restore stack from before allocation of buffer
            call_stackrestore(ctx, stackptr);

            // Allocate `ndarray.data`.
            // `ndarray.shape` must be initialized beforehand in this implementation
            //   (for ndarray.create_data() to know how many elements to allocate)
-            let num_elements =
-                call_ndarray_calc_size(generator, ctx, &ndarray.dim_sizes(), (None, None));
+            unsafe { ndarray.create_data(generator, ctx) }; // NOTE: the strides of `ndarray` has also been set to contiguous in `create_data`.

            // debug_assert(nelems * sizeof(T) >= ndarray_nbytes)
            if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
-                let sizeof_data =
-                    ctx.builder.build_int_mul(num_elements, llvm_elem_sizeof, "").unwrap();
+                let num_elements = ndarray.size(generator, ctx);
+
+                let expected_ndarray_nbytes =
+                    ctx.builder.build_int_mul(num_elements, itemsize, "").unwrap();
+                let cmp = ctx
+                    .builder
+                    .build_int_compare(
+                        IntPredicate::UGE,
+                        expected_ndarray_nbytes,
+                        ndarray_nbytes,
+                        "",
+                    )
+                    .unwrap();

                ctx.make_assert(
                    generator,
-                    ctx.builder.build_int_compare(IntPredicate::UGE,
-                        sizeof_data,
-                        ndarray_nbytes,
-                        "",
-                    ).unwrap(),
+                    cmp,
                    "0:AssertionError",
                    "Unexpected allocation size request for ndarray data - Expected up to {0} bytes, got {1} bytes",
-                    [Some(sizeof_data), Some(ndarray_nbytes), None],
+                    [Some(expected_ndarray_nbytes), Some(ndarray_nbytes), None],
                    ctx.current_loc,
                );
            }

-            ndarray.create_data(ctx, llvm_elem_ty, num_elements);
-
            let ndarray_data = ndarray.data().base_ptr(ctx, generator);
-            let ndarray_data_i8 =
-                ctx.builder.build_pointer_cast(ndarray_data, llvm_pi8, "").unwrap();

            // NOTE: Currently on `prehead_bb`
            ctx.builder.build_unconditional_branch(head_bb).unwrap();
@ -747,7 +718,7 @@ fn format_rpc_ret<'ctx>(
            ctx.builder.position_at_end(head_bb);

            let phi = ctx.builder.build_phi(llvm_pi8, "rpc.ptr").unwrap();
-            phi.add_incoming(&[(&ndarray_data_i8, prehead_bb)]);
+            phi.add_incoming(&[(&ndarray_data, prehead_bb)]);

            let alloc_size = ctx
                .build_call_or_invoke(rpc_recv, &[phi.as_basic_value()], "rpc.size.next")
@ -762,12 +733,13 @@ fn format_rpc_ret<'ctx>(

            ctx.builder.position_at_end(alloc_bb);
            // Align the allocation to sizeof(T)
-            let alloc_size = round_up(ctx, alloc_size, llvm_elem_sizeof);
+            let alloc_size = round_up(ctx, alloc_size, itemsize);
+            // TODO(Derppening): Candidate for refactor into type_aligned_alloca
            let alloc_ptr = ctx
                .builder
                .build_array_alloca(
-                    llvm_elem_ty,
-                    ctx.builder.build_int_unsigned_div(alloc_size, llvm_elem_sizeof, "").unwrap(),
+                    dtype_llvm,
+                    ctx.builder.build_int_unsigned_div(alloc_size, itemsize, "").unwrap(),
                    "rpc.alloc",
                )
                .unwrap();
@ -990,11 +962,12 @@ fn rpc_codegen_callback_fn<'ctx>(
    }
 }

-pub fn attributes_writeback(
-    ctx: &mut CodeGenContext<'_, '_>,
+pub fn attributes_writeback<'ctx>(
+    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)?;
@ -1004,6 +977,11 @@ 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(
@ -1082,7 +1060,7 @@ pub fn attributes_writeback(
        let args: Vec<_> =
            values.into_iter().map(|(_, val)| (None, ValueEnum::Dynamic(val))).collect();
        if let Err(e) =
-            rpc_codegen_callback_fn(ctx, None, (&fun, PrimDef::Int32.id()), args, generator, false)
+            rpc_codegen_callback_fn(ctx, None, (&fun, PrimDef::Int32.id()), args, generator, true)
        {
            return Ok(Err(e));
        }
@ -1308,7 +1286,8 @@ 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();
@ -1359,56 +1338,50 @@ fn polymorphic_print<'ctx>(
            }

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

-                let val = NDArrayValue::from_ptr_val(value.into_pointer_value(), llvm_usize, None);
-                let len = call_ndarray_calc_size(generator, ctx, &val.dim_sizes(), (None, None));
-                let last =
-                    ctx.builder.build_int_sub(len, llvm_usize.const_int(1, false), "").unwrap();
+                let (dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
+                let ndarray = NDArrayType::from_unifier_type(generator, ctx, ty)
+                    .map_value(value.into_pointer_value(), None);

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

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

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

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

                fmt.push_str(")]");
                flush(ctx, generator, &mut fmt, &mut args);
@ -1418,7 +1391,7 @@ 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(
-    future_incompatible,
-    let_underscore,
-    nonstandard_style,
-    rust_2024_compatibility,
-    clippy::all
-)]
+#![deny(future_incompatible, let_underscore, nonstandard_style, clippy::all)]
 #![warn(clippy::pedantic)]
 #![allow(
    unsafe_op_in_unsafe_fn,
@ -30,19 +24,19 @@ use parking_lot::{Mutex, RwLock};
 use pyo3::{
    create_exception, exceptions,
    prelude::*,
-    types::{PyBytes, PyDict, PySet},
+    types::{PyBytes, PyDict, PyNone, PySet},
 };
 use tempfile::{self, TempDir};

 use nac3core::{
    codegen::{
        concrete_type::ConcreteTypeStore, gen_func_impl, irrt::load_irrt, CodeGenLLVMOptions,
-        CodeGenTargetMachineOptions, CodeGenTask, WithCall, WorkerRegistry,
+        CodeGenTargetMachineOptions, CodeGenTask, CodeGenerator, WithCall, WorkerRegistry,
    },
    inkwell::{
        context::Context,
        memory_buffer::MemoryBuffer,
-        module::{Linkage, Module},
+        module::{FlagBehavior, Linkage, Module},
        passes::PassBuilderOptions,
        support::is_multithreaded,
        targets::*,
@ -148,14 +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}")))?;

@ -565,7 +577,7 @@ impl Nac3 {
            field_to_val: RwLock::default(),
            name_to_pyid,
            module: module.to_object(py),
-            helper,
+            helper: helper.clone(),
            string_store: self.string_store.clone(),
            exception_ids: self.exception_ids.clone(),
            deferred_eval_store: self.deferred_eval_store.clone(),
@ -673,33 +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,
        };

@ -723,19 +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 =
-                ArtiqCodeGenerator::new("attributes_writeback".to_string(), size_t, self.time_fns);
+            let mut generator = ArtiqCodeGenerator::new("main".to_string(), size_t, self.time_fns);
            let context = Context::create();
-            let module = context.create_module("attributes_writeback");
+            let module = context.create_module("main");
            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,
@ -743,9 +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();
@ -754,35 +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();
@ -817,6 +822,20 @@ impl Nac3 {
            panic!("Failed to run optimization for module `main`: {}", err.to_string());
        }

+        Python::with_gil(|py| {
+            let string_store = self.string_store.read();
+            let mut string_store_vec = string_store.iter().collect::<Vec<_>>();
+            string_store_vec.sort_by(|(_s1, key1), (_s2, key2)| key1.cmp(key2));
+            for (s, key) in string_store_vec {
+                let embed_key: i32 = helper.store_str.call1(py, (s,)).unwrap().extract(py).unwrap();
+                assert_eq!(
+                    embed_key, *key,
+                    "string {s} is out of sync between embedding map (key={embed_key}) and \
+                    the internal string store (key={key})"
+                );
+            }
+        });
+
        link_fn(&main)
    }

@ -1066,6 +1085,48 @@ impl Nac3 {
        let working_directory = tempfile::Builder::new().prefix("nac3-").tempdir().unwrap();
        fs::write(working_directory.path().join("kernel.ld"), include_bytes!("kernel.ld")).unwrap();

+        let mut string_store: HashMap<String, i32> = HashMap::default();
+
+        // Keep this list of exceptions in sync with `EXCEPTION_ID_LOOKUP` in `artiq::firmware::ksupport::eh_artiq`
+        // The exceptions declared here must be defined in `artiq.coredevice.exceptions`
+        // Verify synchronization by running the test cases in `artiq.test.coredevice.test_exceptions`
+        let runtime_exception_names = [
+            "RTIOUnderflow",
+            "RTIOOverflow",
+            "RTIODestinationUnreachable",
+            "DMAError",
+            "I2CError",
+            "CacheError",
+            "SPIError",
+            "SubkernelError",
+            "0:AssertionError",
+            "0:AttributeError",
+            "0:IndexError",
+            "0:IOError",
+            "0:KeyError",
+            "0:NotImplementedError",
+            "0:OverflowError",
+            "0:RuntimeError",
+            "0:TimeoutError",
+            "0:TypeError",
+            "0:ValueError",
+            "0:ZeroDivisionError",
+            "0:LinAlgError",
+            "UnwrapNoneError",
+        ];
+
+        // Preallocate runtime exception names
+        for (i, name) in runtime_exception_names.iter().enumerate() {
+            let exn_name = if name.find(':').is_none() {
+                format!("0:artiq.coredevice.exceptions.{name}")
+            } else {
+                (*name).to_string()
+            };
+
+            let id = i32::try_from(i).unwrap();
+            string_store.insert(exn_name, id);
+        }
+
        Ok(Nac3 {
            isa,
            time_fns,
@ -1075,7 +1136,7 @@ impl Nac3 {
            top_levels: Vec::default(),
            pyid_to_def: Arc::default(),
            working_directory,
-            string_store: Arc::default(),
+            string_store: Arc::new(string_store.into()),
            exception_ids: Arc::default(),
            deferred_eval_store: DeferredEvaluationStore::new(),
            llvm_options: CodeGenLLVMOptions {
@ -1085,7 +1146,12 @@ 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();
@ -1095,14 +1161,22 @@ 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
@ -10,12 +10,14 @@ use itertools::Itertools;
 use parking_lot::RwLock;
 use pyo3::{
    types::{PyDict, PyTuple},
-    PyAny, PyObject, PyResult, Python,
+    PyAny, PyErr, PyObject, PyResult, Python,
 };

+use super::PrimitivePythonId;
 use nac3core::{
    codegen::{
-        classes::{NDArrayType, ProxyType},
+        types::{ndarray::NDArrayType, ProxyType},
+        values::ndarray::make_contiguous_strides,
        CodeGenContext, CodeGenerator,
    },
    inkwell::{
@ -37,8 +39,6 @@ use nac3core::{
    },
 };

-use super::PrimitivePythonId;
-
 pub enum PrimitiveValue {
    I32(i32),
    I64(i64),
@ -1085,18 +1085,19 @@ impl InnerResolver {
            } else {
                unreachable!("must be ndarray")
            };
-            let (ndarray_dtype, ndarray_ndims) =
-                unpack_ndarray_var_tys(&mut ctx.unifier, ndarray_ty);
+            let (ndarray_dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ndarray_ty);

+            let llvm_i8 = ctx.ctx.i8_type();
+            let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
            let llvm_usize = generator.get_size_type(ctx.ctx);
-            let ndarray_dtype_llvm_ty = ctx.get_llvm_type(generator, ndarray_dtype);
-            let ndarray_llvm_ty = NDArrayType::new(generator, ctx.ctx, ndarray_dtype_llvm_ty);
+            let llvm_ndarray = NDArrayType::from_unifier_type(generator, ctx, ndarray_ty);
+            let dtype = llvm_ndarray.element_type();

            {
                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(),
+                            llvm_ndarray.as_base_type().get_element_type().into_struct_type(),
                            Some(AddressSpace::default()),
                            &id_str,
                        )
@ -1106,40 +1107,41 @@ impl InnerResolver {
                self.global_value_ids.write().insert(id, obj.into());
            }

-            let TypeEnum::TLiteral { values, .. } = &*ctx.unifier.get_ty_immutable(ndarray_ndims)
-            else {
-                unreachable!("Expected Literal for ndarray_ndims")
-            };
-
-            let ndarray_ndims = if values.len() == 1 {
-                values[0].clone()
-            } else {
-                todo!("Unpacking literal of more than one element unimplemented")
-            };
-            let Ok(ndarray_ndims) = u64::try_from(ndarray_ndims) else {
-                unreachable!("Expected u64 value for ndarray_ndims")
-            };
+            let ndims = llvm_ndarray.ndims();

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

            // create a global for ndarray.shape and initialize it using the shape
            let shape_global = ctx.module.add_global(
-                llvm_usize.array_type(ndarray_ndims as u32),
+                llvm_usize.array_type(ndims as u32),
                Some(AddressSpace::default()),
                &(id_str.clone() + ".shape"),
            );
@ -1147,17 +1149,25 @@ impl InnerResolver {

            // Obtain the (flattened) elements of the ndarray
            let sz: usize = obj.getattr("size")?.extract()?;
-            let data: Result<Option<Vec<_>>, _> = (0..sz)
+            let data: Vec<_> = (0..sz)
                .map(|i| {
                    obj.getattr("flat")?.get_item(i).and_then(|elem| {
-                        self.get_obj_value(py, elem, ctx, generator, ndarray_dtype).map_err(|e| {
-                            super::CompileError::new_err(format!("Error getting element {i}: {e}"))
+                        let value = self
+                            .get_obj_value(py, elem, ctx, generator, ndarray_dtype)
+                            .map_err(|e| {
+                                super::CompileError::new_err(format!(
+                                    "Error getting element {i}: {e}"
+                                ))
+                            })?
+                            .unwrap();
+
+                        assert_eq!(value.get_type(), dtype);
+                        Ok(value)
                    })
                })
-                })
-                .collect();
-            let data = data?.unwrap().into_iter();
-            let data = match ndarray_dtype_llvm_ty {
+                .try_collect()?;
+            let data = data.into_iter();
+            let data = match dtype {
                BasicTypeEnum::ArrayType(ty) => {
                    ty.const_array(&data.map(BasicValueEnum::into_array_value).collect_vec())
                }
@ -1182,34 +1192,68 @@ impl InnerResolver {
            };

            // create a global for ndarray.data and initialize it using the elements
+            //
+            // NOTE: NDArray's `data` is `u8*`. Here, `data_global` is an array of `dtype`.
+            // We will have to cast it to an `u8*` later.
            let data_global = ctx.module.add_global(
-                ndarray_dtype_llvm_ty.array_type(sz as u32),
+                dtype.array_type(sz as u32),
                Some(AddressSpace::default()),
                &(id_str.clone() + ".data"),
            );
            data_global.set_initializer(&data);

+            // Get the constant itemsize.
+            let itemsize = dtype.size_of().unwrap();
+            let itemsize = itemsize.get_zero_extended_constant().unwrap();
+
+            // Create the strides needed for ndarray.strides
+            let strides = make_contiguous_strides(itemsize, ndims, &shape_u64s);
+            let strides =
+                strides.into_iter().map(|stride| llvm_usize.const_int(stride, false)).collect_vec();
+            let strides = llvm_usize.const_array(&strides);
+
+            // create a global for ndarray.strides and initialize it
+            let strides_global = ctx.module.add_global(
+                llvm_i8.array_type(ndims as u32),
+                Some(AddressSpace::default()),
+                &format!("${id_str}.strides"),
+            );
+            strides_global.set_initializer(&strides);
+
            // create a global for the ndarray object and initialize it
-            let value = ndarray_llvm_ty.as_underlying_type().const_named_struct(&[
-                llvm_usize.const_int(ndarray_ndims, false).into(),
-                shape_global
-                    .as_pointer_value()
-                    .const_cast(llvm_usize.ptr_type(AddressSpace::default()))
-                    .into(),
-                data_global
-                    .as_pointer_value()
-                    .const_cast(ndarray_dtype_llvm_ty.ptr_type(AddressSpace::default()))
-                    .into(),
+
+            // NOTE: data_global is an array of dtype, we want a `u8*`.
+            let ndarray_data = data_global.as_pointer_value();
+            let ndarray_data = ctx.builder.build_pointer_cast(ndarray_data, llvm_pi8, "").unwrap();
+
+            let ndarray_itemsize = llvm_usize.const_int(itemsize, false);
+
+            let ndarray_ndims = llvm_usize.const_int(ndims, false);
+
+            let ndarray_shape = shape_global.as_pointer_value();
+
+            let ndarray_strides = strides_global.as_pointer_value();
+
+            let ndarray = llvm_ndarray
+                .as_base_type()
+                .get_element_type()
+                .into_struct_type()
+                .const_named_struct(&[
+                    ndarray_itemsize.into(),
+                    ndarray_ndims.into(),
+                    ndarray_shape.into(),
+                    ndarray_strides.into(),
+                    ndarray_data.into(),
                ]);

-            let ndarray = ctx.module.add_global(
-                ndarray_llvm_ty.as_underlying_type(),
+            let ndarray_global = ctx.module.add_global(
+                llvm_ndarray.as_base_type().get_element_type().into_struct_type(),
                Some(AddressSpace::default()),
                &id_str,
            );
-            ndarray.set_initializer(&value);
+            ndarray_global.set_initializer(&ndarray);

-            Ok(Some(ndarray.as_pointer_value().into()))
+            Ok(Some(ndarray_global.as_pointer_value().into()))
        } else if ty_id == self.primitive_ids.tuple {
            let expected_ty_enum = ctx.unifier.get_ty_immutable(expected_ty);
            let TypeEnum::TTuple { ty, is_vararg_ctx: false } = expected_ty_enum.as_ref() else {
@ -1532,10 +1576,7 @@ impl SymbolResolver for Resolver {
        if let Some(id) = string_store.get(s) {
            *id
        } else {
-            let id = Python::with_gil(|py| -> PyResult<i32> {
-                self.0.helper.store_str.call1(py, (s,))?.extract(py)
-            })
-            .unwrap();
+            let id = i32::try_from(string_store.len()).unwrap();
            string_store.insert(s.into(), id);
            id
        }
--- 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 ref INTERNER: Mutex<Interner> =
-        Mutex::new(StringInterner::with_hasher(FxBuildHasher::default()));
-}
+static INTERNER: LazyLock<Mutex<Interner>> =
+    LazyLock::new(|| 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(
-    future_incompatible,
-    let_underscore,
-    nonstandard_style,
-    rust_2024_compatibility,
-    clippy::all
-)]
+#![deny(future_incompatible, let_underscore, nonstandard_style, 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
@ -5,6 +5,8 @@ authors = ["M-Labs"]
 edition = "2021"

 [features]
+default = ["derive"]
+derive = ["dep:nac3core_derive"]
 no-escape-analysis = []

 [dependencies]
@ -13,6 +15,7 @@ crossbeam = "0.8"
 indexmap = "2.6"
 parking_lot = "0.12"
 rayon = "1.10"
+nac3core_derive = { path = "nac3core_derive", optional = true }
 nac3parser = { path = "../nac3parser" }
 strum = "0.26"
 strum_macros = "0.26"
--- a/nac3core/build.rs
+++ b/nac3core/build.rs
@ -56,9 +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
@ -1,6 +1,15 @@
 #include "irrt/exception.hpp"
-#include "irrt/int_types.hpp"
 #include "irrt/list.hpp"
 #include "irrt/math.hpp"
-#include "irrt/ndarray.hpp"
+#include "irrt/range.hpp"
 #include "irrt/slice.hpp"
+#include "irrt/string.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"
+#include "irrt/ndarray/matmul.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.
@ -55,11 +55,14 @@ void _raise_exception_helper(ExceptionId id,
                             int64_t param2) {
    Exception<SizeT> e = {
        .id = id,
-        .filename = {.base = reinterpret_cast<const uint8_t*>(filename), .len = __builtin_strlen(filename)},
+        .filename = {.base = reinterpret_cast<void*>(const_cast<char*>(filename)),
+                     .len = static_cast<SizeT>(__builtin_strlen(filename))},
        .line = line,
        .column = 0,
-        .function = {.base = reinterpret_cast<const uint8_t*>(function), .len = __builtin_strlen(function)},
-        .msg = {.base = reinterpret_cast<const uint8_t*>(msg), .len = __builtin_strlen(msg)},
+        .function = {.base = reinterpret_cast<void*>(const_cast<char*>(function)),
+                     .len = static_cast<SizeT>(__builtin_strlen(function))},
+        .msg = {.base = reinterpret_cast<void*>(const_cast<char*>(msg)),
+                .len = static_cast<SizeT>(__builtin_strlen(msg))},
    };
    e.params[0] = param0;
    e.params[1] = param1;
@ -67,6 +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).
@ -79,4 +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
@ -8,15 +8,18 @@ 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 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
@ -2,6 +2,21 @@

 #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
@ -13,12 +28,12 @@ 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 */
@ -29,11 +44,13 @@ 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 */
@ -44,7 +61,7 @@ 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;
    }
@ -53,20 +70,24 @@ 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
@ -1,5 +1,7 @@
 #pragma once

+#include "irrt/int_types.hpp"
+
 namespace {
 // adapted from GNU Scientific Library: https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
 // need to make sure `exp >= 0` before calling this function
@ -90,4 +92,4 @@ double __nac3_j0(double x) {

    return j0(x);
 }
-}
+}  // namespace
--- a/nac3core/irrt/irrt/ndarray.hpp
+++ b/nac3core/irrt/irrt/ndarray.hpp
@ -1,144 +0,0 @@
-#pragma once
-
-#include "irrt/int_types.hpp"
-
-namespace {
-template<typename SizeT>
-SizeT __nac3_ndarray_calc_size_impl(const SizeT* list_data, SizeT list_len, SizeT begin_idx, SizeT end_idx) {
-    __builtin_assume(end_idx <= list_len);
-
-    SizeT num_elems = 1;
-    for (SizeT i = begin_idx; i < end_idx; ++i) {
-        SizeT val = list_data[i];
-        __builtin_assume(val > 0);
-        num_elems *= val;
-    }
-    return num_elems;
-}
-
-template<typename SizeT>
-void __nac3_ndarray_calc_nd_indices_impl(SizeT index, const SizeT* dims, SizeT num_dims, NDIndex* idxs) {
-    SizeT stride = 1;
-    for (SizeT dim = 0; dim < num_dims; dim++) {
-        SizeT i = num_dims - dim - 1;
-        __builtin_assume(dims[i] > 0);
-        idxs[i] = (index / stride) % dims[i];
-        stride *= dims[i];
-    }
-}
-
-template<typename SizeT>
-SizeT __nac3_ndarray_flatten_index_impl(const SizeT* dims, SizeT num_dims, const NDIndex* indices, SizeT num_indices) {
-    SizeT idx = 0;
-    SizeT stride = 1;
-    for (SizeT i = 0; i < num_dims; ++i) {
-        SizeT ri = num_dims - i - 1;
-        if (ri < num_indices) {
-            idx += stride * indices[ri];
-        }
-
-        __builtin_assume(dims[i] > 0);
-        stride *= dims[ri];
-    }
-    return idx;
-}
-
-template<typename SizeT>
-void __nac3_ndarray_calc_broadcast_impl(const SizeT* lhs_dims,
-                                        SizeT lhs_ndims,
-                                        const SizeT* rhs_dims,
-                                        SizeT rhs_ndims,
-                                        SizeT* out_dims) {
-    SizeT max_ndims = lhs_ndims > rhs_ndims ? lhs_ndims : rhs_ndims;
-
-    for (SizeT i = 0; i < max_ndims; ++i) {
-        const SizeT* lhs_dim_sz = i < lhs_ndims ? &lhs_dims[lhs_ndims - i - 1] : nullptr;
-        const SizeT* rhs_dim_sz = i < rhs_ndims ? &rhs_dims[rhs_ndims - i - 1] : nullptr;
-        SizeT* out_dim = &out_dims[max_ndims - i - 1];
-
-        if (lhs_dim_sz == nullptr) {
-            *out_dim = *rhs_dim_sz;
-        } else if (rhs_dim_sz == nullptr) {
-            *out_dim = *lhs_dim_sz;
-        } else if (*lhs_dim_sz == 1) {
-            *out_dim = *rhs_dim_sz;
-        } else if (*rhs_dim_sz == 1) {
-            *out_dim = *lhs_dim_sz;
-        } else if (*lhs_dim_sz == *rhs_dim_sz) {
-            *out_dim = *lhs_dim_sz;
-        } else {
-            __builtin_unreachable();
-        }
-    }
-}
-
-template<typename SizeT>
-void __nac3_ndarray_calc_broadcast_idx_impl(const SizeT* src_dims,
-                                            SizeT src_ndims,
-                                            const NDIndex* in_idx,
-                                            NDIndex* out_idx) {
-    for (SizeT i = 0; i < src_ndims; ++i) {
-        SizeT src_i = src_ndims - i - 1;
-        out_idx[src_i] = src_dims[src_i] == 1 ? 0 : in_idx[src_i];
-    }
-}
-}  // namespace
-
-extern "C" {
-uint32_t __nac3_ndarray_calc_size(const uint32_t* list_data, uint32_t list_len, uint32_t begin_idx, uint32_t end_idx) {
-    return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
-}
-
-uint64_t
-__nac3_ndarray_calc_size64(const uint64_t* list_data, uint64_t list_len, uint64_t begin_idx, uint64_t end_idx) {
-    return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
-}
-
-void __nac3_ndarray_calc_nd_indices(uint32_t index, const uint32_t* dims, uint32_t num_dims, NDIndex* idxs) {
-    __nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
-}
-
-void __nac3_ndarray_calc_nd_indices64(uint64_t index, const uint64_t* dims, uint64_t num_dims, NDIndex* idxs) {
-    __nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
-}
-
-uint32_t
-__nac3_ndarray_flatten_index(const uint32_t* dims, uint32_t num_dims, const NDIndex* indices, uint32_t num_indices) {
-    return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
-}
-
-uint64_t
-__nac3_ndarray_flatten_index64(const uint64_t* dims, uint64_t num_dims, const NDIndex* indices, uint64_t num_indices) {
-    return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
-}
-
-void __nac3_ndarray_calc_broadcast(const uint32_t* lhs_dims,
-                                   uint32_t lhs_ndims,
-                                   const uint32_t* rhs_dims,
-                                   uint32_t rhs_ndims,
-                                   uint32_t* out_dims) {
-    return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
-}
-
-void __nac3_ndarray_calc_broadcast64(const uint64_t* lhs_dims,
-                                     uint64_t lhs_ndims,
-                                     const uint64_t* rhs_dims,
-                                     uint64_t rhs_ndims,
-                                     uint64_t* out_dims) {
-    return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
-}
-
-void __nac3_ndarray_calc_broadcast_idx(const uint32_t* src_dims,
-                                       uint32_t src_ndims,
-                                       const NDIndex* in_idx,
-                                       NDIndex* out_idx) {
-    __nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
-}
-
-void __nac3_ndarray_calc_broadcast_idx64(const uint64_t* src_dims,
-                                         uint64_t src_ndims,
-                                         const NDIndex* in_idx,
-                                         NDIndex* out_idx) {
-    __nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
-}
-}
--- a/nac3core/irrt/irrt/ndarray/array.hpp
+++ b/nac3core/irrt/irrt/ndarray/array.hpp
@ -0,0 +1,132 @@
+#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::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 = static_cast<uint8_t*>(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 ndarray::array
+}  // namespace
+
+extern "C" {
+using namespace ndarray::array;
+
+void __nac3_ndarray_array_set_and_validate_list_shape(List<int32_t>* list, int32_t ndims, int32_t* shape) {
+    set_and_validate_list_shape(list, ndims, shape);
+}
+
+void __nac3_ndarray_array_set_and_validate_list_shape64(List<int64_t>* list, int64_t ndims, int64_t* shape) {
+    set_and_validate_list_shape(list, ndims, shape);
+}
+
+void __nac3_ndarray_array_write_list_to_array(List<int32_t>* list, NDArray<int32_t>* ndarray) {
+    write_list_to_array(list, ndarray);
+}
+
+void __nac3_ndarray_array_write_list_to_array64(List<int64_t>* list, NDArray<int64_t>* ndarray) {
+    write_list_to_array(list, ndarray);
+}
+}
--- a/nac3core/irrt/irrt/ndarray/basic.hpp
+++ b/nac3core/irrt/irrt/ndarray/basic.hpp
@ -0,0 +1,340 @@
+#pragma once
+
+#include "irrt/debug.hpp"
+#include "irrt/exception.hpp"
+#include "irrt/int_types.hpp"
+#include "irrt/ndarray/def.hpp"
+
+namespace {
+namespace ndarray::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) {
+    if (ndarray->ndims != 0) {
+        return ndarray->shape[0];
+    }
+
+    // numpy prohibits `__len__` on unsized objects
+    raise_exception(SizeT, EXN_TYPE_ERROR, "len() of unsized object", NO_PARAM, NO_PARAM, NO_PARAM);
+    __builtin_unreachable();
+}
+
+/**
+ * @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>
+void* get_pelement_by_indices(const NDArray<SizeT>* ndarray, const SizeT* indices) {
+    void* element = ndarray->data;
+    for (SizeT dim_i = 0; dim_i < ndarray->ndims; dim_i++)
+        element = static_cast<uint8_t*>(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>
+void* get_nth_pelement(const NDArray<SizeT>* ndarray, SizeT nth) {
+    void* element = ndarray->data;
+    for (SizeT i = 0; i < ndarray->ndims; i++) {
+        SizeT axis = ndarray->ndims - i - 1;
+        SizeT dim = ndarray->shape[axis];
+        element = static_cast<uint8_t*>(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, void* pelement, const void* 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 ndarray::basic
+}  // 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);
+}
+
+void* __nac3_ndarray_get_nth_pelement(const NDArray<int32_t>* ndarray, int32_t nth) {
+    return get_nth_pelement(ndarray, nth);
+}
+
+void* __nac3_ndarray_get_nth_pelement64(const NDArray<int64_t>* ndarray, int64_t nth) {
+    return get_nth_pelement(ndarray, nth);
+}
+
+void* __nac3_ndarray_get_pelement_by_indices(const NDArray<int32_t>* ndarray, int32_t* indices) {
+    return get_pelement_by_indices(ndarray, indices);
+}
+
+void* __nac3_ndarray_get_pelement_by_indices64(const NDArray<int64_t>* ndarray, int64_t* indices) {
+    return get_pelement_by_indices(ndarray, indices);
+}
+
+void __nac3_ndarray_set_strides_by_shape(NDArray<int32_t>* ndarray) {
+    set_strides_by_shape(ndarray);
+}
+
+void __nac3_ndarray_set_strides_by_shape64(NDArray<int64_t>* ndarray) {
+    set_strides_by_shape(ndarray);
+}
+
+void __nac3_ndarray_copy_data(NDArray<int32_t>* src_ndarray, NDArray<int32_t>* dst_ndarray) {
+    copy_data(src_ndarray, dst_ndarray);
+}
+
+void __nac3_ndarray_copy_data64(NDArray<int64_t>* src_ndarray, NDArray<int64_t>* dst_ndarray) {
+    copy_data(src_ndarray, dst_ndarray);
+}
+}
--- a/nac3core/irrt/irrt/ndarray/broadcast.hpp
+++ b/nac3core/irrt/irrt/ndarray/broadcast.hpp
@ -0,0 +1,165 @@
+#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::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);
+            }
+        }
+    }
+
+#ifdef IRRT_DEBUG_ASSERT
+    // Check pre-condition: `dst_ndims` must be `max([shape.ndims for shape in shapes])`
+    debug_assert_eq(SizeT, max_ndims_found, dst_ndims);
+#endif
+}
+
+/**
+ * @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 ndarray::broadcast
+}  // namespace
+
+extern "C" {
+using namespace ndarray::broadcast;
+
+void __nac3_ndarray_broadcast_to(NDArray<int32_t>* src_ndarray, NDArray<int32_t>* dst_ndarray) {
+    broadcast_to(src_ndarray, dst_ndarray);
+}
+
+void __nac3_ndarray_broadcast_to64(NDArray<int64_t>* src_ndarray, NDArray<int64_t>* dst_ndarray) {
+    broadcast_to(src_ndarray, dst_ndarray);
+}
+
+void __nac3_ndarray_broadcast_shapes(int32_t num_shapes,
+                                     const ShapeEntry<int32_t>* shapes,
+                                     int32_t dst_ndims,
+                                     int32_t* dst_shape) {
+    broadcast_shapes(num_shapes, shapes, dst_ndims, dst_shape);
+}
+
+void __nac3_ndarray_broadcast_shapes64(int64_t num_shapes,
+                                       const ShapeEntry<int64_t>* shapes,
+                                       int64_t dst_ndims,
+                                       int64_t* dst_shape) {
+    broadcast_shapes(num_shapes, shapes, dst_ndims, dst_shape);
+}
+}
--- a/nac3core/irrt/irrt/ndarray/def.hpp
+++ b/nac3core/irrt/irrt/ndarray/def.hpp
@ -0,0 +1,51 @@
+#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#pyarrayinterface
+ *
+ * Note that this implementation is based on `PyArrayInterface` rather of `PyArrayObject`. The
+ * difference between `PyArrayInterface` and `PyArrayObject` (relevant to our implementation) is
+ * that `PyArrayInterface` *has* `itemsize` and uses `void*` for its `data`, whereas `PyArrayObject`
+ * does not require `itemsize` (probably using `strides[-1]` instead) and uses `char*` for its
+ * `data`. There are also minor differences in the struct layout.
+ */
+template<typename SizeT>
+struct NDArray {
+    /**
+     * @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;
+
+    /**
+     * @brief The underlying data this `ndarray` is pointing to.
+     */
+    void* data;
+};
+}  // namespace
--- a/nac3core/irrt/irrt/ndarray/indexing.hpp
+++ b/nac3core/irrt/irrt/ndarray/indexing.hpp
@ -0,0 +1,219 @@
+#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::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 = static_cast<uint8_t*>(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 =
+                static_cast<uint8_t*>(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 ndarray::indexing
+}  // namespace
+
+extern "C" {
+using namespace ndarray::indexing;
+
+void __nac3_ndarray_index(int32_t num_indices,
+                          NDIndex* indices,
+                          NDArray<int32_t>* src_ndarray,
+                          NDArray<int32_t>* dst_ndarray) {
+    index(num_indices, indices, src_ndarray, dst_ndarray);
+}
+
+void __nac3_ndarray_index64(int64_t num_indices,
+                            NDIndex* indices,
+                            NDArray<int64_t>* src_ndarray,
+                            NDArray<int64_t>* dst_ndarray) {
+    index(num_indices, indices, src_ndarray, dst_ndarray);
+}
+}
--- a/nac3core/irrt/irrt/ndarray/iter.hpp
+++ b/nac3core/irrt/irrt/ndarray/iter.hpp
@ -0,0 +1,146 @@
+#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.
+     */
+    void* 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, void* 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 = static_cast<void*>(reinterpret_cast<uint8_t*>(element) - strides[axis] * (shape[axis] - 1));
+            } else {
+                element = static_cast<void*>(reinterpret_cast<uint8_t*>(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/matmul.hpp
+++ b/nac3core/irrt/irrt/ndarray/matmul.hpp
@ -0,0 +1,98 @@
+#pragma once
+
+#include "irrt/debug.hpp"
+#include "irrt/exception.hpp"
+#include "irrt/int_types.hpp"
+#include "irrt/ndarray/basic.hpp"
+#include "irrt/ndarray/broadcast.hpp"
+#include "irrt/ndarray/iter.hpp"
+
+// NOTE: Everything would be much easier and elegant if einsum is implemented.
+
+namespace {
+namespace ndarray::matmul {
+
+/**
+ * @brief Perform the broadcast in `np.einsum("...ij,...jk->...ik", a, b)`.
+ *
+ * Example:
+ *   Suppose      `a_shape ==      [1, 97, 4, 2]`
+ *       and      `b_shape == [99, 98,  1, 2, 5]`,
+ *
+ *   ...then  `new_a_shape == [99, 98, 97, 4, 2]`,
+ *            `new_b_shape == [99, 98, 97, 2, 5]`,
+ *      and     `dst_shape == [99, 98, 97, 4, 5]`.
+ *                             ^^^^^^^^^^  ^^^^
+ *                          (broadcasted)  (4x2 @ 2x5 => 4x5)
+ *
+ * @param a_ndims Length of `a_shape`.
+ * @param a_shape Shape of `a`.
+ * @param b_ndims Length of `b_shape`.
+ * @param b_shape Shape of `b`.
+ * @param final_ndims Should be equal to `max(a_ndims, b_ndims)`. This is the length of `new_a_shape`,
+ * `new_b_shape`, and `dst_shape` - the number of dimensions after broadcasting.
+ */
+template<typename SizeT>
+void calculate_shapes(SizeT a_ndims,
+                      SizeT* a_shape,
+                      SizeT b_ndims,
+                      SizeT* b_shape,
+                      SizeT final_ndims,
+                      SizeT* new_a_shape,
+                      SizeT* new_b_shape,
+                      SizeT* dst_shape) {
+    debug_assert(SizeT, a_ndims >= 2);
+    debug_assert(SizeT, b_ndims >= 2);
+    debug_assert_eq(SizeT, max(a_ndims, b_ndims), final_ndims);
+
+    // Check that a and b are compatible for matmul
+    if (a_shape[a_ndims - 1] != b_shape[b_ndims - 2]) {
+        // This is a custom error message. Different from NumPy.
+        raise_exception(SizeT, EXN_VALUE_ERROR, "Cannot multiply LHS (shape ?x{0}) with RHS (shape {1}x?})",
+                        a_shape[a_ndims - 1], b_shape[b_ndims - 2], NO_PARAM);
+    }
+
+    const SizeT num_entries = 2;
+    ShapeEntry<SizeT> entries[num_entries] = {{.ndims = a_ndims - 2, .shape = a_shape},
+                                              {.ndims = b_ndims - 2, .shape = b_shape}};
+
+    // TODO: Optimize this
+    ndarray::broadcast::broadcast_shapes<SizeT>(num_entries, entries, final_ndims - 2, new_a_shape);
+    ndarray::broadcast::broadcast_shapes<SizeT>(num_entries, entries, final_ndims - 2, new_b_shape);
+    ndarray::broadcast::broadcast_shapes<SizeT>(num_entries, entries, final_ndims - 2, dst_shape);
+
+    new_a_shape[final_ndims - 2] = a_shape[a_ndims - 2];
+    new_a_shape[final_ndims - 1] = a_shape[a_ndims - 1];
+    new_b_shape[final_ndims - 2] = b_shape[b_ndims - 2];
+    new_b_shape[final_ndims - 1] = b_shape[b_ndims - 1];
+    dst_shape[final_ndims - 2] = a_shape[a_ndims - 2];
+    dst_shape[final_ndims - 1] = b_shape[b_ndims - 1];
+}
+}  // namespace ndarray::matmul
+}  // namespace
+
+extern "C" {
+using namespace ndarray::matmul;
+
+void __nac3_ndarray_matmul_calculate_shapes(int32_t a_ndims,
+                                            int32_t* a_shape,
+                                            int32_t b_ndims,
+                                            int32_t* b_shape,
+                                            int32_t final_ndims,
+                                            int32_t* new_a_shape,
+                                            int32_t* new_b_shape,
+                                            int32_t* dst_shape) {
+    calculate_shapes(a_ndims, a_shape, b_ndims, b_shape, final_ndims, new_a_shape, new_b_shape, dst_shape);
+}
+
+void __nac3_ndarray_matmul_calculate_shapes64(int64_t a_ndims,
+                                              int64_t* a_shape,
+                                              int64_t b_ndims,
+                                              int64_t* b_shape,
+                                              int64_t final_ndims,
+                                              int64_t* new_a_shape,
+                                              int64_t* new_b_shape,
+                                              int64_t* dst_shape) {
+    calculate_shapes(a_ndims, a_shape, b_ndims, b_shape, final_ndims, new_a_shape, new_b_shape, dst_shape);
+}
+}
--- a/nac3core/irrt/irrt/ndarray/reshape.hpp
+++ b/nac3core/irrt/irrt/ndarray/reshape.hpp
@ -0,0 +1,97 @@
+#pragma once
+
+#include "irrt/exception.hpp"
+#include "irrt/int_types.hpp"
+#include "irrt/ndarray/def.hpp"
+
+namespace {
+namespace ndarray::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 ndarray::reshape
+}  // namespace
+
+extern "C" {
+void __nac3_ndarray_reshape_resolve_and_check_new_shape(int32_t size, int32_t new_ndims, int32_t* new_shape) {
+    ndarray::reshape::resolve_and_check_new_shape(size, new_ndims, new_shape);
+}
+
+void __nac3_ndarray_reshape_resolve_and_check_new_shape64(int64_t size, int64_t new_ndims, int64_t* new_shape) {
+    ndarray::reshape::resolve_and_check_new_shape(size, new_ndims, new_shape);
+}
+}
--- a/nac3core/irrt/irrt/ndarray/transpose.hpp
+++ b/nac3core/irrt/irrt/ndarray/transpose.hpp
@ -0,0 +1,143 @@
+#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::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 ndarray::transpose
+}  // 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
@ -0,0 +1,47 @@
+#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
@ -1,6 +1,145 @@
 #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) {
@ -14,15 +153,4 @@ 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;
-    }
-}
 }
--- a/nac3core/irrt/irrt/string.hpp
+++ b/nac3core/irrt/irrt/string.hpp
@ -0,0 +1,23 @@
+#pragma once
+
+#include "irrt/int_types.hpp"
+
+namespace {
+template<typename SizeT>
+bool __nac3_str_eq_impl(const char* str1, SizeT len1, const char* str2, SizeT len2) {
+    if (len1 != len2) {
+        return 0;
+    }
+    return __builtin_memcmp(str1, str2, static_cast<SizeT>(len1)) == 0;
+}
+}  // namespace
+
+extern "C" {
+bool nac3_str_eq(const char* str1, uint32_t len1, const char* str2, uint32_t len2) {
+    return __nac3_str_eq_impl<uint32_t>(str1, len1, str2, len2);
+}
+
+bool nac3_str_eq64(const char* str1, uint64_t len1, const char* str2, uint64_t len2) {
+    return __nac3_str_eq_impl<uint64_t>(str1, len1, str2, len2);
+}
+}
--- 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
--- a/nac3core/src/codegen/classes.rs
+++ b/nac3core/src/codegen/classes.rs
--- a/nac3core/src/codegen/expr.rs
+++ b/nac3core/src/codegen/expr.rs
--- a/nac3core/src/codegen/generator.rs
+++ b/nac3core/src/codegen/generator.rs
@ -6,7 +6,7 @@ use inkwell::{

 use nac3parser::ast::{Expr, Stmt, StrRef};

-use super::{bool_to_i1, bool_to_i8, classes::ArraySliceValue, expr::*, stmt::*, CodeGenContext};
+use super::{bool_to_i1, bool_to_i8, expr::*, stmt::*, values::ArraySliceValue, CodeGenContext};
 use crate::{
    symbol_resolver::ValueEnum,
    toplevel::{DefinitionId, TopLevelDef},
@ -17,6 +17,7 @@ pub trait CodeGenerator {
    /// Return the module name for the code generator.
    fn get_name(&self) -> &str;

+    /// Return an instance of [`IntType`] corresponding to the type of `size_t` for this instance.
    fn get_size_type<'ctx>(&self, ctx: &'ctx Context) -> IntType<'ctx>;

    /// Generate function call and returns the function return value.
--- a/nac3core/src/codegen/irrt/list.rs
+++ b/nac3core/src/codegen/irrt/list.rs
@ -0,0 +1,174 @@
+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 llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_pi8 = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
+    let llvm_i32 = ctx.ctx.i32_type();
+
+    assert_eq!(dest_idx.0.get_type(), llvm_i32);
+    assert_eq!(dest_idx.1.get_type(), llvm_i32);
+    assert_eq!(dest_idx.2.get_type(), llvm_i32);
+    assert_eq!(src_idx.0.get_type(), llvm_i32);
+    assert_eq!(src_idx.1.get_type(), llvm_i32);
+    assert_eq!(src_idx.2.get_type(), llvm_i32);
+
+    let (fun_symbol, elem_ptr_type) = ("__nac3_list_slice_assign_var_size", llvm_pi8);
+    let slice_assign_fun = {
+        let ty_vec = vec![
+            llvm_i32.into(),      // dest start idx
+            llvm_i32.into(),      // dest end idx
+            llvm_i32.into(),      // dest step
+            elem_ptr_type.into(), // dest arr ptr
+            llvm_i32.into(),      // dest arr len
+            llvm_i32.into(),      // src start idx
+            llvm_i32.into(),      // src end idx
+            llvm_i32.into(),      // src step
+            elem_ptr_type.into(), // src arr ptr
+            llvm_i32.into(),      // src arr len
+            llvm_i32.into(),      // size
+        ];
+        ctx.module.get_function(fun_symbol).unwrap_or_else(|| {
+            let fn_t = llvm_i32.fn_type(ty_vec.as_slice(), false);
+            ctx.module.add_function(fun_symbol, fn_t, None)
+        })
+    };
+
+    let zero = llvm_i32.const_zero();
+    let one = llvm_i32.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, llvm_i32, "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, llvm_i32, "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, llvm_i32, "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, llvm_usize, "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 +1,168 @@
+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 llvm_i32 = ctx.ctx.i32_type();
+    let llvm_f64 = ctx.ctx.f64_type();
+
+    assert_eq!(v.get_type(), llvm_f64);
+
+    let intrinsic_fn = ctx.module.get_function("__nac3_isinf").unwrap_or_else(|| {
+        let fn_type = llvm_i32.fn_type(&[llvm_f64.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 llvm_i32 = ctx.ctx.i32_type();
+    let llvm_f64 = ctx.ctx.f64_type();
+
+    assert_eq!(v.get_type(), llvm_f64);
+
+    let intrinsic_fn = ctx.module.get_function("__nac3_isnan").unwrap_or_else(|| {
+        let fn_type = llvm_i32.fn_type(&[llvm_f64.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();
+
+    assert_eq!(v.get_type(), llvm_f64);
+
+    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();
+
+    assert_eq!(v.get_type(), llvm_f64);
+
+    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();
+
+    assert_eq!(v.get_type(), llvm_f64);
+
+    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
@ -3,25 +3,26 @@ use inkwell::{
    context::Context,
    memory_buffer::MemoryBuffer,
    module::Module,
-    types::{BasicTypeEnum, IntType},
-    values::{BasicValue, BasicValueEnum, CallSiteValue, FloatValue, IntValue},
-    AddressSpace, IntPredicate,
+    values::{BasicValue, BasicValueEnum, IntValue},
+    IntPredicate,
 };
-use itertools::Either;

 use nac3parser::ast::Expr;

-use super::{
-    classes::{
-        ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue,
-        TypedArrayLikeAccessor, TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
-    },
-    llvm_intrinsics,
-    macros::codegen_unreachable,
-    stmt::gen_for_callback_incrementing,
-    CodeGenContext, CodeGenerator,
-};
+use super::{CodeGenContext, CodeGenerator};
 use crate::{symbol_resolver::SymbolResolver, typecheck::typedef::Type};
+pub use list::*;
+pub use math::*;
+pub use range::*;
+pub use slice::*;
+pub use string::*;
+
+mod list;
+mod math;
+pub mod ndarray;
+mod range;
+mod slice;
+mod string;

 #[must_use]
 pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver) -> Module<'ctx> {
@ -62,86 +63,25 @@ pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver)
    irrt_mod
 }

-// 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()
+/// Returns the name of a function which contains variants for 32-bit and 64-bit `size_t`.
+///
+/// - When [`TypeContext::size_type`] is 32-bits, the function name is `fn_name}`.
+/// - When [`TypeContext::size_type`] is 64-bits, the function name is `{fn_name}64`.
+#[must_use]
+pub fn get_usize_dependent_function_name<G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'_, '_>,
+    name: &str,
+) -> String {
+    let mut name = name.to_owned();
+    match generator.get_size_type(ctx.ctx).get_bit_width() {
+        32 => {}
+        64 => name.push_str("64"),
+        bit_width => {
+            panic!("Unsupported int type bit width {bit_width}, must be either 32-bits or 64-bits")
        }
-
-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()
+    }
+    name
 }

 /// NOTE: the output value of the end index of this function should be compared ***inclusively***,
@ -192,10 +132,11 @@ pub fn handle_slice_indices<'ctx, G: CodeGenerator>(
    generator: &mut G,
    length: IntValue<'ctx>,
 ) -> Result<Option<(IntValue<'ctx>, IntValue<'ctx>, IntValue<'ctx>)>, String> {
-    let int32 = ctx.ctx.i32_type();
-    let zero = int32.const_zero();
-    let one = int32.const_int(1, false);
-    let length = ctx.builder.build_int_truncate_or_bit_cast(length, int32, "leni32").unwrap();
+    let llvm_i32 = ctx.ctx.i32_type();
+
+    let zero = llvm_i32.const_zero();
+    let one = llvm_i32.const_int(1, false);
+    let length = ctx.builder.build_int_truncate_or_bit_cast(length, llvm_i32, "leni32").unwrap();
    Ok(Some(match (start, end, step) {
        (s, e, None) => (
            if let Some(s) = s.as_ref() {
@ -204,7 +145,7 @@ pub fn handle_slice_indices<'ctx, G: CodeGenerator>(
                    None => return Ok(None),
                }
            } else {
-                int32.const_zero()
+                llvm_i32.const_zero()
            },
            {
                let e = if let Some(s) = e.as_ref() {
@ -309,644 +250,3 @@ pub fn handle_slice_indices<'ctx, G: CodeGenerator>(
        }
    }))
 }
-
-/// 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(),
-    ))
-}
-
-/// 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);
-}
-
-/// 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()
-}
-
-/// 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.dim_sizes();
-
-    let indices = ctx.builder.build_array_alloca(llvm_i32, ndarray_num_dims, "").unwrap();
-
-    ctx.builder
-        .build_call(
-            ndarray_calc_nd_indices_fn,
-            &[
-                index.into(),
-                ndarray_dims.base_ptr(ctx, generator).into(),
-                ndarray_num_dims.into(),
-                indices.into(),
-            ],
-            "",
-        )
-        .unwrap();
-
-    TypedArrayLikeAdapter::from(
-        ArraySliceValue::from_ptr_val(indices, ndarray_num_dims, None),
-        Box::new(|_, v| v.into_int_value()),
-        Box::new(|_, v| v.into()),
-    )
-}
-
-fn call_ndarray_flatten_index_impl<'ctx, G, Indices>(
-    generator: &G,
-    ctx: &CodeGenContext<'ctx, '_>,
-    ndarray: NDArrayValue<'ctx>,
-    indices: &Indices,
-) -> IntValue<'ctx>
-where
-    G: CodeGenerator + ?Sized,
-    Indices: ArrayLikeIndexer<'ctx>,
-{
-    let llvm_i32 = ctx.ctx.i32_type();
-    let llvm_usize = generator.get_size_type(ctx.ctx);
-
-    let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
-    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
-
-    debug_assert_eq!(
-        IntType::try_from(indices.element_type(ctx, generator))
-            .map(IntType::get_bit_width)
-            .unwrap_or_default(),
-        llvm_i32.get_bit_width(),
-        "Expected i32 value for argument `indices` to `call_ndarray_flatten_index_impl`"
-    );
-    debug_assert_eq!(
-        indices.size(ctx, generator).get_type().get_bit_width(),
-        llvm_usize.get_bit_width(),
-        "Expected usize integer value for argument `indices_size` to `call_ndarray_flatten_index_impl`"
-    );
-
-    let ndarray_flatten_index_fn_name = match llvm_usize.get_bit_width() {
-        32 => "__nac3_ndarray_flatten_index",
-        64 => "__nac3_ndarray_flatten_index64",
-        bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
-    };
-    let ndarray_flatten_index_fn =
-        ctx.module.get_function(ndarray_flatten_index_fn_name).unwrap_or_else(|| {
-            let fn_type = llvm_usize.fn_type(
-                &[llvm_pusize.into(), llvm_usize.into(), llvm_pi32.into(), llvm_usize.into()],
-                false,
-            );
-
-            ctx.module.add_function(ndarray_flatten_index_fn_name, fn_type, None)
-        });
-
-    let ndarray_num_dims = ndarray.load_ndims(ctx);
-    let ndarray_dims = ndarray.dim_sizes();
-
-    let index = ctx
-        .builder
-        .build_call(
-            ndarray_flatten_index_fn,
-            &[
-                ndarray_dims.base_ptr(ctx, generator).into(),
-                ndarray_num_dims.into(),
-                indices.base_ptr(ctx, generator).into(),
-                indices.size(ctx, generator).into(),
-            ],
-            "",
-        )
-        .map(CallSiteValue::try_as_basic_value)
-        .map(|v| v.map_left(BasicValueEnum::into_int_value))
-        .map(Either::unwrap_left)
-        .unwrap();
-
-    index
-}
-
-/// Generates a call to `__nac3_ndarray_flatten_index`. Returns the flattened index for the
-/// multidimensional index.
-///
-/// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
-///   `NDArray`.
-/// * `indices` - The multidimensional index to compute the flattened index for.
-pub fn call_ndarray_flatten_index<'ctx, G, Index>(
-    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.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None),
-                    rhs.dim_sizes().get_typed_unchecked(ctx, generator, &idx, None),
-                )
-            };
-
-            let llvm_usize_const_one = llvm_usize.const_int(1, false);
-            let lhs_eqz = ctx
-                .builder
-                .build_int_compare(IntPredicate::EQ, lhs_dim_sz, llvm_usize_const_one, "")
-                .unwrap();
-            let rhs_eqz = ctx
-                .builder
-                .build_int_compare(IntPredicate::EQ, rhs_dim_sz, llvm_usize_const_one, "")
-                .unwrap();
-            let lhs_or_rhs_eqz = ctx.builder.build_or(lhs_eqz, rhs_eqz, "").unwrap();
-
-            let lhs_eq_rhs = ctx
-                .builder
-                .build_int_compare(IntPredicate::EQ, lhs_dim_sz, rhs_dim_sz, "")
-                .unwrap();
-
-            let is_compatible = ctx.builder.build_or(lhs_or_rhs_eqz, lhs_eq_rhs, "").unwrap();
-
-            ctx.make_assert(
-                generator,
-                is_compatible,
-                "0:ValueError",
-                "operands could not be broadcast together",
-                [None, None, None],
-                ctx.current_loc,
-            );
-
-            Ok(())
-        },
-        llvm_usize.const_int(1, false),
-    )
-    .unwrap();
-
-    let max_ndims = llvm_intrinsics::call_int_umax(ctx, lhs_ndims, rhs_ndims, None);
-    let lhs_dims = lhs.dim_sizes().base_ptr(ctx, generator);
-    let lhs_ndims = lhs.load_ndims(ctx);
-    let rhs_dims = rhs.dim_sizes().base_ptr(ctx, generator);
-    let rhs_ndims = rhs.load_ndims(ctx);
-    let out_dims = ctx.builder.build_array_alloca(llvm_usize, max_ndims, "").unwrap();
-    let out_dims = ArraySliceValue::from_ptr_val(out_dims, max_ndims, None);
-
-    ctx.builder
-        .build_call(
-            ndarray_calc_broadcast_fn,
-            &[
-                lhs_dims.into(),
-                lhs_ndims.into(),
-                rhs_dims.into(),
-                rhs_ndims.into(),
-                out_dims.base_ptr(ctx, generator).into(),
-            ],
-            "",
-        )
-        .unwrap();
-
-    TypedArrayLikeAdapter::from(
-        out_dims,
-        Box::new(|_, v| v.into_int_value()),
-        Box::new(|_, v| v.into()),
-    )
-}
-
-/// 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.dim_sizes().base_ptr(ctx, generator);
-    let array_ndims = array.load_ndims(ctx);
-    let broadcast_idx_ptr = unsafe {
-        broadcast_idx.ptr_offset_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
-    };
-
-    ctx.builder
-        .build_call(
-            ndarray_calc_broadcast_fn,
-            &[array_dims.into(), array_ndims.into(), broadcast_idx_ptr.into(), out_idx.into()],
-            "",
-        )
-        .unwrap();
-
-    TypedArrayLikeAdapter::from(
-        ArraySliceValue::from_ptr_val(out_idx, broadcast_size, None),
-        Box::new(|_, v| v.into_int_value()),
-        Box::new(|_, v| v.into()),
-    )
-}
--- a/nac3core/src/codegen/irrt/ndarray/array.rs
+++ b/nac3core/src/codegen/irrt/ndarray/array.rs
@ -0,0 +1,80 @@
+use inkwell::{types::BasicTypeEnum, values::IntValue};
+
+use crate::codegen::{
+    expr::infer_and_call_function,
+    irrt::get_usize_dependent_function_name,
+    values::{ndarray::NDArrayValue, ListValue, ProxyValue, TypedArrayLikeAccessor},
+    CodeGenContext, CodeGenerator,
+};
+
+/// Generates a call to `__nac3_ndarray_array_set_and_validate_list_shape`.
+///
+/// Deduces the target shape of the `ndarray` from the provided `list`, raising an exception if
+/// there is any issue with the resultant `shape`.
+///
+/// `shape` must be pre-allocated by the caller of this function to `[usize; ndims]`, and must be
+/// initialized to all `-1`s.
+pub fn call_nac3_ndarray_array_set_and_validate_list_shape<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    list: ListValue<'ctx>,
+    ndims: IntValue<'ctx>,
+    shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+) {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    assert_eq!(list.get_type().element_type().unwrap(), ctx.ctx.i8_type().into());
+    assert_eq!(ndims.get_type(), llvm_usize);
+    assert_eq!(
+        BasicTypeEnum::try_from(shape.element_type(ctx, generator)).unwrap(),
+        llvm_usize.into()
+    );
+
+    let name = get_usize_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_array_set_and_validate_list_shape",
+    );
+
+    infer_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[list.as_base_value().into(), ndims.into(), shape.base_ptr(ctx, generator).into()],
+        None,
+        None,
+    );
+}
+
+/// Generates a call to `__nac3_ndarray_array_write_list_to_array`.
+///
+/// Copies the contents stored in `list` into `ndarray`.
+///
+/// The `ndarray` must fulfill the following preconditions:
+///
+/// - `ndarray.itemsize`: Must be initialized.
+/// - `ndarray.ndims`: Must be initialized.
+/// - `ndarray.shape`: Must be initialized.
+/// - `ndarray.data`: Must be allocated and contiguous.
+pub fn call_nac3_ndarray_array_write_list_to_array<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    list: ListValue<'ctx>,
+    ndarray: NDArrayValue<'ctx>,
+) {
+    assert_eq!(list.get_type().element_type().unwrap(), ctx.ctx.i8_type().into());
+
+    let name = get_usize_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_array_write_list_to_array",
+    );
+
+    infer_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[list.as_base_value().into(), ndarray.as_base_value().into()],
+        None,
+        None,
+    );
+}
--- a/nac3core/src/codegen/irrt/ndarray/basic.rs
+++ b/nac3core/src/codegen/irrt/ndarray/basic.rs
@ -0,0 +1,310 @@
+use inkwell::{
+    types::BasicTypeEnum,
+    values::{BasicValueEnum, IntValue, PointerValue},
+    AddressSpace,
+};
+
+use crate::codegen::{
+    expr::{create_and_call_function, infer_and_call_function},
+    irrt::get_usize_dependent_function_name,
+    types::ProxyType,
+    values::{ndarray::NDArrayValue, ProxyValue, TypedArrayLikeAccessor},
+    CodeGenContext, CodeGenerator,
+};
+
+/// Generates a call to `__nac3_ndarray_util_assert_shape_no_negative`.
+///
+/// Assets that `shape` does not contain negative dimensions.
+pub fn call_nac3_ndarray_util_assert_shape_no_negative<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+) {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
+
+    assert_eq!(
+        BasicTypeEnum::try_from(shape.element_type(ctx, generator)).unwrap(),
+        llvm_usize.into()
+    );
+
+    let name = get_usize_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_util_assert_shape_no_negative",
+    );
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_usize.into()),
+        &[
+            (llvm_usize.into(), shape.size(ctx, generator).into()),
+            (llvm_pusize.into(), shape.base_ptr(ctx, generator).into()),
+        ],
+        None,
+        None,
+    );
+}
+
+/// Generates a call to `__nac3_ndarray_util_assert_shape_output_shape_same`.
+///
+/// Asserts that `ndarray_shape` and `output_shape` are the same in the context of writing output to
+/// an `ndarray`.
+pub fn call_nac3_ndarray_util_assert_output_shape_same<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray_shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+    output_shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+) {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
+
+    assert_eq!(
+        BasicTypeEnum::try_from(ndarray_shape.element_type(ctx, generator)).unwrap(),
+        llvm_usize.into()
+    );
+    assert_eq!(
+        BasicTypeEnum::try_from(output_shape.element_type(ctx, generator)).unwrap(),
+        llvm_usize.into()
+    );
+
+    let name = get_usize_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_util_assert_output_shape_same",
+    );
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_usize.into()),
+        &[
+            (llvm_usize.into(), ndarray_shape.size(ctx, generator).into()),
+            (llvm_pusize.into(), ndarray_shape.base_ptr(ctx, generator).into()),
+            (llvm_usize.into(), output_shape.size(ctx, generator).into()),
+            (llvm_pusize.into(), output_shape.base_ptr(ctx, generator).into()),
+        ],
+        None,
+        None,
+    );
+}
+
+/// Generates a call to `__nac3_ndarray_size`.
+///
+/// Returns a [`usize`][CodeGenerator::get_size_type] value of the number of elements of an
+/// `ndarray`, corresponding to the value of `ndarray.size`.
+pub fn call_nac3_ndarray_size<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+) -> IntValue<'ctx> {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_ndarray = ndarray.get_type().as_base_type();
+
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_size");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_usize.into()),
+        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
+        Some("size"),
+        None,
+    )
+    .map(BasicValueEnum::into_int_value)
+    .unwrap()
+}
+
+/// Generates a call to `__nac3_ndarray_nbytes`.
+///
+/// Returns a [`usize`][CodeGenerator::get_size_type] value of the number of bytes consumed by the
+/// data of the `ndarray`, corresponding to the value of `ndarray.nbytes`.
+pub fn call_nac3_ndarray_nbytes<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+) -> IntValue<'ctx> {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_ndarray = ndarray.get_type().as_base_type();
+
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_nbytes");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_usize.into()),
+        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
+        Some("nbytes"),
+        None,
+    )
+    .map(BasicValueEnum::into_int_value)
+    .unwrap()
+}
+
+/// Generates a call to `__nac3_ndarray_len`.
+///
+/// Returns a [`usize`][CodeGenerator::get_size_type] value of the size of the topmost dimension of
+/// the `ndarray`, corresponding to the value of `ndarray.__len__`.
+pub fn call_nac3_ndarray_len<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+) -> IntValue<'ctx> {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_ndarray = ndarray.get_type().as_base_type();
+
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_len");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_usize.into()),
+        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
+        Some("len"),
+        None,
+    )
+    .map(BasicValueEnum::into_int_value)
+    .unwrap()
+}
+
+/// Generates a call to `__nac3_ndarray_is_c_contiguous`.
+///
+/// Returns an `i1` value indicating whether the `ndarray` is C-contiguous.
+pub fn call_nac3_ndarray_is_c_contiguous<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+) -> IntValue<'ctx> {
+    let llvm_i1 = ctx.ctx.bool_type();
+    let llvm_ndarray = ndarray.get_type().as_base_type();
+
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_is_c_contiguous");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_i1.into()),
+        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
+        Some("is_c_contiguous"),
+        None,
+    )
+    .map(BasicValueEnum::into_int_value)
+    .unwrap()
+}
+
+/// Generates a call to `__nac3_ndarray_get_nth_pelement`.
+///
+/// Returns a [`PointerValue`] to the `index`-th flattened element of the `ndarray`.
+pub fn call_nac3_ndarray_get_nth_pelement<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+    index: IntValue<'ctx>,
+) -> PointerValue<'ctx> {
+    let llvm_i8 = ctx.ctx.i8_type();
+    let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_ndarray = ndarray.get_type().as_base_type();
+
+    assert_eq!(index.get_type(), llvm_usize);
+
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_get_nth_pelement");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_pi8.into()),
+        &[(llvm_ndarray.into(), ndarray.as_base_value().into()), (llvm_usize.into(), index.into())],
+        Some("pelement"),
+        None,
+    )
+    .map(BasicValueEnum::into_pointer_value)
+    .unwrap()
+}
+
+/// Generates a call to `__nac3_ndarray_get_pelement_by_indices`.
+///
+/// `indices` must have the same number of elements as the number of dimensions in `ndarray`.
+///
+/// Returns a [`PointerValue`] to the element indexed by `indices`.
+pub fn call_nac3_ndarray_get_pelement_by_indices<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+    indices: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+) -> PointerValue<'ctx> {
+    let llvm_i8 = ctx.ctx.i8_type();
+    let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
+    let llvm_ndarray = ndarray.get_type().as_base_type();
+
+    assert_eq!(
+        BasicTypeEnum::try_from(indices.element_type(ctx, generator)).unwrap(),
+        llvm_usize.into()
+    );
+
+    let name =
+        get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_get_pelement_by_indices");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        Some(llvm_pi8.into()),
+        &[
+            (llvm_ndarray.into(), ndarray.as_base_value().into()),
+            (llvm_pusize.into(), indices.base_ptr(ctx, generator).into()),
+        ],
+        Some("pelement"),
+        None,
+    )
+    .map(BasicValueEnum::into_pointer_value)
+    .unwrap()
+}
+
+/// Generates a call to `__nac3_ndarray_set_strides_by_shape`.
+///
+/// Sets `ndarray.strides` assuming that `ndarray.shape` is C-contiguous.
+pub fn call_nac3_ndarray_set_strides_by_shape<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    ndarray: NDArrayValue<'ctx>,
+) {
+    let llvm_ndarray = ndarray.get_type().as_base_type();
+
+    let name =
+        get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_set_strides_by_shape");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[(llvm_ndarray.into(), ndarray.as_base_value().into())],
+        None,
+        None,
+    );
+}
+
+/// Generates a call to `__nac3_ndarray_copy_data`.
+///
+/// Copies all elements from `src_ndarray` to `dst_ndarray` using their flattened views. The number
+/// of elements in `src_ndarray` must be greater than or equal to the number of elements in
+/// `dst_ndarray`.
+pub fn call_nac3_ndarray_copy_data<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    src_ndarray: NDArrayValue<'ctx>,
+    dst_ndarray: NDArrayValue<'ctx>,
+) {
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_copy_data");
+
+    infer_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[src_ndarray.as_base_value().into(), dst_ndarray.as_base_value().into()],
+        None,
+        None,
+    );
+}
--- a/nac3core/src/codegen/irrt/ndarray/broadcast.rs
+++ b/nac3core/src/codegen/irrt/ndarray/broadcast.rs
@ -0,0 +1,82 @@
+use inkwell::values::IntValue;
+
+use crate::codegen::{
+    expr::infer_and_call_function,
+    irrt::get_usize_dependent_function_name,
+    types::{ndarray::ShapeEntryType, ProxyType},
+    values::{
+        ndarray::NDArrayValue, ArrayLikeValue, ArraySliceValue, ProxyValue, TypedArrayLikeAccessor,
+        TypedArrayLikeMutator,
+    },
+    CodeGenContext, CodeGenerator,
+};
+
+/// Generates a call to `__nac3_ndarray_broadcast_to`.
+///
+/// Attempts to broadcast `src_ndarray` to the new shape defined by `dst_ndarray`.
+///
+/// `dst_ndarray` must meet the following preconditions:
+///
+/// - `dst_ndarray.ndims` must be initialized and matching the length of `dst_ndarray.shape`.
+/// - `dst_ndarray.shape` must be initialized and contains the target broadcast shape.
+/// - `dst_ndarray.strides` must be allocated and may contain uninitialized values.
+pub fn call_nac3_ndarray_broadcast_to<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    src_ndarray: NDArrayValue<'ctx>,
+    dst_ndarray: NDArrayValue<'ctx>,
+) {
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_broadcast_to");
+    infer_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[src_ndarray.as_base_value().into(), dst_ndarray.as_base_value().into()],
+        None,
+        None,
+    );
+}
+
+/// Generates a call to `__nac3_ndarray_broadcast_shapes`.
+///
+/// Attempts to calculate the resultant shape from broadcasting all shapes in `shape_entries`,
+/// writing the result to `dst_shape`.
+pub fn call_nac3_ndarray_broadcast_shapes<'ctx, G, Shape>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    num_shape_entries: IntValue<'ctx>,
+    shape_entries: ArraySliceValue<'ctx>,
+    dst_ndims: IntValue<'ctx>,
+    dst_shape: &Shape,
+) where
+    G: CodeGenerator + ?Sized,
+    Shape: TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>
+        + TypedArrayLikeMutator<'ctx, G, IntValue<'ctx>>,
+{
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+
+    assert_eq!(num_shape_entries.get_type(), llvm_usize);
+    assert!(ShapeEntryType::is_type(
+        generator,
+        ctx.ctx,
+        shape_entries.base_ptr(ctx, generator).get_type()
+    )
+    .is_ok());
+    assert_eq!(dst_ndims.get_type(), llvm_usize);
+    assert_eq!(dst_shape.element_type(ctx, generator), llvm_usize.into());
+
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_broadcast_shapes");
+    infer_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[
+            num_shape_entries.into(),
+            shape_entries.base_ptr(ctx, generator).into(),
+            dst_ndims.into(),
+            dst_shape.base_ptr(ctx, generator).into(),
+        ],
+        None,
+        None,
+    );
+}
--- a/nac3core/src/codegen/irrt/ndarray/indexing.rs
+++ b/nac3core/src/codegen/irrt/ndarray/indexing.rs
@ -0,0 +1,34 @@
+use crate::codegen::{
+    expr::infer_and_call_function,
+    irrt::get_usize_dependent_function_name,
+    values::{ndarray::NDArrayValue, ArrayLikeValue, ArraySliceValue, ProxyValue},
+    CodeGenContext, CodeGenerator,
+};
+
+/// Generates a call to `__nac3_ndarray_index`.
+///
+/// Performs [basic indexing](https://numpy.org/doc/stable/user/basics.indexing.html#basic-indexing)
+/// on `src_ndarray` using `indices`, writing the result to `dst_ndarray`, corresponding to the
+/// operation `dst_ndarray = src_ndarray[indices]`.
+pub fn call_nac3_ndarray_index<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    indices: ArraySliceValue<'ctx>,
+    src_ndarray: NDArrayValue<'ctx>,
+    dst_ndarray: NDArrayValue<'ctx>,
+) {
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_index");
+    infer_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[
+            indices.size(ctx, generator).into(),
+            indices.base_ptr(ctx, generator).into(),
+            src_ndarray.as_base_value().into(),
+            dst_ndarray.as_base_value().into(),
+        ],
+        None,
+        None,
+    );
+}
--- a/nac3core/src/codegen/irrt/ndarray/iter.rs
+++ b/nac3core/src/codegen/irrt/ndarray/iter.rs
@ -0,0 +1,86 @@
+use inkwell::{
+    types::BasicTypeEnum,
+    values::{BasicValueEnum, IntValue},
+    AddressSpace,
+};
+
+use crate::codegen::{
+    expr::{create_and_call_function, infer_and_call_function},
+    irrt::get_usize_dependent_function_name,
+    types::ProxyType,
+    values::{
+        ndarray::{NDArrayValue, NDIterValue},
+        ProxyValue, TypedArrayLikeAccessor,
+    },
+    CodeGenContext, CodeGenerator,
+};
+
+/// Generates a call to `__nac3_nditer_initialize`.
+///
+/// Initializes the `iter` object.
+pub fn call_nac3_nditer_initialize<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    iter: NDIterValue<'ctx>,
+    ndarray: NDArrayValue<'ctx>,
+    indices: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+) {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
+
+    assert_eq!(
+        BasicTypeEnum::try_from(indices.element_type(ctx, generator)).unwrap(),
+        llvm_usize.into()
+    );
+
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_nditer_initialize");
+
+    create_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[
+            (iter.get_type().as_base_type().into(), iter.as_base_value().into()),
+            (ndarray.get_type().as_base_type().into(), ndarray.as_base_value().into()),
+            (llvm_pusize.into(), indices.base_ptr(ctx, generator).into()),
+        ],
+        None,
+        None,
+    );
+}
+
+/// Generates a call to `__nac3_nditer_initialize_has_element`.
+///
+/// Returns an `i1` value indicating whether there are elements left to traverse for the `iter`
+/// object.
+pub fn call_nac3_nditer_has_element<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    iter: NDIterValue<'ctx>,
+) -> IntValue<'ctx> {
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_nditer_has_element");
+
+    infer_and_call_function(
+        ctx,
+        &name,
+        Some(ctx.ctx.bool_type().into()),
+        &[iter.as_base_value().into()],
+        None,
+        None,
+    )
+    .map(BasicValueEnum::into_int_value)
+    .unwrap()
+}
+
+/// Generates a call to `__nac3_nditer_next`.
+///
+/// Moves `iter` to point to the next element.
+pub fn call_nac3_nditer_next<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    iter: NDIterValue<'ctx>,
+) {
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_nditer_next");
+
+    infer_and_call_function(ctx, &name, None, &[iter.as_base_value().into()], None, None);
+}
--- a/nac3core/src/codegen/irrt/ndarray/matmul.rs
+++ b/nac3core/src/codegen/irrt/ndarray/matmul.rs
@ -0,0 +1,66 @@
+use inkwell::{types::BasicTypeEnum, values::IntValue};
+
+use crate::codegen::{
+    expr::infer_and_call_function, irrt::get_usize_dependent_function_name,
+    values::TypedArrayLikeAccessor, CodeGenContext, CodeGenerator,
+};
+
+/// Generates a call to `__nac3_ndarray_matmul_calculate_shapes`.
+///
+/// Calculates the broadcasted shapes for `a`, `b`, and the `ndarray` holding the final values of
+/// `a @ b`.
+#[allow(clippy::too_many_arguments)]
+pub fn call_nac3_ndarray_matmul_calculate_shapes<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    a_shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+    b_shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+    final_ndims: IntValue<'ctx>,
+    new_a_shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+    new_b_shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+    dst_shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+) {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+
+    assert_eq!(
+        BasicTypeEnum::try_from(a_shape.element_type(ctx, generator)).unwrap(),
+        llvm_usize.into()
+    );
+    assert_eq!(
+        BasicTypeEnum::try_from(b_shape.element_type(ctx, generator)).unwrap(),
+        llvm_usize.into()
+    );
+    assert_eq!(
+        BasicTypeEnum::try_from(new_a_shape.element_type(ctx, generator)).unwrap(),
+        llvm_usize.into()
+    );
+    assert_eq!(
+        BasicTypeEnum::try_from(new_b_shape.element_type(ctx, generator)).unwrap(),
+        llvm_usize.into()
+    );
+    assert_eq!(
+        BasicTypeEnum::try_from(dst_shape.element_type(ctx, generator)).unwrap(),
+        llvm_usize.into()
+    );
+
+    let name =
+        get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_matmul_calculate_shapes");
+
+    infer_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[
+            a_shape.size(ctx, generator).into(),
+            a_shape.base_ptr(ctx, generator).into(),
+            b_shape.size(ctx, generator).into(),
+            b_shape.base_ptr(ctx, generator).into(),
+            final_ndims.into(),
+            new_a_shape.base_ptr(ctx, generator).into(),
+            new_b_shape.base_ptr(ctx, generator).into(),
+            dst_shape.base_ptr(ctx, generator).into(),
+        ],
+        None,
+        None,
+    );
+}
--- a/nac3core/src/codegen/irrt/ndarray/mod.rs
+++ b/nac3core/src/codegen/irrt/ndarray/mod.rs
@ -0,0 +1,17 @@
+pub use array::*;
+pub use basic::*;
+pub use broadcast::*;
+pub use indexing::*;
+pub use iter::*;
+pub use matmul::*;
+pub use reshape::*;
+pub use transpose::*;
+
+mod array;
+mod basic;
+mod broadcast;
+mod indexing;
+mod iter;
+mod matmul;
+mod reshape;
+mod transpose;
--- a/nac3core/src/codegen/irrt/ndarray/reshape.rs
+++ b/nac3core/src/codegen/irrt/ndarray/reshape.rs
@ -0,0 +1,40 @@
+use inkwell::values::IntValue;
+
+use crate::codegen::{
+    expr::infer_and_call_function,
+    irrt::get_usize_dependent_function_name,
+    values::{ArrayLikeValue, ArraySliceValue},
+    CodeGenContext, CodeGenerator,
+};
+
+/// Generates a call to `__nac3_ndarray_reshape_resolve_and_check_new_shape`.
+///
+/// Resolves unknown dimensions in `new_shape` for `numpy.reshape(<ndarray>, new_shape)`, raising an
+/// assertion if multiple dimensions are unknown (`-1`).
+pub fn call_nac3_ndarray_reshape_resolve_and_check_new_shape<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    size: IntValue<'ctx>,
+    new_ndims: IntValue<'ctx>,
+    new_shape: ArraySliceValue<'ctx>,
+) {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+
+    assert_eq!(size.get_type(), llvm_usize);
+    assert_eq!(new_ndims.get_type(), llvm_usize);
+    assert_eq!(new_shape.element_type(ctx, generator), llvm_usize.into());
+
+    let name = get_usize_dependent_function_name(
+        generator,
+        ctx,
+        "__nac3_ndarray_reshape_resolve_and_check_new_shape",
+    );
+    infer_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[size.into(), new_ndims.into(), new_shape.base_ptr(ctx, generator).into()],
+        None,
+        None,
+    );
+}
--- a/nac3core/src/codegen/irrt/ndarray/transpose.rs
+++ b/nac3core/src/codegen/irrt/ndarray/transpose.rs
@ -0,0 +1,48 @@
+use inkwell::{values::IntValue, AddressSpace};
+
+use crate::codegen::{
+    expr::infer_and_call_function,
+    irrt::get_usize_dependent_function_name,
+    values::{ndarray::NDArrayValue, ProxyValue, TypedArrayLikeAccessor},
+    CodeGenContext, CodeGenerator,
+};
+
+/// Generates a call to `__nac3_ndarray_transpose`.
+///
+/// Creates a transpose view of `src_ndarray` and writes the result to `dst_ndarray`.
+///
+/// `dst_ndarray` must fulfill the following preconditions:
+///
+/// - `dst_ndarray.ndims` must be initialized and must be equal to `src_ndarray.ndims`.
+/// - `dst_ndarray.shape` must be allocated and may contain uninitialized values.
+/// - `dst_ndarray.strides` must be allocated and may contain uninitialized values.
+pub fn call_nac3_ndarray_transpose<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    src_ndarray: NDArrayValue<'ctx>,
+    dst_ndarray: NDArrayValue<'ctx>,
+    axes: Option<&impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>>,
+) {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+
+    assert!(axes.is_none_or(|axes| axes.size(ctx, generator).get_type() == llvm_usize));
+    assert!(axes.is_none_or(|axes| axes.element_type(ctx, generator) == llvm_usize.into()));
+
+    let name = get_usize_dependent_function_name(generator, ctx, "__nac3_ndarray_transpose");
+    infer_and_call_function(
+        ctx,
+        &name,
+        None,
+        &[
+            src_ndarray.as_base_value().into(),
+            dst_ndarray.as_base_value().into(),
+            axes.map_or(llvm_usize.const_zero(), |axes| axes.size(ctx, generator)).into(),
+            axes.map_or(llvm_usize.ptr_type(AddressSpace::default()).const_null(), |axes| {
+                axes.base_ptr(ctx, generator)
+            })
+            .into(),
+        ],
+        None,
+        None,
+    );
+}
--- a/nac3core/src/codegen/irrt/range.rs
+++ b/nac3core/src/codegen/irrt/range.rs
@ -0,0 +1,56 @@
+use inkwell::{
+    values::{BasicValueEnum, CallSiteValue, IntValue},
+    IntPredicate,
+};
+use itertools::Either;
+
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+/// Invokes the `__nac3_range_slice_len` in IRRT.
+///
+/// - `start`: The `i32` start value for the slice.
+/// - `end`: The `i32` end value for the slice.
+/// - `step`: The `i32` step value for the slice.
+///
+/// Returns an `i32` value of the length of the slice.
+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 llvm_i32 = ctx.ctx.i32_type();
+
+    assert_eq!(start.get_type(), llvm_i32);
+    assert_eq!(end.get_type(), llvm_i32);
+    assert_eq!(step.get_type(), llvm_i32);
+
+    let len_func = ctx.module.get_function(SYMBOL).unwrap_or_else(|| {
+        let fn_t = llvm_i32.fn_type(&[llvm_i32.into(), llvm_i32.into(), llvm_i32.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/irrt/slice.rs
+++ b/nac3core/src/codegen/irrt/slice.rs
@ -0,0 +1,39 @@
+use inkwell::values::{BasicValueEnum, CallSiteValue, IntValue};
+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(),
+    ))
+}
--- a/nac3core/src/codegen/irrt/string.rs
+++ b/nac3core/src/codegen/irrt/string.rs
@ -0,0 +1,46 @@
+use inkwell::values::{BasicValueEnum, CallSiteValue, IntValue, PointerValue};
+use itertools::Either;
+
+use super::get_usize_dependent_function_name;
+use crate::codegen::{CodeGenContext, CodeGenerator};
+
+/// Generates a call to string equality comparison. Returns an `i1` representing whether the strings are equal.
+pub fn call_string_eq<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &CodeGenContext<'ctx, '_>,
+    str1_ptr: PointerValue<'ctx>,
+    str1_len: IntValue<'ctx>,
+    str2_ptr: PointerValue<'ctx>,
+    str2_len: IntValue<'ctx>,
+) -> IntValue<'ctx> {
+    let llvm_i1 = ctx.ctx.bool_type();
+
+    let func_name = get_usize_dependent_function_name(generator, ctx, "nac3_str_eq");
+
+    let func = ctx.module.get_function(&func_name).unwrap_or_else(|| {
+        ctx.module.add_function(
+            &func_name,
+            llvm_i1.fn_type(
+                &[
+                    str1_ptr.get_type().into(),
+                    str1_len.get_type().into(),
+                    str2_ptr.get_type().into(),
+                    str2_len.get_type().into(),
+                ],
+                false,
+            ),
+            None,
+        )
+    });
+
+    ctx.builder
+        .build_call(
+            func,
+            &[str1_ptr.into(), str1_len.into(), str2_ptr.into(), str2_len.into()],
+            "str_eq_call",
+        )
+        .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
@ -1,7 +1,6 @@
 use inkwell::{
-    context::Context,
    intrinsics::Intrinsic,
-    types::{AnyTypeEnum::IntType, FloatType},
+    types::AnyTypeEnum::IntType,
    values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue, PointerValue},
    AddressSpace,
 };
@ -9,34 +8,6 @@ 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 {
-    // Standard LLVM floating-point types
-    if ft == ctx.f16_type() {
-        return "f16";
-    }
-    if ft == ctx.f32_type() {
-        return "f32";
-    }
-    if ft == ctx.f64_type() {
-        return "f64";
-    }
-    if ft == ctx.f128_type() {
-        return "f128";
-    }
-
-    // Non-standard floating-point types
-    if ft == ctx.x86_f80_type() {
-        return "f80";
-    }
-    if ft == ctx.ppc_f128_type() {
-        return "ppcf128";
-    }
-
-    unreachable!()
-}
-
 /// Invokes the [`llvm.va_start`](https://llvm.org/docs/LangRef.html#llvm-va-start-intrinsic)
 /// intrinsic.
 pub fn call_va_start<'ctx>(ctx: &CodeGenContext<'ctx, '_>, arglist: PointerValue<'ctx>) {
@ -54,7 +25,7 @@ pub fn call_va_start<'ctx>(ctx: &CodeGenContext<'ctx, '_>, arglist: PointerValue
    ctx.builder.build_call(intrinsic_fn, &[arglist.into()], "").unwrap();
 }

-/// Invokes the [`llvm.va_start`](https://llvm.org/docs/LangRef.html#llvm-va-start-intrinsic)
+/// Invokes the [`llvm.va_end`](https://llvm.org/docs/LangRef.html#llvm-va-end-intrinsic)
 /// intrinsic.
 pub fn call_va_end<'ctx>(ctx: &CodeGenContext<'ctx, '_>, arglist: PointerValue<'ctx>) {
    const FN_NAME: &str = "llvm.va_end";
@ -201,6 +172,49 @@ pub fn call_memcpy_generic<'ctx>(
    call_memcpy(ctx, dest, src, len, is_volatile);
 }

+/// Invokes the `llvm.memcpy` intrinsic.
+///
+/// Unlike [`call_memcpy`], this function accepts any type of pointer value. If `dest` or `src` is
+/// not a pointer to an integer, the pointer(s) will be cast to `i8*` before invoking `memcpy`.
+/// Moreover, `len` now refers to the number of elements to copy (rather than number of bytes to
+/// copy).
+pub fn call_memcpy_generic_array<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    dest: PointerValue<'ctx>,
+    src: PointerValue<'ctx>,
+    len: IntValue<'ctx>,
+    is_volatile: IntValue<'ctx>,
+) {
+    let llvm_i8 = ctx.ctx.i8_type();
+    let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
+    let llvm_sizeof_expr_t = llvm_i8.size_of().get_type();
+
+    let dest_elem_t = dest.get_type().get_element_type();
+    let src_elem_t = src.get_type().get_element_type();
+
+    let dest = if matches!(dest_elem_t, IntType(t) if t.get_bit_width() == 8) {
+        dest
+    } else {
+        ctx.builder
+            .build_bit_cast(dest, llvm_p0i8, "")
+            .map(BasicValueEnum::into_pointer_value)
+            .unwrap()
+    };
+    let src = if matches!(src_elem_t, IntType(t) if t.get_bit_width() == 8) {
+        src
+    } else {
+        ctx.builder
+            .build_bit_cast(src, llvm_p0i8, "")
+            .map(BasicValueEnum::into_pointer_value)
+            .unwrap()
+    };
+
+    let len = ctx.builder.build_int_z_extend_or_bit_cast(len, llvm_sizeof_expr_t, "").unwrap();
+    let len = ctx.builder.build_int_mul(len, src_elem_t.size_of().unwrap(), "").unwrap();
+
+    call_memcpy(ctx, dest, src, len, is_volatile);
+}
+
 /// Macro to find and generate build call for llvm intrinsic (body of llvm intrinsic function)
 ///
 /// Arguments:
@ -343,3 +357,25 @@ pub fn call_float_powi<'ctx>(
        .map(Either::unwrap_left)
        .unwrap()
 }
+
+/// Invokes the [`llvm.ctpop`](https://llvm.org/docs/LangRef.html#llvm-ctpop-intrinsic) intrinsic.
+pub fn call_int_ctpop<'ctx>(
+    ctx: &CodeGenContext<'ctx, '_>,
+    src: IntValue<'ctx>,
+    name: Option<&str>,
+) -> IntValue<'ctx> {
+    const FN_NAME: &str = "llvm.ctpop";
+
+    let llvm_src_t = src.get_type();
+
+    let intrinsic_fn = Intrinsic::find(FN_NAME)
+        .and_then(|intrinsic| intrinsic.get_declaration(&ctx.module, &[llvm_src_t.into()]))
+        .unwrap();
+
+    ctx.builder
+        .build_call(intrinsic_fn, &[src.into()], name.unwrap_or_default())
+        .map(CallSiteValue::try_as_basic_value)
+        .map(|v| v.map_left(BasicValueEnum::into_int_value))
+        .map(Either::unwrap_left)
+        .unwrap()
+}
--- a/nac3core/src/codegen/mod.rs
+++ b/nac3core/src/codegen/mod.rs
@ -30,18 +30,21 @@ use nac3parser::ast::{Location, Stmt, StrRef};

 use crate::{
    symbol_resolver::{StaticValue, SymbolResolver},
-    toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, TopLevelContext, TopLevelDef},
+    toplevel::{
+        helper::{extract_ndims, PrimDef},
+        numpy::unpack_ndarray_var_tys,
+        TopLevelContext, TopLevelDef,
+    },
    typecheck::{
        type_inferencer::{CodeLocation, PrimitiveStore},
        typedef::{CallId, FuncArg, Type, TypeEnum, Unifier},
    },
 };
-use classes::{ListType, NDArrayType, ProxyType, RangeType};
 use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
 pub use generator::{CodeGenerator, DefaultCodeGenerator};
+use types::{ndarray::NDArrayType, ListType, ProxyType, RangeType, TupleType};

 pub mod builtin_fns;
-pub mod classes;
 pub mod concrete_type;
 pub mod expr;
 pub mod extern_fns;
@ -50,6 +53,8 @@ pub mod irrt;
 pub mod llvm_intrinsics;
 pub mod numpy;
 pub mod stmt;
+pub mod types;
+pub mod values;

 #[cfg(test)]
 mod test;
@ -509,12 +514,13 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
                        }

                        TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
-                            let (dtype, _) = unpack_ndarray_var_tys(unifier, ty);
+                            let (dtype, ndims) = unpack_ndarray_var_tys(unifier, ty);
+                            let ndims = extract_ndims(unifier, ndims);
                            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()
+                            NDArrayType::new(generator, ctx, element_type, ndims).as_base_type().into()
                        }

                        _ => unreachable!(
@ -568,7 +574,7 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
                        get_llvm_type(ctx, module, generator, unifier, top_level, type_cache, *ty)
                    })
                    .collect_vec();
-                ctx.struct_type(&fields, false).into()
+                TupleType::new(generator, ctx, &fields).as_base_type().into()
            }
            TVirtual { .. } => unimplemented!(),
            _ => unreachable!("{}", ty_enum.get_type_name()),
@ -1118,3 +1124,106 @@ fn gen_in_range_check<'ctx>(
 fn get_va_count_arg_name(arg_name: StrRef) -> StrRef {
    format!("__{}_va_count", &arg_name).into()
 }
+
+/// Returns the alignment of the type.
+///
+/// This is necessary as `get_alignment` is not implemented as part of [`BasicType`].
+pub fn get_type_alignment<'ctx>(ty: impl Into<BasicTypeEnum<'ctx>>) -> IntValue<'ctx> {
+    match ty.into() {
+        BasicTypeEnum::ArrayType(ty) => ty.get_alignment(),
+        BasicTypeEnum::FloatType(ty) => ty.get_alignment(),
+        BasicTypeEnum::IntType(ty) => ty.get_alignment(),
+        BasicTypeEnum::PointerType(ty) => ty.get_alignment(),
+        BasicTypeEnum::StructType(ty) => ty.get_alignment(),
+        BasicTypeEnum::VectorType(ty) => ty.get_alignment(),
+    }
+}
+
+/// Inserts an `alloca` instruction with allocation `size` given in bytes and the alignment of the
+/// given type.
+///
+/// The returned [`PointerValue`] will have a type of `i8*`, a size of at least `size`, and will be
+/// aligned with the alignment of `align_ty`.
+pub fn type_aligned_alloca<'ctx, G: CodeGenerator + ?Sized>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    align_ty: impl Into<BasicTypeEnum<'ctx>>,
+    size: IntValue<'ctx>,
+    name: Option<&str>,
+) -> PointerValue<'ctx> {
+    /// Round `val` up to its modulo `power_of_two`.
+    fn round_up<'ctx>(
+        ctx: &CodeGenContext<'ctx, '_>,
+        val: IntValue<'ctx>,
+        power_of_two: IntValue<'ctx>,
+    ) -> IntValue<'ctx> {
+        debug_assert_eq!(
+            val.get_type().get_bit_width(),
+            power_of_two.get_type().get_bit_width(),
+            "`val` ({}) and `power_of_two` ({}) must be the same type",
+            val.get_type(),
+            power_of_two.get_type(),
+        );
+
+        let llvm_val_t = val.get_type();
+
+        let max_rem =
+            ctx.builder.build_int_sub(power_of_two, llvm_val_t.const_int(1, false), "").unwrap();
+        ctx.builder
+            .build_and(
+                ctx.builder.build_int_add(val, max_rem, "").unwrap(),
+                ctx.builder.build_not(max_rem, "").unwrap(),
+                "",
+            )
+            .unwrap()
+    }
+
+    let llvm_i8 = ctx.ctx.i8_type();
+    let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let align_ty = align_ty.into();
+
+    let size = ctx.builder.build_int_truncate_or_bit_cast(size, llvm_usize, "").unwrap();
+
+    debug_assert_eq!(
+        size.get_type().get_bit_width(),
+        llvm_usize.get_bit_width(),
+        "Expected size_t ({}) for parameter `size` of `aligned_alloca`, got {}",
+        llvm_usize,
+        size.get_type(),
+    );
+
+    let alignment = get_type_alignment(align_ty);
+    let alignment = ctx.builder.build_int_truncate_or_bit_cast(alignment, llvm_usize, "").unwrap();
+
+    if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
+        let alignment_bitcount = llvm_intrinsics::call_int_ctpop(ctx, alignment, None);
+
+        ctx.make_assert(
+            generator,
+            ctx.builder
+                .build_int_compare(
+                    IntPredicate::EQ,
+                    alignment_bitcount,
+                    alignment_bitcount.get_type().const_int(1, false),
+                    "",
+                )
+                .unwrap(),
+            "0:AssertionError",
+            "Expected power-of-two alignment for aligned_alloca, got {0}",
+            [Some(alignment), None, None],
+            ctx.current_loc,
+        );
+    }
+
+    let buffer_size = round_up(ctx, size, alignment);
+    let aligned_slices = ctx.builder.build_int_unsigned_div(buffer_size, alignment, "").unwrap();
+
+    // Just to be absolutely sure, alloca in [i8 x alignment] slices
+    let buffer = ctx.builder.build_array_alloca(align_ty, aligned_slices, "").unwrap();
+
+    ctx.builder
+        .build_bit_cast(buffer, llvm_pi8, name.unwrap_or_default())
+        .map(BasicValueEnum::into_pointer_value)
+        .unwrap()
+}
--- a/nac3core/src/codegen/numpy.rs
+++ b/nac3core/src/codegen/numpy.rs
--- a/nac3core/src/codegen/stmt.rs
+++ b/nac3core/src/codegen/stmt.rs
@ -12,11 +12,15 @@ use nac3parser::ast::{
 };

 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,
+    types::ndarray::NDArrayType,
+    values::{
+        ndarray::{RustNDIndex, ScalarOrNDArray},
+        ArrayLikeIndexer, ArraySliceValue, ListValue, ProxyValue, RangeValue,
+    },
    CodeGenContext, CodeGenerator,
 };
 use crate::{
@ -310,7 +314,7 @@ 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
@ -331,7 +335,7 @@ 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(
@ -411,7 +415,52 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
            if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
        {
            // Handle NDArray item assignment
-            todo!("ndarray subscript assignment is not yet implemented");
+            // Process target
+            let target = generator
+                .gen_expr(ctx, target)?
+                .unwrap()
+                .to_basic_value_enum(ctx, generator, target_ty)?;
+
+            // Process key
+            let key = RustNDIndex::from_subscript_expr(generator, ctx, key)?;
+
+            // Process value
+            let value = value.to_basic_value_enum(ctx, generator, 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 = NDArrayType::from_unifier_type(generator, ctx, target_ty)
+                .map_value(target.into_pointer_value(), None);
+            let target = target.index(generator, ctx, &key);
+
+            let value = ScalarOrNDArray::from_value(generator, ctx, (value_ty, value))
+                .to_ndarray(generator, ctx);
+
+            let broadcast_ndims =
+                [target.get_type().ndims(), value.get_type().ndims()].into_iter().max().unwrap();
+            let broadcast_result = NDArrayType::new(
+                generator,
+                ctx.ctx,
+                value.get_type().element_type(),
+                broadcast_ndims,
+            )
+            .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));
@ -463,7 +512,8 @@ 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
--- a/nac3core/src/codegen/test.rs
+++ b/nac3core/src/codegen/test.rs
@ -16,8 +16,8 @@ use nac3parser::{
 use parking_lot::RwLock;

 use super::{
-    classes::{ListType, NDArrayType, ProxyType, RangeType},
    concrete_type::ConcreteTypeStore,
+    types::{ndarray::NDArrayType, ListType, ProxyType, RangeType},
    CodeGenContext, CodeGenLLVMOptions, CodeGenTargetMachineOptions, CodeGenTask, CodeGenerator,
    DefaultCodeGenerator, WithCall, WorkerRegistry,
 };
@ -36,7 +36,6 @@ use crate::{
 struct Resolver {
    id_to_type: HashMap<StrRef, Type>,
    id_to_def: RwLock<HashMap<StrRef, DefinitionId>>,
-    class_names: HashMap<StrRef, Type>,
 }

 impl Resolver {
@ -104,11 +103,9 @@ fn test_primitives() {
    let top_level = Arc::new(composer.make_top_level_context());
    unifier.top_level = Some(top_level.clone());

-    let resolver = Arc::new(Resolver {
-        id_to_type: HashMap::new(),
-        id_to_def: RwLock::new(HashMap::new()),
-        class_names: HashMap::default(),
-    }) as Arc<dyn SymbolResolver + Send + Sync>;
+    let resolver =
+        Arc::new(Resolver { id_to_type: HashMap::new(), id_to_def: RwLock::new(HashMap::new()) })
+            as Arc<dyn SymbolResolver + Send + Sync>;

    let threads = vec![DefaultCodeGenerator::new("test".into(), 32).into()];
    let signature = FunSignature {
@ -298,11 +295,7 @@ fn test_simple_call() {
        loc: None,
    })));

-    let resolver = Resolver {
-        id_to_type: HashMap::new(),
-        id_to_def: RwLock::new(HashMap::new()),
-        class_names: HashMap::default(),
-    };
+    let resolver = Resolver { id_to_type: HashMap::new(), id_to_def: RwLock::new(HashMap::new()) };
    resolver.add_id_def("foo".into(), DefinitionId(foo_id));
    let resolver = Arc::new(resolver) as Arc<dyn SymbolResolver + Send + Sync>;

@ -452,7 +445,7 @@ 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]
@ -460,7 +453,7 @@ 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]
@ -471,6 +464,6 @@ fn test_classes_ndarray_type_new() {
    let llvm_i32 = ctx.i32_type();
    let llvm_usize = generator.get_size_type(&ctx);

-    let llvm_ndarray = NDArrayType::new(&generator, &ctx, llvm_i32.into());
-    assert!(NDArrayType::is_type(llvm_ndarray.as_base_type(), llvm_usize).is_ok());
+    let llvm_ndarray = NDArrayType::new(&generator, &ctx, llvm_i32.into(), 2);
+    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 +1,357 @@
+use inkwell::{
+    context::{AsContextRef, Context},
+    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
+    values::{IntValue, PointerValue},
+    AddressSpace, IntPredicate, OptimizationLevel,
+};
+use itertools::Itertools;
+
+use nac3core_derive::StructFields;
+
+use super::ProxyType;
+use crate::{
+    codegen::{
+        types::structure::{
+            check_struct_type_matches_fields, FieldIndexCounter, StructField, StructFields,
+        },
+        values::{ListValue, ProxyValue},
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::{iter_type_vars, Type, TypeEnum},
+};
+
+/// Proxy type for a `list` type in LLVM.
+#[derive(Debug, PartialEq, Eq, Clone, Copy)]
+pub struct ListType<'ctx> {
+    ty: PointerType<'ctx>,
+    item: Option<BasicTypeEnum<'ctx>>,
+    llvm_usize: IntType<'ctx>,
+}
+
+#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
+pub struct ListStructFields<'ctx> {
+    /// Array pointer to content.
+    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
+    pub items: StructField<'ctx, PointerValue<'ctx>>,
+
+    /// Number of items in the array.
+    #[value_type(usize)]
+    pub len: StructField<'ctx, IntValue<'ctx>>,
+}
+
+impl<'ctx> ListStructFields<'ctx> {
+    #[must_use]
+    pub fn new_typed(item: BasicTypeEnum<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
+        let mut counter = FieldIndexCounter::default();
+
+        ListStructFields {
+            items: StructField::create(
+                &mut counter,
+                "items",
+                item.ptr_type(AddressSpace::default()),
+            ),
+            len: StructField::create(&mut counter, "len", llvm_usize),
+        }
+    }
+}
+
+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 ctx = llvm_ty.get_context();
+
+        let llvm_ty = llvm_ty.get_element_type();
+        let AnyTypeEnum::StructType(llvm_ty) = llvm_ty else {
+            return Err(format!("Expected struct type for `list` type, got {llvm_ty}"));
+        };
+
+        let fields = ListStructFields::new(ctx, llvm_usize);
+
+        check_struct_type_matches_fields(
+            fields,
+            llvm_ty,
+            "list",
+            &[(fields.items.name(), &|ty| {
+                if ty.is_pointer_type() {
+                    Ok(())
+                } else {
+                    Err(format!("Expected T* for `list.items`, got {ty}"))
+                }
+            })],
+        )
+    }
+
+    /// Returns an instance of [`StructFields`] containing all field accessors for this type.
+    #[must_use]
+    fn fields(item: BasicTypeEnum<'ctx>, llvm_usize: IntType<'ctx>) -> ListStructFields<'ctx> {
+        ListStructFields::new_typed(item, llvm_usize)
+    }
+
+    /// See [`ListType::fields`].
+    // TODO: Move this into e.g. StructProxyType
+    #[must_use]
+    pub fn get_fields(&self, _ctx: &impl AsContextRef<'ctx>) -> ListStructFields<'ctx> {
+        Self::fields(self.item.unwrap_or(self.llvm_usize.into()), self.llvm_usize)
+    }
+
+    /// Creates an LLVM type corresponding to the expected structure of a `List`.
+    #[must_use]
+    fn llvm_type(
+        ctx: &'ctx Context,
+        element_type: Option<BasicTypeEnum<'ctx>>,
+        llvm_usize: IntType<'ctx>,
+    ) -> PointerType<'ctx> {
+        let element_type = element_type.unwrap_or(llvm_usize.into());
+
+        let field_tys =
+            Self::fields(element_type, llvm_usize).into_iter().map(|field| field.1).collect_vec();
+
+        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, Some(element_type), llvm_usize);
+
+        Self { ty: llvm_list, item: Some(element_type), llvm_usize }
+    }
+
+    /// Creates an instance of [`ListType`] with an unknown element type.
+    #[must_use]
+    pub fn new_untyped<G: CodeGenerator + ?Sized>(generator: &G, ctx: &'ctx Context) -> Self {
+        let llvm_usize = generator.get_size_type(ctx);
+        let llvm_list = Self::llvm_type(ctx, None, llvm_usize);
+
+        Self { ty: llvm_list, item: None, llvm_usize }
+    }
+
+    /// Creates an [`ListType`] from a [unifier type][Type].
+    #[must_use]
+    pub fn from_unifier_type<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ty: Type,
+    ) -> Self {
+        // Check unifier type and extract `item_type`
+        let elem_type = match &*ctx.unifier.get_ty_immutable(ty) {
+            TypeEnum::TObj { obj_id, params, .. }
+                if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
+            {
+                iter_type_vars(params).next().unwrap().ty
+            }
+
+            _ => panic!("Expected `list` type, but got {}", ctx.unifier.stringify(ty)),
+        };
+
+        let llvm_usize = generator.get_size_type(ctx.ctx);
+        let llvm_elem_type = if let TypeEnum::TVar { .. } = &*ctx.unifier.get_ty_immutable(ty) {
+            None
+        } else {
+            Some(ctx.get_llvm_type(generator, elem_type))
+        };
+
+        Self {
+            ty: Self::llvm_type(ctx.ctx, llvm_elem_type, llvm_usize),
+            item: llvm_elem_type,
+            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());
+
+        let ctx = ptr_ty.get_context();
+
+        // We are just searching for the index off a field - Slot an arbitrary element type in.
+        let item_field_idx =
+            Self::fields(ctx.i8_type().into(), llvm_usize).index_of_field(|f| f.items);
+        let item = unsafe {
+            ptr_ty
+                .get_element_type()
+                .into_struct_type()
+                .get_field_type_at_index_unchecked(item_field_idx)
+                .into_pointer_type()
+                .get_element_type()
+        };
+        let item = BasicTypeEnum::try_from(item).unwrap_or_else(|()| {
+            panic!(
+                "Expected BasicTypeEnum for list element type, got {}",
+                ptr_ty.get_element_type().print_to_string()
+            )
+        });
+
+        ListType { ty: ptr_ty, item: Some(item), llvm_usize }
+    }
+
+    /// Returns the type of the `size` field of this `list` type.
+    #[must_use]
+    pub fn size_type(&self) -> IntType<'ctx> {
+        self.llvm_usize
+    }
+
+    /// Returns the element type of this `list` type.
+    #[must_use]
+    pub fn element_type(&self) -> Option<BasicTypeEnum<'ctx>> {
+        self.item
+    }
+
+    /// Allocates an instance of [`ListValue`] as if by calling `alloca` on the base type.
+    ///
+    /// See [`ProxyType::raw_alloca`].
+    #[must_use]
+    pub fn alloca(
+        &self,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca(ctx, name),
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Allocates an instance of [`ListValue`] as if by calling `alloca` on the base type.
+    ///
+    /// See [`ProxyType::raw_alloca_var`].
+    #[must_use]
+    pub fn alloca_var<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca_var(generator, ctx, name),
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Allocates a [`ListValue`] on the stack using `item` of this [`ListType`] instance.
+    ///
+    /// The returned list will contain:
+    ///
+    /// - `data`: Allocated with `len` number of elements.
+    /// - `len`: Initialized to the value of `len` passed to this function.
+    #[must_use]
+    pub fn construct<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        len: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        let len = ctx.builder.build_int_z_extend(len, self.llvm_usize, "").unwrap();
+
+        // Generate a runtime assertion if allocating a non-empty list with unknown element type
+        if ctx.registry.llvm_options.opt_level == OptimizationLevel::None && self.item.is_none() {
+            let len_eqz = ctx
+                .builder
+                .build_int_compare(IntPredicate::EQ, len, self.llvm_usize.const_zero(), "")
+                .unwrap();
+
+            ctx.make_assert(
+                generator,
+                len_eqz,
+                "0:AssertionError",
+                "Cannot allocate a non-empty list with unknown element type",
+                [None, None, None],
+                ctx.current_loc,
+            );
+        }
+
+        let plist = self.alloca_var(generator, ctx, name);
+        plist.store_size(ctx, generator, len);
+
+        let item = self.item.unwrap_or(self.llvm_usize.into());
+        plist.create_data(ctx, item, None);
+
+        plist
+    }
+
+    /// Convenience function for creating a list with zero elements.
+    ///
+    /// This function is preferred over [`ListType::construct`] if the length is known to always be
+    /// 0, as this function avoids injecting an IR assertion for checking if a non-empty untyped
+    /// list is being allocated.
+    ///
+    /// The returned list will contain:
+    ///
+    /// - `data`: Initialized to `(T*) 0`.
+    /// - `len`: Initialized to `0`.
+    #[must_use]
+    pub fn construct_empty<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        let plist = self.alloca_var(generator, ctx, name);
+
+        plist.store_size(ctx, generator, self.llvm_usize.const_zero());
+        plist.create_data(ctx, self.item.unwrap_or(self.llvm_usize.into()), None);
+
+        plist
+    }
+
+    /// Converts an existing value into a [`ListValue`].
+    #[must_use]
+    pub fn map_value(
+        &self,
+        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(value, self.llvm_usize, name)
+    }
+}
+
+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 alloca_type(&self) -> impl BasicType<'ctx> {
+        self.as_base_type().get_element_type().into_struct_type()
+    }
+
+    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 +1,125 @@
+//! This module contains abstraction over all intrinsic composite types of NAC3.
+//!
+//! # `raw_alloca` vs `alloca` vs `construct`
+//!
+//! There are three ways of creating a new object instance using the abstractions provided by this
+//! module.
+//!
+//! - `raw_alloca`: Allocates the object on the stack, returning an instance of
+//!   [`impl BasicValue`][inkwell::values::BasicValue]. This is similar to a `malloc` expression in
+//!   C++ but the object is allocated on the stack.
+//! - `alloca`: Similar to `raw_alloca`, but also wraps the allocated object with
+//!   [`<Self as ProxyType<'ctx>>::Value`][ProxyValue], and returns the wrapped object. The returned
+//!   object will not initialize any value or fields. This is similar to a type-safe `malloc`
+//!   expression in C++ but the object is allocated on the stack.
+//! - `construct`: Similar to `alloca`, but performs some initialization on the value or fields of
+//!   the returned object. This is similar to a `new` expression in C++ but the object is allocated
+//!   on the stack.
+
+use inkwell::{
+    context::Context,
+    types::BasicType,
+    values::{IntValue, PointerValue},
+};
+
+use super::{
+    values::{ArraySliceValue, ProxyValue},
+    {CodeGenContext, CodeGenerator},
+};
+pub use list::*;
+pub use range::*;
+pub use tuple::*;
+
+mod list;
+pub mod ndarray;
+mod range;
+pub mod structure;
+mod tuple;
+pub mod utils;
+
+/// 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>;
+
+    /// Returns the type that should be used in `alloca` IR statements.
+    fn alloca_type(&self) -> impl BasicType<'ctx>;
+
+    /// Creates a new value of this type by invoking `alloca` at the current builder location,
+    /// returning a [`PointerValue`] instance representing the allocated value.
+    fn raw_alloca(
+        &self,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> PointerValue<'ctx> {
+        ctx.builder
+            .build_alloca(self.alloca_type().as_basic_type_enum(), name.unwrap_or_default())
+            .unwrap()
+    }
+
+    /// Creates a new value of this type by invoking `alloca` at the beginning of the function,
+    /// returning a [`PointerValue`] instance representing the allocated value.
+    fn raw_alloca_var<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> PointerValue<'ctx> {
+        generator.gen_var_alloc(ctx, self.alloca_type().as_basic_type_enum(), name).unwrap()
+    }
+
+    /// Creates a new array value of this type by invoking `alloca` at the current builder location,
+    /// returning an [`ArraySliceValue`] encapsulating the resulting array.
+    fn array_alloca(
+        &self,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        size: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> ArraySliceValue<'ctx> {
+        ArraySliceValue::from_ptr_val(
+            ctx.builder
+                .build_array_alloca(
+                    self.alloca_type().as_basic_type_enum(),
+                    size,
+                    name.unwrap_or_default(),
+                )
+                .unwrap(),
+            size,
+            name,
+        )
+    }
+
+    /// Creates a new array value of this type by invoking `alloca` at the beginning of the
+    /// function, returning an [`ArraySliceValue`] encapsulating the resulting array.
+    fn array_alloca_var<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.alloca_type().as_basic_type_enum(), size, name)
+            .unwrap()
+    }
+
+    /// Returns the [base type][Self::Base] of this proxy.
+    fn as_base_type(&self) -> Self::Base;
+}
--- a/nac3core/src/codegen/types/ndarray/array.rs
+++ b/nac3core/src/codegen/types/ndarray/array.rs
@ -0,0 +1,243 @@
+use inkwell::{
+    types::BasicTypeEnum,
+    values::{BasicValueEnum, IntValue},
+    AddressSpace,
+};
+
+use crate::{
+    codegen::{
+        irrt,
+        stmt::gen_if_else_expr_callback,
+        types::{ndarray::NDArrayType, ListType, ProxyType},
+        values::{
+            ndarray::NDArrayValue, ArrayLikeValue, ArraySliceValue, ListValue, ProxyValue,
+            TypedArrayLikeAdapter, TypedArrayLikeMutator,
+        },
+        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, G: CodeGenerator + ?Sized>(
+    generator: &G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    list_ty: Type,
+) -> (BasicTypeEnum<'ctx>, u64) {
+    let dtype = arraylike_flatten_element_type(&mut ctx.unifier, list_ty);
+    let ndims = arraylike_get_ndims(&mut ctx.unifier, list_ty);
+
+    (ctx.get_llvm_type(generator, dtype), ndims)
+}
+
+impl<'ctx> NDArrayType<'ctx> {
+    /// Implementation of `np_array(<list>, copy=True)`
+    fn construct_numpy_array_from_list_copy_true_impl<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        (list_ty, list): (Type, ListValue<'ctx>),
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        let (dtype, ndims_int) = get_list_object_dtype_and_ndims(generator, ctx, list_ty);
+        assert!(self.ndims >= ndims_int);
+        assert_eq!(dtype, self.dtype);
+
+        let list_value = list.as_i8_list(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 = self.llvm_usize.const_int(ndims_int, false);
+        let shape = ctx.builder.build_array_alloca(self.llvm_usize, ndims, "").unwrap();
+        let shape = ArraySliceValue::from_ptr_val(shape, ndims, None);
+        let shape = TypedArrayLikeAdapter::from(
+            shape,
+            |_, _, val| val.into_int_value(),
+            |_, _, val| val.into(),
+        );
+        irrt::ndarray::call_nac3_ndarray_array_set_and_validate_list_shape(
+            generator, ctx, list_value, ndims, &shape,
+        );
+
+        let ndarray = Self::new(generator, ctx.ctx, dtype, ndims_int)
+            .construct_uninitialized(generator, ctx, name);
+        ndarray.copy_shape_from_array(generator, ctx, shape.base_ptr(ctx, generator));
+        unsafe { ndarray.create_data(generator, ctx) };
+
+        // Copy all contents from the list.
+        irrt::ndarray::call_nac3_ndarray_array_write_list_to_array(
+            generator, ctx, list_value, ndarray,
+        );
+
+        ndarray
+    }
+
+    /// Implementation of `np_array(<list>, copy=None)`
+    fn construct_numpy_array_from_list_copy_none_impl<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        (list_ty, list): (Type, ListValue<'ctx>),
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        // 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(generator, ctx, list_ty);
+        if ndims == 1 {
+            // `list` is not nested
+            assert_eq!(ndims, 1);
+            assert!(self.ndims >= ndims);
+            assert_eq!(dtype, self.dtype);
+
+            let llvm_pi8 = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
+
+            let ndarray = Self::new(generator, ctx.ctx, dtype, 1)
+                .construct_uninitialized(generator, ctx, name);
+
+            // Set data
+            let data = ctx
+                .builder
+                .build_pointer_cast(list.data().base_ptr(ctx, generator), llvm_pi8, "")
+                .unwrap();
+            ndarray.store_data(ctx, data);
+
+            // ndarray->shape[0] = list->len;
+            let shape = ndarray.shape();
+            let list_len = list.load_size(ctx, None);
+            unsafe {
+                shape.set_typed_unchecked(ctx, generator, &self.llvm_usize.const_zero(), list_len);
+            }
+
+            // Set strides, the `data` is contiguous
+            ndarray.set_strides_contiguous(generator, ctx);
+
+            ndarray
+        } else {
+            // `list` is nested, copy
+            self.construct_numpy_array_from_list_copy_true_impl(
+                generator,
+                ctx,
+                (list_ty, list),
+                name,
+            )
+        }
+    }
+
+    /// Implementation of `np_array(<list>, copy=copy)`
+    fn construct_numpy_array_list_impl<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        (list_ty, list): (Type, ListValue<'ctx>),
+        copy: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        assert_eq!(copy.get_type(), ctx.ctx.bool_type());
+
+        let (dtype, ndims) = get_list_object_dtype_and_ndims(generator, ctx, list_ty);
+
+        let ndarray = gen_if_else_expr_callback(
+            generator,
+            ctx,
+            |_generator, _ctx| Ok(copy),
+            |generator, ctx| {
+                let ndarray = self.construct_numpy_array_from_list_copy_true_impl(
+                    generator,
+                    ctx,
+                    (list_ty, list),
+                    name,
+                );
+                Ok(Some(ndarray.as_base_value()))
+            },
+            |generator, ctx| {
+                let ndarray = self.construct_numpy_array_from_list_copy_none_impl(
+                    generator,
+                    ctx,
+                    (list_ty, list),
+                    name,
+                );
+                Ok(Some(ndarray.as_base_value()))
+            },
+        )
+        .unwrap()
+        .map(BasicValueEnum::into_pointer_value)
+        .unwrap();
+
+        NDArrayType::new(generator, ctx.ctx, dtype, ndims).map_value(ndarray, None)
+    }
+
+    /// Implementation of `np_array(<ndarray>, copy=copy)`.
+    pub fn construct_numpy_array_ndarray_impl<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndarray: NDArrayValue<'ctx>,
+        copy: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        assert_eq!(ndarray.get_type().dtype, self.dtype);
+        assert!(self.ndims >= ndarray.get_type().ndims);
+        assert_eq!(copy.get_type(), ctx.ctx.bool_type());
+
+        let ndarray_val = gen_if_else_expr_callback(
+            generator,
+            ctx,
+            |_generator, _ctx| Ok(copy),
+            |generator, ctx| {
+                let ndarray = ndarray.make_copy(generator, ctx); // Force copy
+                Ok(Some(ndarray.as_base_value()))
+            },
+            |_generator, _ctx| {
+                // No need to copy. Return `ndarray` itself.
+                Ok(Some(ndarray.as_base_value()))
+            },
+        )
+        .unwrap()
+        .map(BasicValueEnum::into_pointer_value)
+        .unwrap();
+
+        ndarray.get_type().map_value(ndarray_val, name)
+    }
+
+    /// Create a new ndarray like
+    /// [`np.array()`](https://numpy.org/doc/stable/reference/generated/numpy.array.html).
+    ///
+    /// Note that the returned [`NDArrayValue`] may have fewer dimensions than is specified by this
+    /// instance. Use [`NDArrayValue::atleast_nd`] on the returned value if an `ndarray` instance
+    /// with the exact number of dimensions is needed.
+    pub fn construct_numpy_array<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        (object_ty, object): (Type, BasicValueEnum<'ctx>),
+        copy: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        match &*ctx.unifier.get_ty_immutable(object_ty) {
+            TypeEnum::TObj { obj_id, .. }
+                if *obj_id == ctx.primitives.list.obj_id(&ctx.unifier).unwrap() =>
+            {
+                let list = ListType::from_unifier_type(generator, ctx, object_ty)
+                    .map_value(object.into_pointer_value(), None);
+                self.construct_numpy_array_list_impl(generator, ctx, (object_ty, list), copy, name)
+            }
+
+            TypeEnum::TObj { obj_id, .. }
+                if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
+            {
+                let ndarray = NDArrayType::from_unifier_type(generator, ctx, object_ty)
+                    .map_value(object.into_pointer_value(), None);
+                self.construct_numpy_array_ndarray_impl(generator, ctx, ndarray, copy, name)
+            }
+
+            _ => panic!("Unrecognized object type: {}", ctx.unifier.stringify(object_ty)), // Typechecker ensures this
+        }
+    }
+}
--- a/nac3core/src/codegen/types/ndarray/broadcast.rs
+++ b/nac3core/src/codegen/types/ndarray/broadcast.rs
@ -0,0 +1,176 @@
+use inkwell::{
+    context::{AsContextRef, Context},
+    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
+    values::{IntValue, PointerValue},
+    AddressSpace,
+};
+use itertools::Itertools;
+
+use nac3core_derive::StructFields;
+
+use crate::codegen::{
+    types::{
+        structure::{check_struct_type_matches_fields, StructField, StructFields},
+        ProxyType,
+    },
+    values::{ndarray::ShapeEntryValue, ProxyValue},
+    CodeGenContext, CodeGenerator,
+};
+
+#[derive(Debug, PartialEq, Eq, Clone, Copy)]
+pub struct ShapeEntryType<'ctx> {
+    ty: PointerType<'ctx>,
+    llvm_usize: IntType<'ctx>,
+}
+
+#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
+pub struct ShapeEntryStructFields<'ctx> {
+    #[value_type(usize)]
+    pub ndims: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(usize.ptr_type(AddressSpace::default()))]
+    pub shape: StructField<'ctx, PointerValue<'ctx>>,
+}
+
+impl<'ctx> ShapeEntryType<'ctx> {
+    /// Checks whether `llvm_ty` represents a [`ShapeEntryType`], returning [Err] if it does not.
+    pub fn is_representable(
+        llvm_ty: PointerType<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        let ctx = llvm_ty.get_context();
+
+        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 `ShapeEntry` type, got {llvm_ndarray_ty}"
+            ));
+        };
+
+        check_struct_type_matches_fields(
+            Self::fields(ctx, llvm_usize),
+            llvm_ndarray_ty,
+            "NDArray",
+            &[],
+        )
+    }
+
+    /// Returns an instance of [`StructFields`] containing all field accessors for this type.
+    #[must_use]
+    fn fields(
+        ctx: impl AsContextRef<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> ShapeEntryStructFields<'ctx> {
+        ShapeEntryStructFields::new(ctx, llvm_usize)
+    }
+
+    /// See [`ShapeEntryStructFields::fields`].
+    // TODO: Move this into e.g. StructProxyType
+    #[must_use]
+    pub fn get_fields(&self, ctx: impl AsContextRef<'ctx>) -> ShapeEntryStructFields<'ctx> {
+        Self::fields(ctx, self.llvm_usize)
+    }
+
+    /// Creates an LLVM type corresponding to the expected structure of a `ShapeEntry`.
+    #[must_use]
+    fn llvm_type(ctx: &'ctx Context, llvm_usize: IntType<'ctx>) -> PointerType<'ctx> {
+        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 [`ShapeEntryType`].
+    #[must_use]
+    pub fn new<G: CodeGenerator + ?Sized>(generator: &G, ctx: &'ctx Context) -> Self {
+        let llvm_usize = generator.get_size_type(ctx);
+        let llvm_ty = Self::llvm_type(ctx, llvm_usize);
+
+        Self { ty: llvm_ty, llvm_usize }
+    }
+
+    /// Creates a [`ShapeEntryType`] from a [`PointerType`] representing an `ShapeEntry`.
+    #[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());
+
+        Self { ty: ptr_ty, llvm_usize }
+    }
+
+    /// Allocates an instance of [`ShapeEntryValue`] as if by calling `alloca` on the base type.
+    #[must_use]
+    pub fn alloca(
+        &self,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca(ctx, name),
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Allocates an instance of [`ShapeEntryValue`] as if by calling `alloca` on the base type.
+    #[must_use]
+    pub fn alloca_var<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca_var(generator, ctx, name),
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Converts an existing value into a [`ShapeEntryValue`].
+    #[must_use]
+    pub fn map_value(
+        &self,
+        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(value, self.llvm_usize, name)
+    }
+}
+
+impl<'ctx> ProxyType<'ctx> for ShapeEntryType<'ctx> {
+    type Base = PointerType<'ctx>;
+    type Value = ShapeEntryValue<'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 alloca_type(&self) -> impl BasicType<'ctx> {
+        self.as_base_type().get_element_type().into_struct_type()
+    }
+
+    fn as_base_type(&self) -> Self::Base {
+        self.ty
+    }
+}
+
+impl<'ctx> From<ShapeEntryType<'ctx>> for PointerType<'ctx> {
+    fn from(value: ShapeEntryType<'ctx>) -> Self {
+        value.as_base_type()
+    }
+}
--- a/nac3core/src/codegen/types/ndarray/contiguous.rs
+++ b/nac3core/src/codegen/types/ndarray/contiguous.rs
@ -0,0 +1,250 @@
+use inkwell::{
+    context::Context,
+    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
+    values::{IntValue, PointerValue},
+    AddressSpace,
+};
+use itertools::Itertools;
+
+use nac3core_derive::StructFields;
+
+use crate::{
+    codegen::{
+        types::{
+            structure::{
+                check_struct_type_matches_fields, FieldIndexCounter, StructField, StructFields,
+            },
+            ProxyType,
+        },
+        values::{ndarray::ContiguousNDArrayValue, ProxyValue},
+        CodeGenContext, CodeGenerator,
+    },
+    toplevel::numpy::unpack_ndarray_var_tys,
+    typecheck::typedef::Type,
+};
+
+#[derive(Debug, PartialEq, Eq, Clone, Copy)]
+pub struct ContiguousNDArrayType<'ctx> {
+    ty: PointerType<'ctx>,
+    item: BasicTypeEnum<'ctx>,
+    llvm_usize: IntType<'ctx>,
+}
+
+#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
+pub struct ContiguousNDArrayStructFields<'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> ContiguousNDArrayStructFields<'ctx> {
+    #[must_use]
+    pub fn new_typed(item: BasicTypeEnum<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
+        let mut counter = FieldIndexCounter::default();
+
+        ContiguousNDArrayStructFields {
+            ndims: StructField::create(&mut counter, "ndims", llvm_usize),
+            shape: StructField::create(
+                &mut counter,
+                "shape",
+                llvm_usize.ptr_type(AddressSpace::default()),
+            ),
+            data: StructField::create(&mut counter, "data", item.ptr_type(AddressSpace::default())),
+        }
+    }
+}
+
+impl<'ctx> ContiguousNDArrayType<'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 ctx = llvm_ty.get_context();
+
+        let llvm_ty = llvm_ty.get_element_type();
+        let AnyTypeEnum::StructType(llvm_ty) = llvm_ty else {
+            return Err(format!(
+                "Expected struct type for `ContiguousNDArray` type, got {llvm_ty}"
+            ));
+        };
+
+        let fields = ContiguousNDArrayStructFields::new(ctx, llvm_usize);
+
+        check_struct_type_matches_fields(
+            fields,
+            llvm_ty,
+            "ContiguousNDArray",
+            &[(fields.data.name(), &|ty| {
+                if ty.is_pointer_type() {
+                    Ok(())
+                } else {
+                    Err(format!("Expected T* for `ContiguousNDArray.data`, got {ty}"))
+                }
+            })],
+        )
+    }
+
+    /// Returns an instance of [`StructFields`] containing all field accessors for this type.
+    #[must_use]
+    fn fields(
+        item: BasicTypeEnum<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> ContiguousNDArrayStructFields<'ctx> {
+        ContiguousNDArrayStructFields::new_typed(item, llvm_usize)
+    }
+
+    /// See [`NDArrayType::fields`].
+    // TODO: Move this into e.g. StructProxyType
+    #[must_use]
+    pub fn get_fields(&self) -> ContiguousNDArrayStructFields<'ctx> {
+        Self::fields(self.item, self.llvm_usize)
+    }
+
+    /// Creates an LLVM type corresponding to the expected structure of an `NDArray`.
+    #[must_use]
+    fn llvm_type(
+        ctx: &'ctx Context,
+        item: BasicTypeEnum<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> PointerType<'ctx> {
+        let field_tys =
+            Self::fields(item, llvm_usize).into_iter().map(|field| field.1).collect_vec();
+
+        ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
+    }
+
+    /// Creates an instance of [`ContiguousNDArrayType`].
+    #[must_use]
+    pub fn new<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &'ctx Context,
+        item: BasicTypeEnum<'ctx>,
+    ) -> Self {
+        let llvm_usize = generator.get_size_type(ctx);
+        let llvm_cndarray = Self::llvm_type(ctx, item, llvm_usize);
+
+        Self { ty: llvm_cndarray, item, llvm_usize }
+    }
+
+    /// Creates an [`ContiguousNDArrayType`] from a [unifier type][Type].
+    #[must_use]
+    pub fn from_unifier_type<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ty: Type,
+    ) -> Self {
+        let (dtype, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
+
+        let llvm_dtype = ctx.get_llvm_type(generator, dtype);
+        let llvm_usize = generator.get_size_type(ctx.ctx);
+
+        Self { ty: Self::llvm_type(ctx.ctx, llvm_dtype, llvm_usize), item: llvm_dtype, llvm_usize }
+    }
+
+    /// Creates an [`ContiguousNDArrayType`] from a [`PointerType`] representing an `NDArray`.
+    #[must_use]
+    pub fn from_type(
+        ptr_ty: PointerType<'ctx>,
+        item: BasicTypeEnum<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Self {
+        debug_assert!(Self::is_representable(ptr_ty, llvm_usize).is_ok());
+
+        Self { ty: ptr_ty, item, llvm_usize }
+    }
+
+    /// Allocates an instance of [`ContiguousNDArrayValue`] as if by calling `alloca` on the base
+    /// type.
+    ///
+    /// See [`ProxyType::raw_alloca`].
+    #[must_use]
+    pub fn alloca(
+        &self,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca(ctx, name),
+            self.item,
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Allocates an instance of [`ContiguousNDArrayValue`] as if by calling `alloca` on the base
+    /// type.
+    ///
+    /// See [`ProxyType::raw_alloca_var`].
+    #[must_use]
+    pub fn alloca_var<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca_var(generator, ctx, name),
+            self.item,
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Converts an existing value into a [`ContiguousNDArrayValue`].
+    #[must_use]
+    pub fn map_value(
+        &self,
+        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            value,
+            self.item,
+            self.llvm_usize,
+            name,
+        )
+    }
+}
+
+impl<'ctx> ProxyType<'ctx> for ContiguousNDArrayType<'ctx> {
+    type Base = PointerType<'ctx>;
+    type Value = ContiguousNDArrayValue<'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 alloca_type(&self) -> impl BasicType<'ctx> {
+        self.as_base_type().get_element_type().into_struct_type()
+    }
+
+    fn as_base_type(&self) -> Self::Base {
+        self.ty
+    }
+}
+
+impl<'ctx> From<ContiguousNDArrayType<'ctx>> for PointerType<'ctx> {
+    fn from(value: ContiguousNDArrayType<'ctx>) -> Self {
+        value.as_base_type()
+    }
+}
--- a/nac3core/src/codegen/types/ndarray/factory.rs
+++ b/nac3core/src/codegen/types/ndarray/factory.rs
@ -0,0 +1,236 @@
+use inkwell::{
+    values::{BasicValueEnum, IntValue},
+    IntPredicate,
+};
+
+use super::NDArrayType;
+use crate::{
+    codegen::{
+        irrt, types::ProxyType, values::TypedArrayLikeAccessor, CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::Type,
+};
+
+/// 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> NDArrayType<'ctx> {
+    /// Create an ndarray like
+    /// [`np.empty`](https://numpy.org/doc/stable/reference/generated/numpy.empty.html).
+    pub fn construct_numpy_empty<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        let ndarray = self.construct_uninitialized(generator, ctx, name);
+
+        // Validate `shape`
+        irrt::ndarray::call_nac3_ndarray_util_assert_shape_no_negative(generator, ctx, shape);
+
+        ndarray.copy_shape_from_array(generator, ctx, shape.base_ptr(ctx, generator));
+        unsafe { ndarray.create_data(generator, ctx) };
+
+        ndarray
+    }
+
+    /// Create an ndarray like
+    /// [`np.full`](https://numpy.org/doc/stable/reference/generated/numpy.full.html).
+    pub fn construct_numpy_full<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+        fill_value: BasicValueEnum<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        let ndarray = self.construct_numpy_empty(generator, ctx, shape, name);
+        ndarray.fill(generator, ctx, fill_value);
+        ndarray
+    }
+
+    /// Create an ndarray like
+    /// [`np.zero`](https://numpy.org/doc/stable/reference/generated/numpy.zeros.html).
+    pub fn construct_numpy_zeros<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        assert_eq!(
+            ctx.get_llvm_type(generator, dtype),
+            self.dtype,
+            "Expected LLVM dtype={} but got {}",
+            self.dtype.print_to_string(),
+            ctx.get_llvm_type(generator, dtype).print_to_string(),
+        );
+
+        let fill_value = ndarray_zero_value(generator, ctx, dtype);
+        self.construct_numpy_full(generator, ctx, shape, fill_value, name)
+    }
+
+    /// Create an ndarray like
+    /// [`np.ones`](https://numpy.org/doc/stable/reference/generated/numpy.ones.html).
+    pub fn construct_numpy_ones<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        shape: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        assert_eq!(
+            ctx.get_llvm_type(generator, dtype),
+            self.dtype,
+            "Expected LLVM dtype={} but got {}",
+            self.dtype.print_to_string(),
+            ctx.get_llvm_type(generator, dtype).print_to_string(),
+        );
+
+        let fill_value = ndarray_one_value(generator, ctx, dtype);
+        self.construct_numpy_full(generator, ctx, shape, fill_value, name)
+    }
+
+    /// Create an ndarray like
+    /// [`np.eye`](https://numpy.org/doc/stable/reference/generated/numpy.eye.html).
+    #[allow(clippy::too_many_arguments)]
+    pub fn construct_numpy_eye<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        nrows: IntValue<'ctx>,
+        ncols: IntValue<'ctx>,
+        offset: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        assert_eq!(
+            ctx.get_llvm_type(generator, dtype),
+            self.dtype,
+            "Expected LLVM dtype={} but got {}",
+            self.dtype.print_to_string(),
+            ctx.get_llvm_type(generator, dtype).print_to_string(),
+        );
+        assert_eq!(nrows.get_type(), self.llvm_usize);
+        assert_eq!(ncols.get_type(), self.llvm_usize);
+        assert_eq!(offset.get_type(), self.llvm_usize);
+
+        let ndzero = ndarray_zero_value(generator, ctx, dtype);
+        let ndone = ndarray_one_value(generator, ctx, dtype);
+
+        let ndarray = self.construct_dyn_shape(generator, ctx, &[nrows, ncols], name);
+
+        // Create data and make the matrix like look np.eye()
+        unsafe {
+            ndarray.create_data(generator, ctx);
+        }
+        ndarray
+            .foreach(generator, ctx, |generator, ctx, _, 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.
+
+                let indices = nditer.get_indices();
+
+                let row_i = unsafe {
+                    indices.get_typed_unchecked(ctx, generator, &self.llvm_usize.const_zero(), None)
+                };
+                let col_i = unsafe {
+                    indices.get_typed_unchecked(
+                        ctx,
+                        generator,
+                        &self.llvm_usize.const_int(1, false),
+                        None,
+                    )
+                };
+
+                let be_one = ctx
+                    .builder
+                    .build_int_compare(
+                        IntPredicate::EQ,
+                        ctx.builder.build_int_add(row_i, offset, "").unwrap(),
+                        col_i,
+                        "",
+                    )
+                    .unwrap();
+                let value = ctx.builder.build_select(be_one, ndone, ndzero, "value").unwrap();
+
+                let p = nditer.get_pointer(ctx);
+                ctx.builder.build_store(p, value).unwrap();
+
+                Ok(())
+            })
+            .unwrap();
+
+        ndarray
+    }
+
+    /// Create an ndarray like
+    /// [`np.identity`](https://numpy.org/doc/stable/reference/generated/numpy.identity.html).
+    pub fn construct_numpy_identity<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dtype: Type,
+        size: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        let offset = self.llvm_usize.const_zero();
+        self.construct_numpy_eye(generator, ctx, dtype, size, size, offset, name)
+    }
+}
--- a/nac3core/src/codegen/types/ndarray/indexing.rs
+++ b/nac3core/src/codegen/types/ndarray/indexing.rs
@ -0,0 +1,205 @@
+use inkwell::{
+    context::{AsContextRef, Context},
+    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
+    values::{IntValue, PointerValue},
+    AddressSpace,
+};
+use itertools::Itertools;
+
+use nac3core_derive::StructFields;
+
+use crate::codegen::{
+    types::{
+        structure::{check_struct_type_matches_fields, StructField, StructFields},
+        ProxyType,
+    },
+    values::{
+        ndarray::{NDIndexValue, RustNDIndex},
+        ArrayLikeIndexer, ArraySliceValue, ProxyValue,
+    },
+    CodeGenContext, CodeGenerator,
+};
+
+#[derive(Debug, PartialEq, Eq, Clone, Copy)]
+pub struct NDIndexType<'ctx> {
+    ty: PointerType<'ctx>,
+    llvm_usize: IntType<'ctx>,
+}
+
+#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
+pub struct NDIndexStructFields<'ctx> {
+    #[value_type(i8_type())]
+    pub type_: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
+    pub data: StructField<'ctx, PointerValue<'ctx>>,
+}
+
+impl<'ctx> NDIndexType<'ctx> {
+    /// Checks whether `llvm_ty` represents a `ndindex` type, returning [Err] if it does not.
+    pub fn is_representable(
+        llvm_ty: PointerType<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        let ctx = llvm_ty.get_context();
+
+        let llvm_ty = llvm_ty.get_element_type();
+        let AnyTypeEnum::StructType(llvm_ty) = llvm_ty else {
+            return Err(format!(
+                "Expected struct type for `ContiguousNDArray` type, got {llvm_ty}"
+            ));
+        };
+
+        let fields = NDIndexStructFields::new(ctx, llvm_usize);
+
+        check_struct_type_matches_fields(fields, llvm_ty, "NDIndex", &[])
+    }
+
+    #[must_use]
+    fn fields(
+        ctx: impl AsContextRef<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> NDIndexStructFields<'ctx> {
+        NDIndexStructFields::new(ctx, llvm_usize)
+    }
+
+    #[must_use]
+    pub fn get_fields(&self) -> NDIndexStructFields<'ctx> {
+        Self::fields(self.ty.get_context(), self.llvm_usize)
+    }
+
+    #[must_use]
+    fn llvm_type(ctx: &'ctx Context, llvm_usize: IntType<'ctx>) -> PointerType<'ctx> {
+        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())
+    }
+
+    #[must_use]
+    pub fn new<G: CodeGenerator + ?Sized>(generator: &G, ctx: &'ctx Context) -> Self {
+        let llvm_usize = generator.get_size_type(ctx);
+        let llvm_ndindex = Self::llvm_type(ctx, llvm_usize);
+
+        Self { ty: llvm_ndindex, llvm_usize }
+    }
+
+    #[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());
+
+        Self { ty: ptr_ty, llvm_usize }
+    }
+
+    /// Allocates an instance of [`NDIndexValue`] as if by calling `alloca` on the base type.
+    ///
+    /// See [`ProxyType::raw_alloca`].
+    #[must_use]
+    pub fn alloca(
+        &self,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca(ctx, name),
+            self.llvm_usize,
+            name,
+        )
+    }
+    /// Allocates an instance of [`NDIndexValue`] as if by calling `alloca` on the base type.
+    ///
+    /// See [`ProxyType::raw_alloca_var`].
+    #[must_use]
+    pub fn alloca_var<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca_var(generator, ctx, name),
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Serialize a list of [`RustNDIndex`] as a newly allocated LLVM array of [`NDIndexValue`].
+    #[must_use]
+    pub fn construct_ndindices<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        in_ndindices: &[RustNDIndex<'ctx>],
+    ) -> ArraySliceValue<'ctx> {
+        // Allocate the LLVM ndindices.
+        let num_ndindices = self.llvm_usize.const_int(in_ndindices.len() as u64, false);
+        let ndindices = self.array_alloca_var(generator, ctx, num_ndindices, None);
+
+        // Initialize all of them.
+        for (i, in_ndindex) in in_ndindices.iter().enumerate() {
+            let pndindex = unsafe {
+                ndindices.ptr_offset_unchecked(
+                    ctx,
+                    generator,
+                    &ctx.ctx.i64_type().const_int(u64::try_from(i).unwrap(), false),
+                    None,
+                )
+            };
+
+            in_ndindex.write_to_ndindex(
+                generator,
+                ctx,
+                NDIndexValue::from_pointer_value(pndindex, self.llvm_usize, None),
+            );
+        }
+
+        ndindices
+    }
+
+    #[must_use]
+    pub fn map_value(
+        &self,
+        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(value, self.llvm_usize, name)
+    }
+}
+
+impl<'ctx> ProxyType<'ctx> for NDIndexType<'ctx> {
+    type Base = PointerType<'ctx>;
+    type Value = NDIndexValue<'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 alloca_type(&self) -> impl BasicType<'ctx> {
+        self.as_base_type().get_element_type().into_struct_type()
+    }
+
+    fn as_base_type(&self) -> Self::Base {
+        self.ty
+    }
+}
+
+impl<'ctx> From<NDIndexType<'ctx>> for PointerType<'ctx> {
+    fn from(value: NDIndexType<'ctx>) -> Self {
+        value.as_base_type()
+    }
+}
--- a/nac3core/src/codegen/types/ndarray/map.rs
+++ b/nac3core/src/codegen/types/ndarray/map.rs
@ -0,0 +1,187 @@
+use inkwell::{types::BasicTypeEnum, values::BasicValueEnum};
+use itertools::Itertools;
+
+use crate::codegen::{
+    stmt::gen_for_callback,
+    types::{
+        ndarray::{NDArrayType, NDIterType},
+        ProxyType,
+    },
+    values::{
+        ndarray::{NDArrayOut, NDArrayValue, ScalarOrNDArray},
+        ArrayLikeValue, ProxyValue,
+    },
+    CodeGenContext, CodeGenerator,
+};
+
+impl<'ctx> NDArrayType<'ctx> {
+    /// Generate LLVM IR to broadcast `ndarray`s together, and starmap through them with `mapping`
+    /// elementwise.
+    ///
+    /// `mapping` is an LLVM IR generator. The input of `mapping` is the list of elements when
+    /// iterating through the input `ndarrays` after broadcasting. The output of `mapping` is the
+    /// result of the elementwise operation.
+    ///
+    /// `out` specifies whether the result should be a new ndarray or to be written an existing
+    /// ndarray.
+    pub fn broadcast_starmap<'a, G, MappingFn>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        ndarrays: &[NDArrayValue<'ctx>],
+        out: NDArrayOut<'ctx>,
+        mapping: MappingFn,
+    ) -> Result<<Self as ProxyType<'ctx>>::Value, String>
+    where
+        G: CodeGenerator + ?Sized,
+        MappingFn: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            &[BasicValueEnum<'ctx>],
+        ) -> Result<BasicValueEnum<'ctx>, String>,
+    {
+        // Broadcast inputs
+        let broadcast_result = self.broadcast(generator, ctx, ndarrays);
+
+        let out_ndarray = match out {
+            NDArrayOut::NewNDArray { dtype } => {
+                // Create a new ndarray based on the broadcast shape.
+                let result_ndarray =
+                    NDArrayType::new(generator, ctx.ctx, dtype, broadcast_result.ndims)
+                        .construct_uninitialized(generator, ctx, None);
+                result_ndarray.copy_shape_from_array(
+                    generator,
+                    ctx,
+                    broadcast_result.shape.base_ptr(ctx, generator),
+                );
+                unsafe {
+                    result_ndarray.create_data(generator, ctx);
+                }
+                result_ndarray
+            }
+
+            NDArrayOut::WriteToNDArray { ndarray: result_ndarray } => {
+                // Use an existing ndarray.
+
+                // Check that its shape is compatible with the broadcast shape.
+                result_ndarray.assert_can_be_written_by_out(generator, ctx, broadcast_result.shape);
+                result_ndarray
+            }
+        };
+
+        // Map element-wise and store results into `mapped_ndarray`.
+        let nditer = NDIterType::new(generator, ctx.ctx).construct(generator, ctx, out_ndarray);
+        gen_for_callback(
+            generator,
+            ctx,
+            Some("broadcast_starmap"),
+            |generator, ctx| {
+                // Create NDIters for all broadcasted input ndarrays.
+                let other_nditers = broadcast_result
+                    .ndarrays
+                    .iter()
+                    .map(|ndarray| {
+                        NDIterType::new(generator, ctx.ctx).construct(generator, ctx, *ndarray)
+                    })
+                    .collect_vec();
+                Ok((nditer, other_nditers))
+            },
+            |generator, ctx, (out_nditer, _in_nditers)| {
+                // We can simply use `out_nditer`'s `has_element()`.
+                // `in_nditers`' `has_element()`s should return the same value.
+                Ok(out_nditer.has_element(generator, ctx))
+            },
+            |generator, ctx, _hooks, (out_nditer, in_nditers)| {
+                // Get all the scalars from the broadcasted input ndarrays, pass them to `mapping`,
+                // and write to `out_ndarray`.
+                let in_scalars =
+                    in_nditers.iter().map(|nditer| nditer.get_scalar(ctx)).collect_vec();
+
+                let result = mapping(generator, ctx, &in_scalars)?;
+
+                let p = out_nditer.get_pointer(ctx);
+                ctx.builder.build_store(p, result).unwrap();
+
+                Ok(())
+            },
+            |generator, ctx, (out_nditer, in_nditers)| {
+                // Advance all iterators
+                out_nditer.next(generator, ctx);
+                in_nditers.iter().for_each(|nditer| nditer.next(generator, ctx));
+                Ok(())
+            },
+        )?;
+
+        Ok(out_ndarray)
+    }
+}
+
+impl<'ctx> ScalarOrNDArray<'ctx> {
+    /// Starmap through a list of inputs using `mapping`, where an input could be an ndarray, a
+    /// scalar.
+    ///
+    /// This function is very helpful when implementing NumPy functions that takes on either scalars
+    /// or ndarrays or a mix of them as their inputs and produces either an ndarray with broadcast,
+    /// or a scalar if all its inputs are all scalars.
+    ///
+    /// For example ,this function can be used to implement `np.add`, which has the following
+    /// behaviors:
+    ///
+    /// - `np.add(3, 4) = 7` # (scalar, scalar) -> scalar
+    /// - `np.add(3, np.array([4, 5, 6]))` # (scalar, ndarray) -> ndarray; the first `scalar` is
+    ///   converted into an ndarray and broadcasted.
+    /// - `np.add(np.array([[1], [2], [3]]), np.array([[4, 5, 6]]))` # (ndarray, ndarray) ->
+    ///   ndarray; there is broadcasting.
+    ///
+    /// ## Details:
+    ///
+    /// If `inputs` are all [`ScalarOrNDArray::Scalar`], the output will be a
+    /// [`ScalarOrNDArray::Scalar`] with type `ret_dtype`.
+    ///
+    /// Otherwise (if there are any [`ScalarOrNDArray::NDArray`] in `inputs`), all inputs will be
+    /// 'as-ndarray'-ed into ndarrays, then all inputs (now all ndarrays) will be passed to
+    /// [`NDArrayValue::broadcasting_starmap`] and **create** a new ndarray with dtype `ret_dtype`.
+    pub fn broadcasting_starmap<'a, G, MappingFn>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        inputs: &[ScalarOrNDArray<'ctx>],
+        ret_dtype: BasicTypeEnum<'ctx>,
+        mapping: MappingFn,
+    ) -> Result<ScalarOrNDArray<'ctx>, String>
+    where
+        G: CodeGenerator + ?Sized,
+        MappingFn: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            &[BasicValueEnum<'ctx>],
+        ) -> Result<BasicValueEnum<'ctx>, String>,
+    {
+        // Check if all inputs are Scalars
+        let all_scalars: Option<Vec<_>> =
+            inputs.iter().map(BasicValueEnum::<'ctx>::try_from).try_collect().ok();
+
+        if let Some(scalars) = all_scalars {
+            let scalars = scalars.iter().copied().collect_vec();
+            let value = mapping(generator, ctx, &scalars)?;
+
+            Ok(ScalarOrNDArray::Scalar(value))
+        } else {
+            // Promote all input to ndarrays and map through them.
+            let inputs = inputs.iter().map(|input| input.to_ndarray(generator, ctx)).collect_vec();
+            let ndarray = NDArrayType::new_broadcast(
+                generator,
+                ctx.ctx,
+                ret_dtype,
+                &inputs.iter().map(NDArrayValue::get_type).collect_vec(),
+            )
+            .broadcast_starmap(
+                generator,
+                ctx,
+                &inputs,
+                NDArrayOut::NewNDArray { dtype: ret_dtype },
+                mapping,
+            )?;
+            Ok(ScalarOrNDArray::NDArray(ndarray))
+        }
+    }
+}
--- a/nac3core/src/codegen/types/ndarray/mod.rs
+++ b/nac3core/src/codegen/types/ndarray/mod.rs
@ -0,0 +1,452 @@
+use inkwell::{
+    context::{AsContextRef, Context},
+    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
+    values::{BasicValue, IntValue, PointerValue},
+    AddressSpace,
+};
+use itertools::Itertools;
+
+use nac3core_derive::StructFields;
+
+use super::{
+    structure::{check_struct_type_matches_fields, StructField, StructFields},
+    ProxyType,
+};
+use crate::{
+    codegen::{
+        values::{ndarray::NDArrayValue, ProxyValue, TypedArrayLikeMutator},
+        {CodeGenContext, CodeGenerator},
+    },
+    toplevel::{helper::extract_ndims, numpy::unpack_ndarray_var_tys},
+    typecheck::typedef::Type,
+};
+pub use broadcast::*;
+pub use contiguous::*;
+pub use indexing::*;
+pub use nditer::*;
+
+mod array;
+mod broadcast;
+mod contiguous;
+pub mod factory;
+mod indexing;
+mod map;
+mod nditer;
+
+/// Proxy type for a `ndarray` type in LLVM.
+#[derive(Debug, PartialEq, Eq, Clone, Copy)]
+pub struct NDArrayType<'ctx> {
+    ty: PointerType<'ctx>,
+    dtype: BasicTypeEnum<'ctx>,
+    ndims: u64,
+    llvm_usize: IntType<'ctx>,
+}
+
+#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
+pub struct NDArrayStructFields<'ctx> {
+    /// The size of each `NDArray` element in bytes.
+    #[value_type(usize)]
+    pub itemsize: StructField<'ctx, IntValue<'ctx>>,
+    /// Number of dimensions in the array.
+    #[value_type(usize)]
+    pub ndims: StructField<'ctx, IntValue<'ctx>>,
+    /// Pointer to an array containing the shape of the `NDArray`.
+    #[value_type(usize.ptr_type(AddressSpace::default()))]
+    pub shape: StructField<'ctx, PointerValue<'ctx>>,
+    /// Pointer to an array indicating the number of bytes between each element at a dimension
+    #[value_type(usize.ptr_type(AddressSpace::default()))]
+    pub strides: StructField<'ctx, PointerValue<'ctx>>,
+    /// Pointer to an array containing the array data
+    #[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 ctx = llvm_ty.get_context();
+
+        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}"));
+        };
+
+        check_struct_type_matches_fields(
+            Self::fields(ctx, llvm_usize),
+            llvm_ndarray_ty,
+            "NDArray",
+            &[],
+        )
+    }
+
+    /// Returns an instance of [`StructFields`] containing all field accessors for this type.
+    #[must_use]
+    fn fields(
+        ctx: impl AsContextRef<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> NDArrayStructFields<'ctx> {
+        NDArrayStructFields::new(ctx, llvm_usize)
+    }
+
+    /// See [`NDArrayType::fields`].
+    // TODO: Move this into e.g. StructProxyType
+    #[must_use]
+    pub fn get_fields(&self, ctx: impl AsContextRef<'ctx>) -> NDArrayStructFields<'ctx> {
+        Self::fields(ctx, self.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> {
+        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>,
+        ndims: u64,
+    ) -> Self {
+        let llvm_usize = generator.get_size_type(ctx);
+        let llvm_ndarray = Self::llvm_type(ctx, llvm_usize);
+
+        NDArrayType { ty: llvm_ndarray, dtype, ndims, llvm_usize }
+    }
+
+    /// Creates an instance of [`NDArrayType`] as a result of a broadcast operation over one or more
+    /// `ndarray` operands.
+    #[must_use]
+    pub fn new_broadcast<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &'ctx Context,
+        dtype: BasicTypeEnum<'ctx>,
+        inputs: &[NDArrayType<'ctx>],
+    ) -> Self {
+        assert!(!inputs.is_empty());
+
+        Self::new(generator, ctx, dtype, inputs.iter().map(NDArrayType::ndims).max().unwrap())
+    }
+
+    /// Creates an instance of [`NDArrayType`] with `ndims` of 0.
+    #[must_use]
+    pub fn new_unsized<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, ndims: 0, llvm_usize }
+    }
+
+    /// Creates an [`NDArrayType`] from a [unifier type][Type].
+    #[must_use]
+    pub fn from_unifier_type<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ty: Type,
+    ) -> Self {
+        let (dtype, ndims) = unpack_ndarray_var_tys(&mut ctx.unifier, ty);
+
+        let llvm_dtype = ctx.get_llvm_type(generator, dtype);
+        let llvm_usize = generator.get_size_type(ctx.ctx);
+        let ndims = extract_ndims(&ctx.unifier, ndims);
+
+        NDArrayType {
+            ty: Self::llvm_type(ctx.ctx, llvm_usize),
+            dtype: llvm_dtype,
+            ndims,
+            llvm_usize,
+        }
+    }
+
+    /// Creates an [`NDArrayType`] from a [`PointerType`] representing an `NDArray`.
+    #[must_use]
+    pub fn from_type(
+        ptr_ty: PointerType<'ctx>,
+        dtype: BasicTypeEnum<'ctx>,
+        ndims: u64,
+        llvm_usize: IntType<'ctx>,
+    ) -> Self {
+        debug_assert!(Self::is_representable(ptr_ty, llvm_usize).is_ok());
+
+        NDArrayType { ty: ptr_ty, dtype, ndims, llvm_usize }
+    }
+
+    /// Returns the type of the `size` field of this `ndarray` type.
+    #[must_use]
+    pub fn size_type(&self) -> IntType<'ctx> {
+        self.llvm_usize
+    }
+
+    /// Returns the element type of this `ndarray` type.
+    #[must_use]
+    pub fn element_type(&self) -> BasicTypeEnum<'ctx> {
+        self.dtype
+    }
+
+    /// Returns the number of dimensions of this `ndarray` type.
+    #[must_use]
+    pub fn ndims(&self) -> u64 {
+        self.ndims
+    }
+
+    /// Allocates an instance of [`NDArrayValue`] as if by calling `alloca` on the base type.
+    ///
+    /// See [`ProxyType::raw_alloca`].
+    #[must_use]
+    pub fn alloca(
+        &self,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca(ctx, name),
+            self.dtype,
+            self.ndims,
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Allocates an instance of [`NDArrayValue`] as if by calling `alloca` on the base type.
+    ///
+    /// See [`ProxyType::raw_alloca_var`].
+    #[must_use]
+    pub fn alloca_var<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca_var(generator, ctx, name),
+            self.dtype,
+            self.ndims,
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Allocates an [`NDArrayValue`] on the stack and initializes all fields as follows:
+    ///
+    /// - `data`: uninitialized.
+    /// - `itemsize`: set to the size of `self.dtype`.
+    /// - `ndims`: set to the value of  `ndims`.
+    /// - `shape`: allocated on the stack with an array of length `ndims` with uninitialized values.
+    /// - `strides`: allocated on the stack with an array of length `ndims` with uninitialized
+    ///   values.
+    #[must_use]
+    fn construct_impl<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndims: IntValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        let ndarray = self.alloca_var(generator, ctx, name);
+
+        let itemsize = ctx
+            .builder
+            .build_int_truncate_or_bit_cast(self.dtype.size_of().unwrap(), self.llvm_usize, "")
+            .unwrap();
+        ndarray.store_itemsize(ctx, generator, itemsize);
+
+        ndarray.store_ndims(ctx, generator, ndims);
+
+        ndarray.create_shape(ctx, self.llvm_usize, ndims);
+        ndarray.create_strides(ctx, self.llvm_usize, ndims);
+
+        ndarray
+    }
+
+    /// Allocate an [`NDArrayValue`] on the stack using `dtype` and `ndims` of this [`NDArrayType`]
+    /// instance.
+    ///
+    /// The returned ndarray's content will be:
+    /// - `data`: uninitialized.
+    /// - `itemsize`: set to the size of `dtype`.
+    /// - `ndims`: set to the value of `self.ndims`.
+    /// - `shape`: allocated on the stack with an array of length `ndims` with uninitialized values.
+    /// - `strides`: allocated on the stack with an array of length `ndims` with uninitialized
+    ///   values.
+    #[must_use]
+    pub fn construct_uninitialized<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        let ndims = self.llvm_usize.const_int(self.ndims, false);
+
+        self.construct_impl(generator, ctx, ndims, name)
+    }
+
+    /// Convenience function. Allocate an [`NDArrayValue`] with a statically known shape.
+    ///
+    /// The returned [`NDArrayValue`]'s `data` and `strides` are uninitialized.
+    #[must_use]
+    pub fn construct_const_shape<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        shape: &[u64],
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        assert_eq!(shape.len() as u64, self.ndims);
+
+        let ndarray = Self::new(generator, ctx.ctx, self.dtype, shape.len() as u64)
+            .construct_uninitialized(generator, ctx, name);
+
+        let llvm_usize = generator.get_size_type(ctx.ctx);
+
+        // Write shape
+        let ndarray_shape = ndarray.shape();
+        for (i, dim) in shape.iter().enumerate() {
+            let dim = llvm_usize.const_int(*dim, false);
+            unsafe {
+                ndarray_shape.set_typed_unchecked(
+                    ctx,
+                    generator,
+                    &llvm_usize.const_int(i as u64, false),
+                    dim,
+                );
+            }
+        }
+
+        ndarray
+    }
+
+    /// Convenience function. Allocate an [`NDArrayValue`] with a dynamically known shape.
+    ///
+    /// The returned [`NDArrayValue`]'s `data` and `strides` are uninitialized.
+    #[must_use]
+    pub fn construct_dyn_shape<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        shape: &[IntValue<'ctx>],
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        assert_eq!(shape.len() as u64, self.ndims);
+
+        let ndarray = Self::new(generator, ctx.ctx, self.dtype, shape.len() as u64)
+            .construct_uninitialized(generator, ctx, name);
+
+        let llvm_usize = generator.get_size_type(ctx.ctx);
+
+        // Write shape
+        let ndarray_shape = ndarray.shape();
+        for (i, dim) in shape.iter().enumerate() {
+            assert_eq!(
+                dim.get_type(),
+                llvm_usize,
+                "Expected {} but got {}",
+                llvm_usize.print_to_string(),
+                dim.get_type().print_to_string()
+            );
+            unsafe {
+                ndarray_shape.set_typed_unchecked(
+                    ctx,
+                    generator,
+                    &llvm_usize.const_int(i as u64, false),
+                    *dim,
+                );
+            }
+        }
+
+        ndarray
+    }
+
+    /// Create an unsized ndarray to contain `value`.
+    #[must_use]
+    pub fn construct_unsized<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        value: &impl BasicValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> NDArrayValue<'ctx> {
+        let value = value.as_basic_value_enum();
+
+        assert_eq!(value.get_type(), self.dtype);
+        assert_eq!(self.ndims, 0);
+
+        // We have to put the value on the stack to get a data pointer.
+        let data = ctx.builder.build_alloca(value.get_type(), "construct_unsized").unwrap();
+        ctx.builder.build_store(data, value).unwrap();
+        let data = ctx
+            .builder
+            .build_pointer_cast(data, ctx.ctx.i8_type().ptr_type(AddressSpace::default()), "")
+            .unwrap();
+
+        let ndarray = Self::new_unsized(generator, ctx.ctx, value.get_type())
+            .construct_uninitialized(generator, ctx, name);
+        ctx.builder.build_store(ndarray.ptr_to_data(ctx), data).unwrap();
+        ndarray
+    }
+
+    /// Converts an existing value into a [`NDArrayValue`].
+    #[must_use]
+    pub fn map_value(
+        &self,
+        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            value,
+            self.dtype,
+            self.ndims,
+            self.llvm_usize,
+            name,
+        )
+    }
+}
+
+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 alloca_type(&self) -> impl BasicType<'ctx> {
+        self.as_base_type().get_element_type().into_struct_type()
+    }
+
+    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/ndarray/nditer.rs
+++ b/nac3core/src/codegen/types/ndarray/nditer.rs
@ -0,0 +1,237 @@
+use inkwell::{
+    context::{AsContextRef, Context},
+    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
+    values::{IntValue, PointerValue},
+    AddressSpace,
+};
+use itertools::Itertools;
+
+use nac3core_derive::StructFields;
+
+use super::ProxyType;
+use crate::codegen::{
+    irrt,
+    types::structure::{check_struct_type_matches_fields, StructField, StructFields},
+    values::{
+        ndarray::{NDArrayValue, NDIterValue},
+        ArrayLikeValue, ArraySliceValue, ProxyValue, TypedArrayLikeAdapter,
+    },
+    CodeGenContext, CodeGenerator,
+};
+
+#[derive(Debug, PartialEq, Eq, Clone, Copy)]
+pub struct NDIterType<'ctx> {
+    ty: PointerType<'ctx>,
+    llvm_usize: IntType<'ctx>,
+}
+
+#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
+pub struct NDIterStructFields<'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(usize.ptr_type(AddressSpace::default()))]
+    pub strides: StructField<'ctx, PointerValue<'ctx>>,
+    #[value_type(usize.ptr_type(AddressSpace::default()))]
+    pub indices: StructField<'ctx, PointerValue<'ctx>>,
+    #[value_type(usize)]
+    pub nth: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(i8_type().ptr_type(AddressSpace::default()))]
+    pub element: StructField<'ctx, PointerValue<'ctx>>,
+    #[value_type(usize)]
+    pub size: StructField<'ctx, IntValue<'ctx>>,
+}
+
+impl<'ctx> NDIterType<'ctx> {
+    /// Checks whether `llvm_ty` represents a `nditer` type, returning [Err] if it does not.
+    pub fn is_representable(
+        llvm_ty: PointerType<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        let ctx = llvm_ty.get_context();
+
+        let llvm_ty = llvm_ty.get_element_type();
+        let AnyTypeEnum::StructType(llvm_ndarray_ty) = llvm_ty else {
+            return Err(format!("Expected struct type for `NDIter` type, got {llvm_ty}"));
+        };
+
+        check_struct_type_matches_fields(
+            Self::fields(ctx, llvm_usize),
+            llvm_ndarray_ty,
+            "NDIter",
+            &[],
+        )
+    }
+
+    /// Returns an instance of [`StructFields`] containing all field accessors for this type.
+    #[must_use]
+    fn fields(ctx: impl AsContextRef<'ctx>, llvm_usize: IntType<'ctx>) -> NDIterStructFields<'ctx> {
+        NDIterStructFields::new(ctx, llvm_usize)
+    }
+
+    /// See [`NDIterType::fields`].
+    // TODO: Move this into e.g. StructProxyType
+    #[must_use]
+    pub fn get_fields(&self, ctx: impl AsContextRef<'ctx>) -> NDIterStructFields<'ctx> {
+        Self::fields(ctx, self.llvm_usize)
+    }
+
+    /// Creates an LLVM type corresponding to the expected structure of an `NDIter`.
+    #[must_use]
+    fn llvm_type(ctx: &'ctx Context, llvm_usize: IntType<'ctx>) -> PointerType<'ctx> {
+        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 [`NDIter`].
+    #[must_use]
+    pub fn new<G: CodeGenerator + ?Sized>(generator: &G, ctx: &'ctx Context) -> Self {
+        let llvm_usize = generator.get_size_type(ctx);
+        let llvm_nditer = Self::llvm_type(ctx, llvm_usize);
+
+        Self { ty: llvm_nditer, llvm_usize }
+    }
+
+    /// Creates an [`NDIterType`] from a [`PointerType`] representing an `NDIter`.
+    #[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());
+
+        Self { ty: ptr_ty, llvm_usize }
+    }
+
+    /// Returns the type of the `size` field of this `nditer` type.
+    #[must_use]
+    pub fn size_type(&self) -> IntType<'ctx> {
+        self.llvm_usize
+    }
+
+    /// Allocates an instance of [`NDIterValue`] as if by calling `alloca` on the base type.
+    ///
+    /// See [`ProxyType::raw_alloca`].
+    #[must_use]
+    pub fn alloca(
+        &self,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        parent: NDArrayValue<'ctx>,
+        indices: ArraySliceValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca(ctx, name),
+            parent,
+            indices,
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Allocates an instance of [`NDIterValue`] as if by calling `alloca` on the base type.
+    ///
+    /// See [`ProxyType::raw_alloca_var`].
+    #[must_use]
+    pub fn alloca_var<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        parent: NDArrayValue<'ctx>,
+        indices: ArraySliceValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca_var(generator, ctx, name),
+            parent,
+            indices,
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Allocate an [`NDIter`] that iterates through the given `ndarray`.
+    ///
+    /// Note: This function allocates an array on the stack at the current builder location, which
+    /// may lead to stack explosion if called in a hot loop. Therefore, callers are recommended to
+    /// call `llvm.stacksave` before calling this function and call `llvm.stackrestore` after the
+    /// [`NDIter`] is no longer needed.
+    #[must_use]
+    pub fn construct<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndarray: NDArrayValue<'ctx>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        let nditer = self.raw_alloca_var(generator, ctx, None);
+        let ndims = self.llvm_usize.const_int(ndarray.get_type().ndims(), false);
+
+        // The caller has the responsibility to allocate 'indices' for `NDIter`.
+        let indices =
+            generator.gen_array_var_alloc(ctx, self.llvm_usize.into(), ndims, None).unwrap();
+        let indices =
+            TypedArrayLikeAdapter::from(indices, |_, _, v| v.into_int_value(), |_, _, v| v.into());
+
+        let nditer = self.map_value(nditer, ndarray, indices.as_slice_value(ctx, generator), None);
+
+        irrt::ndarray::call_nac3_nditer_initialize(generator, ctx, nditer, ndarray, &indices);
+
+        nditer
+    }
+
+    #[must_use]
+    pub fn map_value(
+        &self,
+        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
+        parent: NDArrayValue<'ctx>,
+        indices: ArraySliceValue<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            value,
+            parent,
+            indices,
+            self.llvm_usize,
+            name,
+        )
+    }
+}
+
+impl<'ctx> ProxyType<'ctx> for NDIterType<'ctx> {
+    type Base = PointerType<'ctx>;
+    type Value = NDIterValue<'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 alloca_type(&self) -> impl BasicType<'ctx> {
+        self.as_base_type().get_element_type().into_struct_type()
+    }
+
+    fn as_base_type(&self) -> Self::Base {
+        self.ty
+    }
+}
+
+impl<'ctx> From<NDIterType<'ctx>> for PointerType<'ctx> {
+    fn from(value: NDIterType<'ctx>) -> Self {
+        value.as_base_type()
+    }
+}
--- a/nac3core/src/codegen/types/range.rs
+++ b/nac3core/src/codegen/types/range.rs
@ -0,0 +1,155 @@
+use inkwell::{
+    context::Context,
+    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
+    AddressSpace,
+};
+
+use super::ProxyType;
+use crate::codegen::{
+    values::{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()
+    }
+
+    /// Allocates an instance of [`RangeValue`] as if by calling `alloca` on the base type.
+    ///
+    /// See [`ProxyType::raw_alloca`].
+    #[must_use]
+    pub fn alloca<G: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(self.raw_alloca(ctx, name), name)
+    }
+
+    /// Allocates an instance of [`RangeValue`] as if by calling `alloca` on the base type.
+    ///
+    /// See [`ProxyType::raw_alloca_var`].
+    #[must_use]
+    pub fn alloca_var<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca_var(generator, ctx, name),
+            name,
+        )
+    }
+
+    /// Converts an existing value into a [`RangeValue`].
+    #[must_use]
+    pub fn map_value(
+        &self,
+        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(value, name)
+    }
+}
+
+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 alloca_type(&self) -> impl BasicType<'ctx> {
+        self.as_base_type().get_element_type().into_struct_type()
+    }
+
+    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 +1,270 @@
+use std::marker::PhantomData;
+
+use inkwell::{
+    context::AsContextRef,
+    types::{BasicTypeEnum, IntType, StructType},
+    values::{BasicValue, BasicValueEnum, IntValue, PointerValue, StructValue},
+};
+use itertools::Itertools;
+
+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()
+    }
+
+    /// Returns the field index of a field in this structure.
+    fn index_of_field<V>(&self, name: impl FnOnce(&Self) -> StructField<'ctx, V>) -> u32
+    where
+        V: BasicValue<'ctx> + TryFrom<BasicValueEnum<'ctx>, Error = ()>,
+    {
+        let field_name = name(self).name;
+        self.index_of_field_name(field_name).unwrap()
+    }
+
+    /// Returns the field index of a field with the given name in this structure.
+    fn index_of_field_name(&self, field_name: &str) -> Option<u32> {
+        self.iter().find_position(|(name, _)| *name == field_name).map(|(idx, _)| idx as u32)
+    }
+}
+
+/// 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 }
+    }
+
+    /// Returns the name of this field.
+    #[must_use]
+    pub fn name(&self) -> &'static str {
+        self.name
+    }
+
+    /// 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_for_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
+    }
+}
+
+type FieldTypeVerifier<'ctx> = dyn Fn(BasicTypeEnum<'ctx>) -> Result<(), String>;
+
+/// Checks whether [`llvm_ty`][StructType] contains the fields described by the given
+/// [`StructFields`] instance.
+///
+/// By default, this function will compare the type of each field in `expected_fields` against
+/// `llvm_ty`. To override this behavior for individual fields, pass in overrides to
+/// `custom_verifiers`, which will use the specified verifier when a field with the matching field
+/// name is being checked.
+pub(super) fn check_struct_type_matches_fields<'ctx>(
+    expected_fields: impl StructFields<'ctx>,
+    llvm_ty: StructType<'ctx>,
+    ty_name: &'static str,
+    custom_verifiers: &[(&str, &FieldTypeVerifier<'ctx>)],
+) -> Result<(), String> {
+    let expected_fields = expected_fields.to_vec();
+
+    if llvm_ty.count_fields() != u32::try_from(expected_fields.len()).unwrap() {
+        return Err(format!(
+            "Expected {} fields in `{ty_name}`, got {}",
+            expected_fields.len(),
+            llvm_ty.count_fields(),
+        ));
+    }
+
+    expected_fields
+        .into_iter()
+        .enumerate()
+        .map(|(i, (field_name, expected_ty))| {
+            (field_name, expected_ty, llvm_ty.get_field_type_at_index(i as u32).unwrap())
+        })
+        .try_for_each(|(field_name, expected_ty, actual_ty)| {
+            if let Some((_, verifier)) =
+                custom_verifiers.iter().find(|verifier| verifier.0 == field_name)
+            {
+                verifier(actual_ty)
+            } else if expected_ty == actual_ty {
+                Ok(())
+            } else {
+                Err(format!("Expected {expected_ty} for `{ty_name}.{field_name}`, got {actual_ty}"))
+            }
+        })?;
+
+    Ok(())
+}
--- a/nac3core/src/codegen/types/tuple.rs
+++ b/nac3core/src/codegen/types/tuple.rs
@ -0,0 +1,184 @@
+use inkwell::{
+    context::Context,
+    types::{BasicType, BasicTypeEnum, IntType, StructType},
+    values::BasicValueEnum,
+};
+use itertools::Itertools;
+
+use super::ProxyType;
+use crate::{
+    codegen::{
+        values::{ProxyValue, TupleValue},
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::{Type, TypeEnum},
+};
+
+#[derive(Debug, PartialEq, Eq, Clone)]
+pub struct TupleType<'ctx> {
+    ty: StructType<'ctx>,
+    llvm_usize: IntType<'ctx>,
+}
+
+impl<'ctx> TupleType<'ctx> {
+    /// Checks whether `llvm_ty` represents any tuple type, returning [Err] if it does not.
+    pub fn is_representable(_value: StructType<'ctx>) -> Result<(), String> {
+        Ok(())
+    }
+
+    /// Creates an LLVM type corresponding to the expected structure of a tuple.
+    #[must_use]
+    fn llvm_type(ctx: &'ctx Context, tys: &[BasicTypeEnum<'ctx>]) -> StructType<'ctx> {
+        ctx.struct_type(tys, false)
+    }
+
+    /// Creates an instance of [`TupleType`].
+    #[must_use]
+    pub fn new<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &'ctx Context,
+        tys: &[BasicTypeEnum<'ctx>],
+    ) -> Self {
+        let llvm_usize = generator.get_size_type(ctx);
+        let llvm_tuple = Self::llvm_type(ctx, tys);
+
+        Self { ty: llvm_tuple, llvm_usize }
+    }
+
+    /// Creates an [`TupleType`] from a [unifier type][Type].
+    #[must_use]
+    pub fn from_unifier_type<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ty: Type,
+    ) -> Self {
+        let llvm_usize = generator.get_size_type(ctx.ctx);
+
+        // Sanity check on object type.
+        let TypeEnum::TTuple { ty: tys, .. } = &*ctx.unifier.get_ty_immutable(ty) else {
+            panic!("Expected type to be a TypeEnum::TTuple, got {}", ctx.unifier.stringify(ty));
+        };
+
+        let llvm_tys = tys.iter().map(|ty| ctx.get_llvm_type(generator, *ty)).collect_vec();
+        Self { ty: Self::llvm_type(ctx.ctx, &llvm_tys), llvm_usize }
+    }
+
+    /// Creates an [`TupleType`] from a [`StructType`].
+    #[must_use]
+    pub fn from_type(struct_ty: StructType<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
+        debug_assert!(Self::is_representable(struct_ty).is_ok());
+
+        TupleType { ty: struct_ty, llvm_usize }
+    }
+
+    /// Returns the number of elements present in this [`TupleType`].
+    #[must_use]
+    pub fn num_elements(&self) -> u32 {
+        self.ty.count_fields()
+    }
+
+    /// Returns the type of the tuple element at the given `index`, or [`None`] if `index` is out of
+    /// range.
+    #[must_use]
+    pub fn type_at_index(&self, index: u32) -> Option<BasicTypeEnum<'ctx>> {
+        if index < self.num_elements() {
+            Some(unsafe { self.type_at_index_unchecked(index) })
+        } else {
+            None
+        }
+    }
+
+    /// Returns the type of the tuple element at the given `index`.
+    ///
+    /// # Safety
+    ///
+    /// The caller must ensure that the index is valid.
+    #[must_use]
+    pub unsafe fn type_at_index_unchecked(&self, index: u32) -> BasicTypeEnum<'ctx> {
+        self.ty.get_field_type_at_index_unchecked(index)
+    }
+
+    /// Constructs a [`TupleValue`] from this type by zero-initializing the tuple value.
+    #[must_use]
+    pub fn construct(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        self.map_value(Self::llvm_type(ctx.ctx, &self.ty.get_field_types()).const_zero(), name)
+    }
+
+    /// Constructs a [`TupleValue`] from `objects`. The resulting tuple preserves the order of
+    /// objects.
+    #[must_use]
+    pub fn construct_from_objects<I: IntoIterator<Item = BasicValueEnum<'ctx>>>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        objects: I,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        let values = objects.into_iter().collect_vec();
+
+        assert_eq!(values.len(), self.num_elements() as usize);
+        assert!(values
+            .iter()
+            .enumerate()
+            .all(|(i, v)| { v.get_type() == unsafe { self.type_at_index_unchecked(i as u32) } }));
+
+        let mut value = self.construct(ctx, name);
+        for (i, val) in values.into_iter().enumerate() {
+            value.store_element(ctx, i as u32, val);
+        }
+
+        value
+    }
+
+    /// Converts an existing value into a [`ListValue`].
+    #[must_use]
+    pub fn map_value(
+        &self,
+        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_struct_value(value, self.llvm_usize, name)
+    }
+}
+
+impl<'ctx> ProxyType<'ctx> for TupleType<'ctx> {
+    type Base = StructType<'ctx>;
+    type Value = TupleValue<'ctx>;
+
+    fn is_type<G: CodeGenerator + ?Sized>(
+        generator: &G,
+        ctx: &'ctx Context,
+        llvm_ty: impl BasicType<'ctx>,
+    ) -> Result<(), String> {
+        if let BasicTypeEnum::StructType(ty) = llvm_ty.as_basic_type_enum() {
+            <Self as ProxyType<'ctx>>::is_representable(generator, ctx, ty)
+        } else {
+            Err(format!("Expected struct 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)
+    }
+
+    fn alloca_type(&self) -> impl BasicType<'ctx> {
+        self.as_base_type()
+    }
+
+    fn as_base_type(&self) -> Self::Base {
+        self.ty
+    }
+}
+
+impl<'ctx> From<TupleType<'ctx>> for StructType<'ctx> {
+    fn from(value: TupleType<'ctx>) -> Self {
+        value.as_base_type()
+    }
+}
--- a/nac3core/src/codegen/types/utils/mod.rs
+++ b/nac3core/src/codegen/types/utils/mod.rs
@ -0,0 +1,3 @@
+pub use slice::*;
+
+mod slice;
--- a/nac3core/src/codegen/types/utils/slice.rs
+++ b/nac3core/src/codegen/types/utils/slice.rs
@ -0,0 +1,245 @@
+use inkwell::{
+    context::{AsContextRef, Context, ContextRef},
+    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType, PointerType},
+    values::IntValue,
+    AddressSpace,
+};
+use itertools::Itertools;
+
+use nac3core_derive::StructFields;
+
+use crate::codegen::{
+    types::{
+        structure::{
+            check_struct_type_matches_fields, FieldIndexCounter, StructField, StructFields,
+        },
+        ProxyType,
+    },
+    values::{utils::SliceValue, ProxyValue},
+    CodeGenContext, CodeGenerator,
+};
+
+#[derive(Debug, PartialEq, Eq, Clone, Copy)]
+pub struct SliceType<'ctx> {
+    ty: PointerType<'ctx>,
+    int_ty: IntType<'ctx>,
+    llvm_usize: IntType<'ctx>,
+}
+
+#[derive(PartialEq, Eq, Clone, Copy, StructFields)]
+pub struct SliceFields<'ctx> {
+    #[value_type(bool_type())]
+    pub start_defined: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(usize)]
+    pub start: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(bool_type())]
+    pub stop_defined: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(usize)]
+    pub stop: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(bool_type())]
+    pub step_defined: StructField<'ctx, IntValue<'ctx>>,
+    #[value_type(usize)]
+    pub step: StructField<'ctx, IntValue<'ctx>>,
+}
+
+impl<'ctx> SliceFields<'ctx> {
+    /// Creates a new instance of [`SliceFields`] with a custom integer type for its range values.
+    #[must_use]
+    pub fn new_sized(ctx: &impl AsContextRef<'ctx>, int_ty: IntType<'ctx>) -> Self {
+        let ctx = unsafe { ContextRef::new(ctx.as_ctx_ref()) };
+        let mut counter = FieldIndexCounter::default();
+
+        SliceFields {
+            start_defined: StructField::create(&mut counter, "start_defined", ctx.bool_type()),
+            start: StructField::create(&mut counter, "start", int_ty),
+            stop_defined: StructField::create(&mut counter, "stop_defined", ctx.bool_type()),
+            stop: StructField::create(&mut counter, "stop", int_ty),
+            step_defined: StructField::create(&mut counter, "step_defined", ctx.bool_type()),
+            step: StructField::create(&mut counter, "step", int_ty),
+        }
+    }
+}
+
+impl<'ctx> SliceType<'ctx> {
+    /// Checks whether `llvm_ty` represents a `slice` type, returning [Err] if it does not.
+    pub fn is_representable(
+        llvm_ty: PointerType<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        let ctx = llvm_ty.get_context();
+
+        let fields = SliceFields::new(ctx, llvm_usize);
+
+        let llvm_ty = llvm_ty.get_element_type();
+        let AnyTypeEnum::StructType(llvm_ty) = llvm_ty else {
+            return Err(format!("Expected struct type for `Slice` type, got {llvm_ty}"));
+        };
+
+        check_struct_type_matches_fields(
+            fields,
+            llvm_ty,
+            "Slice",
+            &[
+                (fields.start.name(), &|ty| {
+                    if ty.is_int_type() {
+                        Ok(())
+                    } else {
+                        Err(format!("Expected int type for `Slice.start`, got {ty}"))
+                    }
+                }),
+                (fields.stop.name(), &|ty| {
+                    if ty.is_int_type() {
+                        Ok(())
+                    } else {
+                        Err(format!("Expected int type for `Slice.stop`, got {ty}"))
+                    }
+                }),
+                (fields.step.name(), &|ty| {
+                    if ty.is_int_type() {
+                        Ok(())
+                    } else {
+                        Err(format!("Expected int type for `Slice.step`, got {ty}"))
+                    }
+                }),
+            ],
+        )
+    }
+
+    // TODO: Move this into e.g. StructProxyType
+    #[must_use]
+    pub fn get_fields(&self) -> SliceFields<'ctx> {
+        SliceFields::new_sized(&self.int_ty.get_context(), self.int_ty)
+    }
+
+    /// Creates an LLVM type corresponding to the expected structure of a `Slice`.
+    #[must_use]
+    fn llvm_type(ctx: &'ctx Context, int_ty: IntType<'ctx>) -> PointerType<'ctx> {
+        let field_tys = SliceFields::new_sized(&int_ty.get_context(), int_ty)
+            .into_iter()
+            .map(|field| field.1)
+            .collect_vec();
+
+        ctx.struct_type(&field_tys, false).ptr_type(AddressSpace::default())
+    }
+
+    /// Creates an instance of [`SliceType`] with `int_ty` as its backing integer type.
+    #[must_use]
+    pub fn new(ctx: &'ctx Context, int_ty: IntType<'ctx>, llvm_usize: IntType<'ctx>) -> Self {
+        let llvm_ty = Self::llvm_type(ctx, int_ty);
+
+        Self { ty: llvm_ty, int_ty, llvm_usize }
+    }
+
+    /// Creates an instance of [`SliceType`] with `usize` as its backing integer type.
+    #[must_use]
+    pub fn new_usize<G: CodeGenerator + ?Sized>(generator: &G, ctx: &'ctx Context) -> Self {
+        let llvm_usize = generator.get_size_type(ctx);
+        Self::new(ctx, llvm_usize, llvm_usize)
+    }
+
+    /// Creates an [`SliceType`] from a [`PointerType`] representing a `slice`.
+    #[must_use]
+    pub fn from_type(
+        ptr_ty: PointerType<'ctx>,
+        int_ty: IntType<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Self {
+        debug_assert!(Self::is_representable(ptr_ty, int_ty).is_ok());
+
+        Self { ty: ptr_ty, int_ty, llvm_usize }
+    }
+
+    #[must_use]
+    pub fn element_type(&self) -> IntType<'ctx> {
+        self.int_ty
+    }
+
+    /// Allocates an instance of [`SliceValue`] as if by calling `alloca` on the base type.
+    ///
+    /// See [`ProxyType::raw_alloca`].
+    #[must_use]
+    pub fn alloca(
+        &self,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca(ctx, name),
+            self.int_ty,
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Allocates an instance of [`SliceValue`] as if by calling `alloca` on the base type.
+    ///
+    /// See [`ProxyType::raw_alloca_var`].
+    #[must_use]
+    pub fn alloca_var<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            self.raw_alloca_var(generator, ctx, name),
+            self.int_ty,
+            self.llvm_usize,
+            name,
+        )
+    }
+
+    /// Converts an existing value into a [`ContiguousNDArrayValue`].
+    #[must_use]
+    pub fn map_value(
+        &self,
+        value: <<Self as ProxyType<'ctx>>::Value as ProxyValue<'ctx>>::Base,
+        name: Option<&'ctx str>,
+    ) -> <Self as ProxyType<'ctx>>::Value {
+        <Self as ProxyType<'ctx>>::Value::from_pointer_value(
+            value,
+            self.int_ty,
+            self.llvm_usize,
+            name,
+        )
+    }
+}
+
+impl<'ctx> ProxyType<'ctx> for SliceType<'ctx> {
+    type Base = PointerType<'ctx>;
+    type Value = SliceValue<'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 alloca_type(&self) -> impl BasicType<'ctx> {
+        self.as_base_type().get_element_type().into_struct_type()
+    }
+
+    fn as_base_type(&self) -> Self::Base {
+        self.ty
+    }
+}
+
+impl<'ctx> From<SliceType<'ctx>> for PointerType<'ctx> {
+    fn from(value: SliceType<'ctx>) -> Self {
+        value.as_base_type()
+    }
+}
--- a/nac3core/src/codegen/values/array.rs
+++ b/nac3core/src/codegen/values/array.rs
@ -0,0 +1,439 @@
+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: &CodeGenContext<'ctx, '_>,
+        generator: &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: &CodeGenContext<'ctx, '_>,
+        generator: &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: &CodeGenContext<'ctx, '_>,
+        generator: &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, G: CodeGenerator + ?Sized, T, Index = IntValue<'ctx>>:
+    UntypedArrayLikeAccessor<'ctx, Index>
+{
+    /// Casts an element from [`BasicValueEnum`] into `T`.
+    fn downcast_to_type(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        generator: &G,
+        value: BasicValueEnum<'ctx>,
+    ) -> T;
+
+    /// # Safety
+    ///
+    /// This function should be called with a valid index.
+    unsafe fn get_typed_unchecked(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        generator: &G,
+        idx: &Index,
+        name: Option<&str>,
+    ) -> T {
+        let value = unsafe { self.get_unchecked(ctx, generator, idx, name) };
+        self.downcast_to_type(ctx, generator, value)
+    }
+
+    /// Returns the data at the `idx`-th index.
+    fn get_typed(
+        &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, generator, value)
+    }
+}
+
+/// An array-like value that can have its array elements mutated as an arbitrary type `T`.
+pub trait TypedArrayLikeMutator<'ctx, G: CodeGenerator + ?Sized, T, Index = IntValue<'ctx>>:
+    UntypedArrayLikeMutator<'ctx, Index>
+{
+    /// Casts an element from T into [`BasicValueEnum`].
+    fn upcast_from_type(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        generator: &G,
+        value: T,
+    ) -> BasicValueEnum<'ctx>;
+
+    /// # Safety
+    ///
+    /// This function should be called with a valid index.
+    unsafe fn set_typed_unchecked(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        generator: &G,
+        idx: &Index,
+        value: T,
+    ) {
+        let value = self.upcast_from_type(ctx, generator, value);
+        unsafe { self.set_unchecked(ctx, generator, idx, value) }
+    }
+
+    /// Sets the data at the `idx`-th index.
+    fn set_typed(
+        &self,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        generator: &mut G,
+        idx: &Index,
+        value: T,
+    ) {
+        let value = self.upcast_from_type(ctx, generator, value);
+        self.set(ctx, generator, idx, value);
+    }
+}
+
+/// An adapter for constraining untyped array values as typed values.
+#[derive(Copy, Clone)]
+pub struct TypedArrayLikeAdapter<
+    'ctx,
+    G: CodeGenerator + ?Sized,
+    T,
+    Adapted: ArrayLikeValue<'ctx> = ArraySliceValue<'ctx>,
+> {
+    adapted: Adapted,
+    downcast_fn: fn(&CodeGenContext<'ctx, '_>, &G, BasicValueEnum<'ctx>) -> T,
+    upcast_fn: fn(&CodeGenContext<'ctx, '_>, &G, T) -> BasicValueEnum<'ctx>,
+}
+
+impl<'ctx, G: CodeGenerator + ?Sized, T, Adapted> TypedArrayLikeAdapter<'ctx, G, 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: fn(&CodeGenContext<'ctx, '_>, &G, BasicValueEnum<'ctx>) -> T,
+        upcast_fn: fn(&CodeGenContext<'ctx, '_>, &G, T) -> BasicValueEnum<'ctx>,
+    ) -> Self {
+        TypedArrayLikeAdapter { adapted, downcast_fn, upcast_fn }
+    }
+}
+
+impl<'ctx, G: CodeGenerator + ?Sized, T, Adapted> ArrayLikeValue<'ctx>
+    for TypedArrayLikeAdapter<'ctx, G, T, Adapted>
+where
+    Adapted: ArrayLikeValue<'ctx>,
+{
+    fn element_type<CG: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        generator: &CG,
+    ) -> AnyTypeEnum<'ctx> {
+        self.adapted.element_type(ctx, generator)
+    }
+
+    fn base_ptr<CG: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        generator: &CG,
+    ) -> PointerValue<'ctx> {
+        self.adapted.base_ptr(ctx, generator)
+    }
+
+    fn size<CG: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        generator: &CG,
+    ) -> IntValue<'ctx> {
+        self.adapted.size(ctx, generator)
+    }
+
+    fn as_slice_value<CG: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        generator: &CG,
+    ) -> ArraySliceValue<'ctx> {
+        self.adapted.as_slice_value(ctx, generator)
+    }
+}
+
+impl<'ctx, G: CodeGenerator + ?Sized, T, Index, Adapted> ArrayLikeIndexer<'ctx, Index>
+    for TypedArrayLikeAdapter<'ctx, G, T, Adapted>
+where
+    Adapted: ArrayLikeIndexer<'ctx, Index>,
+{
+    unsafe fn ptr_offset_unchecked<CG: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        generator: &CG,
+        idx: &Index,
+        name: Option<&str>,
+    ) -> PointerValue<'ctx> {
+        unsafe { self.adapted.ptr_offset_unchecked(ctx, generator, idx, name) }
+    }
+
+    fn ptr_offset<CG: CodeGenerator + ?Sized>(
+        &self,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        generator: &mut CG,
+        idx: &Index,
+        name: Option<&str>,
+    ) -> PointerValue<'ctx> {
+        self.adapted.ptr_offset(ctx, generator, idx, name)
+    }
+}
+
+impl<'ctx, G: CodeGenerator + ?Sized, T, Index, Adapted> UntypedArrayLikeAccessor<'ctx, Index>
+    for TypedArrayLikeAdapter<'ctx, G, T, Adapted>
+where
+    Adapted: UntypedArrayLikeAccessor<'ctx, Index>,
+{
+}
+impl<'ctx, G: CodeGenerator + ?Sized, T, Index, Adapted> UntypedArrayLikeMutator<'ctx, Index>
+    for TypedArrayLikeAdapter<'ctx, G, T, Adapted>
+where
+    Adapted: UntypedArrayLikeMutator<'ctx, Index>,
+{
+}
+
+impl<'ctx, G: CodeGenerator + ?Sized, T, Index, Adapted> TypedArrayLikeAccessor<'ctx, G, T, Index>
+    for TypedArrayLikeAdapter<'ctx, G, T, Adapted>
+where
+    Adapted: UntypedArrayLikeAccessor<'ctx, Index>,
+{
+    fn downcast_to_type(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        generator: &G,
+        value: BasicValueEnum<'ctx>,
+    ) -> T {
+        (self.downcast_fn)(ctx, generator, value)
+    }
+}
+
+impl<'ctx, G: CodeGenerator + ?Sized, T, Index, Adapted> TypedArrayLikeMutator<'ctx, G, T, Index>
+    for TypedArrayLikeAdapter<'ctx, G, T, Adapted>
+where
+    Adapted: UntypedArrayLikeMutator<'ctx, Index>,
+{
+    fn upcast_from_type(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        generator: &G,
+        value: T,
+    ) -> BasicValueEnum<'ctx> {
+        (self.upcast_fn)(ctx, generator, 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: &CodeGenContext<'ctx, '_>,
+        generator: &G,
+        idx: &IntValue<'ctx>,
+        name: Option<&str>,
+    ) -> PointerValue<'ctx> {
+        let var_name = name.or(self.2).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 +1,234 @@
+use inkwell::{
+    types::{AnyTypeEnum, BasicType, BasicTypeEnum, IntType},
+    values::{BasicValueEnum, IntValue, PointerValue},
+    AddressSpace, IntPredicate,
+};
+
+use super::{
+    ArrayLikeIndexer, ArrayLikeValue, ProxyValue, UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
+};
+use crate::codegen::{
+    types::{structure::StructField, ListType, ProxyType},
+    {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 }
+    }
+
+    fn items_field(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, PointerValue<'ctx>> {
+        self.get_type().get_fields(&ctx.ctx).items
+    }
+
+    /// 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> {
+        self.items_field(ctx).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>) {
+        self.items_field(ctx).set(ctx, self.value, data, self.name);
+    }
+
+    /// 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. If
+    /// `size` is resolved to `0` at runtime, `(T*) 0` will be assigned to `data`.
+    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)
+    }
+
+    fn len_field(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields(&ctx.ctx).len
+    }
+
+    /// 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));
+
+        self.len_field(ctx).set(ctx, self.value, size, self.name);
+    }
+
+    /// Returns the size of this `list` as a value.
+    pub fn load_size(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        name: Option<&'ctx str>,
+    ) -> IntValue<'ctx> {
+        self.len_field(ctx).get(ctx, self.value, name)
+    }
+
+    /// Returns an instance of [`ListValue`] with the `items` pointer cast to `i8*`.
+    #[must_use]
+    pub fn as_i8_list<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &G,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> ListValue<'ctx> {
+        let llvm_i8 = ctx.ctx.i8_type();
+        let llvm_list_i8 = <Self as ProxyValue>::Type::new(generator, ctx.ctx, llvm_i8.into());
+
+        Self::from_pointer_value(
+            ctx.builder.build_pointer_cast(self.value, llvm_list_i8.as_base_type(), "").unwrap(),
+            self.llvm_usize,
+            self.name,
+        )
+    }
+}
+
+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: &CodeGenContext<'ctx, '_>,
+        generator: &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 +1,49 @@
+use inkwell::{context::Context, values::BasicValue};
+
+use super::types::ProxyType;
+use crate::codegen::CodeGenerator;
+pub use array::*;
+pub use list::*;
+pub use range::*;
+pub use tuple::*;
+
+mod array;
+mod list;
+pub mod ndarray;
+mod range;
+mod tuple;
+pub mod utils;
+
+/// 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/broadcast.rs
+++ b/nac3core/src/codegen/values/ndarray/broadcast.rs
@ -0,0 +1,243 @@
+use inkwell::{
+    types::IntType,
+    values::{IntValue, PointerValue},
+};
+use itertools::Itertools;
+
+use crate::codegen::{
+    irrt,
+    types::{
+        ndarray::{NDArrayType, ShapeEntryType},
+        structure::StructField,
+        ProxyType,
+    },
+    values::{
+        ndarray::NDArrayValue, ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ProxyValue,
+        TypedArrayLikeAccessor, TypedArrayLikeAdapter, TypedArrayLikeMutator,
+    },
+    CodeGenContext, CodeGenerator,
+};
+
+#[derive(Copy, Clone)]
+pub struct ShapeEntryValue<'ctx> {
+    value: PointerValue<'ctx>,
+    llvm_usize: IntType<'ctx>,
+    name: Option<&'ctx str>,
+}
+
+impl<'ctx> ShapeEntryValue<'ctx> {
+    /// Checks whether `value` is an instance of `ShapeEntry`, returning [Err] if `value` is
+    /// not an instance.
+    pub fn is_representable(
+        value: PointerValue<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        <Self as ProxyValue<'ctx>>::Type::is_representable(value.get_type(), llvm_usize)
+    }
+
+    /// Creates an [`ShapeEntryValue`] 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());
+
+        Self { value: ptr, llvm_usize, name }
+    }
+
+    fn ndims_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields(self.value.get_type().get_context()).ndims
+    }
+
+    /// Stores the number of dimensions into this value.
+    pub fn store_ndims(&self, ctx: &CodeGenContext<'ctx, '_>, value: IntValue<'ctx>) {
+        self.ndims_field().set(ctx, self.value, value, self.name);
+    }
+
+    fn shape_field(&self) -> StructField<'ctx, PointerValue<'ctx>> {
+        self.get_type().get_fields(self.value.get_type().get_context()).shape
+    }
+
+    /// Stores the shape into this value.
+    pub fn store_shape(&self, ctx: &CodeGenContext<'ctx, '_>, value: PointerValue<'ctx>) {
+        self.shape_field().set(ctx, self.value, value, self.name);
+    }
+}
+
+impl<'ctx> ProxyValue<'ctx> for ShapeEntryValue<'ctx> {
+    type Base = PointerValue<'ctx>;
+    type Type = ShapeEntryType<'ctx>;
+
+    fn get_type(&self) -> Self::Type {
+        Self::Type::from_type(self.value.get_type(), self.llvm_usize)
+    }
+
+    fn as_base_value(&self) -> Self::Base {
+        self.value
+    }
+}
+
+impl<'ctx> From<ShapeEntryValue<'ctx>> for PointerValue<'ctx> {
+    fn from(value: ShapeEntryValue<'ctx>) -> Self {
+        value.as_base_value()
+    }
+}
+
+impl<'ctx> NDArrayValue<'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: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+    ) -> Self {
+        assert!(self.ndims <= target_ndims);
+        assert_eq!(target_shape.element_type(ctx, generator), self.llvm_usize.into());
+
+        let broadcast_ndarray = NDArrayType::new(generator, ctx.ctx, self.dtype, target_ndims)
+            .construct_uninitialized(generator, ctx, None);
+        broadcast_ndarray.copy_shape_from_array(
+            generator,
+            ctx,
+            target_shape.base_ptr(ctx, generator),
+        );
+
+        irrt::ndarray::call_nac3_ndarray_broadcast_to(generator, ctx, *self, broadcast_ndarray);
+        broadcast_ndarray
+    }
+}
+
+/// A result produced by [`broadcast_all_ndarrays`]
+#[derive(Clone)]
+pub struct BroadcastAllResult<'ctx, G: CodeGenerator + ?Sized> {
+    /// The statically known `ndims` of the broadcast result.
+    pub ndims: u64,
+
+    /// The broadcasting shape.
+    pub shape: TypedArrayLikeAdapter<'ctx, G, IntValue<'ctx>>,
+
+    /// 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<NDArrayValue<'ctx>>,
+}
+
+/// Helper function to call [`irrt::ndarray::call_nac3_ndarray_broadcast_shapes`].
+fn broadcast_shapes<'ctx, G, Shape>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    in_shape_entries: &[(ArraySliceValue<'ctx>, u64)], // (shape, shape's length/ndims)
+    broadcast_ndims: u64,
+    broadcast_shape: &Shape,
+) where
+    G: CodeGenerator + ?Sized,
+    Shape: TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>
+        + TypedArrayLikeMutator<'ctx, G, IntValue<'ctx>>,
+{
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_shape_ty = ShapeEntryType::new(generator, ctx.ctx);
+
+    assert!(in_shape_entries
+        .iter()
+        .all(|entry| entry.0.element_type(ctx, generator) == llvm_usize.into()));
+    assert_eq!(broadcast_shape.element_type(ctx, generator), llvm_usize.into());
+
+    // Prepare input shape entries to be passed to `call_nac3_ndarray_broadcast_shapes`.
+    let num_shape_entries =
+        llvm_usize.const_int(u64::try_from(in_shape_entries.len()).unwrap(), false);
+    let shape_entries = llvm_shape_ty.array_alloca(ctx, num_shape_entries, None);
+    for (i, (in_shape, in_ndims)) in in_shape_entries.iter().enumerate() {
+        let pshape_entry = unsafe {
+            shape_entries.ptr_offset_unchecked(
+                ctx,
+                generator,
+                &llvm_usize.const_int(i as u64, false),
+                None,
+            )
+        };
+        let shape_entry = llvm_shape_ty.map_value(pshape_entry, None);
+
+        let in_ndims = llvm_usize.const_int(*in_ndims, false);
+        shape_entry.store_ndims(ctx, in_ndims);
+
+        shape_entry.store_shape(ctx, in_shape.base_ptr(ctx, generator));
+    }
+
+    let broadcast_ndims = llvm_usize.const_int(broadcast_ndims, false);
+    irrt::ndarray::call_nac3_ndarray_broadcast_shapes(
+        generator,
+        ctx,
+        num_shape_entries,
+        shape_entries,
+        broadcast_ndims,
+        broadcast_shape,
+    );
+}
+
+impl<'ctx> NDArrayType<'ctx> {
+    /// Broadcast all ndarrays according to
+    /// [`np.broadcast()`](https://numpy.org/doc/stable/reference/generated/numpy.broadcast.html)
+    /// and return a [`BroadcastAllResult`] containing all the information of the result of the
+    /// broadcast operation.
+    pub fn broadcast<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        ndarrays: &[NDArrayValue<'ctx>],
+    ) -> BroadcastAllResult<'ctx, G> {
+        assert!(!ndarrays.is_empty());
+
+        let llvm_usize = generator.get_size_type(ctx.ctx);
+
+        // Infer the broadcast output ndims.
+        let broadcast_ndims_int =
+            ndarrays.iter().map(|ndarray| ndarray.get_type().ndims()).max().unwrap();
+        assert!(self.ndims() >= broadcast_ndims_int);
+
+        let broadcast_ndims = llvm_usize.const_int(broadcast_ndims_int, false);
+        let broadcast_shape = ArraySliceValue::from_ptr_val(
+            ctx.builder.build_array_alloca(llvm_usize, broadcast_ndims, "").unwrap(),
+            broadcast_ndims,
+            None,
+        );
+        let broadcast_shape = TypedArrayLikeAdapter::from(
+            broadcast_shape,
+            |_, _, val| val.into_int_value(),
+            |_, _, val| val.into(),
+        );
+
+        let shape_entries = ndarrays
+            .iter()
+            .map(|ndarray| {
+                (ndarray.shape().as_slice_value(ctx, generator), ndarray.get_type().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 = 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/values/ndarray/contiguous.rs
+++ b/nac3core/src/codegen/values/ndarray/contiguous.rs
@ -0,0 +1,200 @@
+use inkwell::{
+    types::{BasicType, BasicTypeEnum, IntType},
+    values::{IntValue, PointerValue},
+    AddressSpace,
+};
+
+use super::{ArrayLikeValue, NDArrayValue, ProxyValue};
+use crate::codegen::{
+    stmt::gen_if_callback,
+    types::{
+        ndarray::{ContiguousNDArrayType, NDArrayType},
+        structure::StructField,
+    },
+    CodeGenContext, CodeGenerator,
+};
+
+#[derive(Copy, Clone)]
+pub struct ContiguousNDArrayValue<'ctx> {
+    value: PointerValue<'ctx>,
+    item: BasicTypeEnum<'ctx>,
+    llvm_usize: IntType<'ctx>,
+    name: Option<&'ctx str>,
+}
+
+impl<'ctx> ContiguousNDArrayValue<'ctx> {
+    /// Checks whether `value` is an instance of `ContiguousNDArray`, returning [Err] if `value` is
+    /// not an instance.
+    pub fn is_representable(
+        value: PointerValue<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        <Self as ProxyValue<'ctx>>::Type::is_representable(value.get_type(), llvm_usize)
+    }
+
+    /// Creates an [`ContiguousNDArrayValue`] 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());
+
+        Self { value: ptr, item: dtype, llvm_usize, name }
+    }
+
+    fn ndims_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().ndims
+    }
+
+    pub fn store_ndims(&self, ctx: &CodeGenContext<'ctx, '_>, value: IntValue<'ctx>) {
+        self.ndims_field().set(ctx, self.as_base_value(), value, self.name);
+    }
+
+    fn shape_field(&self) -> StructField<'ctx, PointerValue<'ctx>> {
+        self.get_type().get_fields().shape
+    }
+
+    pub fn store_shape(&self, ctx: &CodeGenContext<'ctx, '_>, value: PointerValue<'ctx>) {
+        self.shape_field().set(ctx, self.as_base_value(), value, self.name);
+    }
+
+    pub fn load_shape(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
+        self.shape_field().get(ctx, self.value, self.name)
+    }
+
+    fn data_field(&self) -> StructField<'ctx, PointerValue<'ctx>> {
+        self.get_type().get_fields().data
+    }
+
+    pub fn store_data(&self, ctx: &CodeGenContext<'ctx, '_>, value: PointerValue<'ctx>) {
+        self.data_field().set(ctx, self.as_base_value(), value, self.name);
+    }
+
+    pub fn load_data(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
+        self.data_field().get(ctx, self.value, self.name)
+    }
+}
+
+impl<'ctx> ProxyValue<'ctx> for ContiguousNDArrayValue<'ctx> {
+    type Base = PointerValue<'ctx>;
+    type Type = ContiguousNDArrayType<'ctx>;
+
+    fn get_type(&self) -> Self::Type {
+        <Self as ProxyValue<'ctx>>::Type::from_type(
+            self.as_base_value().get_type(),
+            self.item,
+            self.llvm_usize,
+        )
+    }
+
+    fn as_base_value(&self) -> Self::Base {
+        self.value
+    }
+}
+
+impl<'ctx> From<ContiguousNDArrayValue<'ctx>> for PointerValue<'ctx> {
+    fn from(value: ContiguousNDArrayValue<'ctx>) -> Self {
+        value.as_base_value()
+    }
+}
+
+impl<'ctx> NDArrayValue<'ctx> {
+    /// Create a [`ContiguousNDArrayValue`] from the contents of this ndarray.
+    ///
+    /// This function may or may not be expensive depending on if this ndarray has contiguous data.
+    ///
+    /// If this ndarray is not C-contiguous, this function will allocate memory on the stack for the
+    /// `data` field of the returned [`ContiguousNDArrayValue`] and copy contents of this ndarray to
+    /// there.
+    ///
+    /// If this ndarray is C-contiguous, contents of this ndarray will not be copied. The created
+    /// [`ContiguousNDArrayValue`] will share memory with this ndarray.
+    pub fn make_contiguous_ndarray<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+    ) -> ContiguousNDArrayValue<'ctx> {
+        let result = ContiguousNDArrayType::new(generator, ctx.ctx, self.dtype)
+            .alloca_var(generator, ctx, self.name);
+
+        // Set ndims and shape.
+        let ndims = self.llvm_usize.const_int(self.ndims, false);
+        result.store_ndims(ctx, ndims);
+
+        let shape = self.shape();
+        result.store_shape(ctx, shape.base_ptr(ctx, generator));
+
+        gen_if_callback(
+            generator,
+            ctx,
+            |generator, ctx| Ok(self.is_c_contiguous(generator, ctx)),
+            |_, ctx| {
+                // This ndarray is contiguous.
+                let data = self.data_field(ctx).get(ctx, self.as_base_value(), self.name);
+                let data = ctx
+                    .builder
+                    .build_pointer_cast(data, result.item.ptr_type(AddressSpace::default()), "")
+                    .unwrap();
+                result.store_data(ctx, data);
+
+                Ok(())
+            },
+            |generator, ctx| {
+                // This ndarray is not contiguous. Do a full-copy on `data`. `make_copy` produces an
+                // ndarray with contiguous `data`.
+                let copied_ndarray = self.make_copy(generator, ctx);
+                let data = copied_ndarray.data().base_ptr(ctx, generator);
+                let data = ctx
+                    .builder
+                    .build_pointer_cast(data, result.item.ptr_type(AddressSpace::default()), "")
+                    .unwrap();
+                result.store_data(ctx, data);
+
+                Ok(())
+            },
+        )
+        .unwrap();
+
+        result
+    }
+
+    /// Create an [`NDArrayValue`] from a [`ContiguousNDArrayValue`].
+    ///
+    /// The operation is cheap. The newly created [`NDArrayValue`] will share the same memory as the
+    /// [`ContiguousNDArrayValue`].
+    ///
+    /// `ndims` has to be provided as [`NDArrayValue`] requires a statically known `ndims` value,
+    /// despite the fact that the information should be contained within the
+    /// [`ContiguousNDArrayValue`].
+    pub fn from_contiguous_ndarray<G: CodeGenerator + ?Sized>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        carray: ContiguousNDArrayValue<'ctx>,
+        ndims: u64,
+    ) -> Self {
+        // TODO: Debug assert `ndims == carray.ndims` to catch bugs.
+
+        // Allocate the resulting ndarray.
+        let ndarray = NDArrayType::new(generator, ctx.ctx, carray.item, ndims)
+            .construct_uninitialized(generator, ctx, carray.name);
+
+        // Copy shape and update strides
+        let shape = carray.load_shape(ctx);
+        ndarray.copy_shape_from_array(generator, ctx, shape);
+        ndarray.set_strides_contiguous(generator, ctx);
+
+        // Share data
+        let data = carray.load_data(ctx);
+        ndarray.store_data(
+            ctx,
+            ctx.builder
+                .build_pointer_cast(data, ctx.ctx.i8_type().ptr_type(AddressSpace::default()), "")
+                .unwrap(),
+        );
+
+        ndarray
+    }
+}
--- a/nac3core/src/codegen/values/ndarray/indexing.rs
+++ b/nac3core/src/codegen/values/ndarray/indexing.rs
@ -0,0 +1,260 @@
+use inkwell::{
+    types::IntType,
+    values::{IntValue, PointerValue},
+    AddressSpace,
+};
+use itertools::Itertools;
+
+use nac3parser::ast::{Expr, ExprKind};
+
+use crate::{
+    codegen::{
+        irrt,
+        types::{
+            ndarray::{NDArrayType, NDIndexType},
+            structure::StructField,
+            utils::SliceType,
+        },
+        values::{ndarray::NDArrayValue, utils::RustSlice, ProxyValue},
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::Type,
+};
+
+/// An IRRT representation of an ndarray subscript index.
+#[derive(Copy, Clone)]
+pub struct NDIndexValue<'ctx> {
+    value: PointerValue<'ctx>,
+    llvm_usize: IntType<'ctx>,
+    name: Option<&'ctx str>,
+}
+
+impl<'ctx> NDIndexValue<'ctx> {
+    /// Checks whether `value` is an instance of `ndindex`, returning [Err] if `value` is not an
+    /// instance.
+    pub fn is_representable(
+        value: PointerValue<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        <Self as ProxyValue<'ctx>>::Type::is_representable(value.get_type(), llvm_usize)
+    }
+
+    /// Creates an [`NDIndexValue`] 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());
+
+        Self { value: ptr, llvm_usize, name }
+    }
+
+    fn type_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().type_
+    }
+
+    pub fn load_type(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.type_field().get(ctx, self.value, self.name)
+    }
+
+    pub fn store_type(&self, ctx: &CodeGenContext<'ctx, '_>, value: IntValue<'ctx>) {
+        self.type_field().set(ctx, self.value, value, self.name);
+    }
+
+    fn data_field(&self) -> StructField<'ctx, PointerValue<'ctx>> {
+        self.get_type().get_fields().data
+    }
+
+    pub fn load_data(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
+        self.data_field().get(ctx, self.value, self.name)
+    }
+
+    pub fn store_data(&self, ctx: &CodeGenContext<'ctx, '_>, value: PointerValue<'ctx>) {
+        self.data_field().set(ctx, self.value, value, self.name);
+    }
+}
+
+impl<'ctx> ProxyValue<'ctx> for NDIndexValue<'ctx> {
+    type Base = PointerValue<'ctx>;
+    type Type = NDIndexType<'ctx>;
+
+    fn get_type(&self) -> Self::Type {
+        Self::Type::from_type(self.value.get_type(), self.llvm_usize)
+    }
+
+    fn as_base_value(&self) -> Self::Base {
+        self.value
+    }
+}
+
+impl<'ctx> From<NDIndexValue<'ctx>> for PointerValue<'ctx> {
+    fn from(value: NDIndexValue<'ctx>) -> Self {
+        value.as_base_value()
+    }
+}
+
+impl<'ctx> NDArrayValue<'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 = NDArrayType::new(generator, ctx.ctx, self.dtype, dst_ndims)
+            .construct_uninitialized(generator, ctx, None);
+
+        let indices =
+            NDIndexType::new(generator, ctx.ctx).construct_ndindices(generator, ctx, indices);
+        irrt::ndarray::call_nac3_ndarray_index(generator, ctx, indices, *self, dst_ndarray);
+
+        dst_ndarray
+    }
+}
+
+/// A convenience enum representing a [`NDIndexValue`].
+// TODO: Rename to CTConstNDIndex
+#[derive(Debug, Clone)]
+pub enum RustNDIndex<'ctx> {
+    SingleElement(IntValue<'ctx>),
+    Slice(RustSlice<'ctx>),
+    NewAxis,
+    Ellipsis,
+}
+
+impl<'ctx> RustNDIndex<'ctx> {
+    /// 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 from_subscript_expr<G: CodeGenerator>(
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        subscript: &Expr<Option<Type>>,
+    ) -> Result<Vec<RustNDIndex<'ctx>>, String> {
+        // 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 = RustSlice::from_slice_expr(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 = index.into_int_value();
+
+                RustNDIndex::SingleElement(index)
+            };
+            rust_ndindices.push(ndindex);
+        }
+        Ok(rust_ndindices)
+    }
+
+    /// Get the value to set `NDIndex::type` for this variant.
+    #[must_use]
+    pub 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 [`NDIndexValue`].
+    pub fn write_to_ndindex<G: CodeGenerator + ?Sized>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        dst_ndindex: NDIndexValue<'ctx>,
+    ) {
+        let llvm_pi8 = ctx.ctx.i8_type().ptr_type(AddressSpace::default());
+
+        // Set `dst_ndindex.type`
+        dst_ndindex.store_type(ctx, ctx.ctx.i8_type().const_int(self.get_type_id(), false));
+
+        // Set `dst_ndindex_ptr->data`
+        match self {
+            RustNDIndex::SingleElement(in_index) => {
+                let index_ptr = ctx.builder.build_alloca(ctx.ctx.i32_type(), "").unwrap();
+                ctx.builder.build_store(index_ptr, *in_index).unwrap();
+
+                dst_ndindex.store_data(
+                    ctx,
+                    ctx.builder.build_pointer_cast(index_ptr, llvm_pi8, "").unwrap(),
+                );
+            }
+            RustNDIndex::Slice(in_rust_slice) => {
+                let user_slice_ptr =
+                    SliceType::new(ctx.ctx, ctx.ctx.i32_type(), generator.get_size_type(ctx.ctx))
+                        .alloca_var(generator, ctx, None);
+                in_rust_slice.write_to_slice(ctx, user_slice_ptr);
+
+                dst_ndindex.store_data(
+                    ctx,
+                    ctx.builder.build_pointer_cast(user_slice_ptr.into(), llvm_pi8, "").unwrap(),
+                );
+            }
+            RustNDIndex::NewAxis | RustNDIndex::Ellipsis => {}
+        }
+    }
+}
--- a/nac3core/src/codegen/values/ndarray/map.rs
+++ b/nac3core/src/codegen/values/ndarray/map.rs
@ -0,0 +1,69 @@
+use inkwell::{types::BasicTypeEnum, values::BasicValueEnum};
+
+use crate::codegen::{
+    values::{
+        ndarray::{NDArrayOut, NDArrayValue, ScalarOrNDArray},
+        ProxyValue,
+    },
+    CodeGenContext, CodeGenerator,
+};
+
+impl<'ctx> NDArrayValue<'ctx> {
+    /// Map through this ndarray with an elementwise function.
+    pub fn map<'a, G, Mapping>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        out: NDArrayOut<'ctx>,
+        mapping: Mapping,
+    ) -> Result<Self, String>
+    where
+        G: CodeGenerator + ?Sized,
+        Mapping: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            BasicValueEnum<'ctx>,
+        ) -> Result<BasicValueEnum<'ctx>, String>,
+    {
+        self.get_type().broadcast_starmap(
+            generator,
+            ctx,
+            &[*self],
+            out,
+            |generator, ctx, scalars| mapping(generator, ctx, scalars[0]),
+        )
+    }
+}
+
+impl<'ctx> ScalarOrNDArray<'ctx> {
+    /// Map through this [`ScalarOrNDArray`] with an elementwise function.
+    ///
+    /// If this is a scalar, `mapping` will directly act on the scalar. This function will return a
+    /// [`ScalarOrNDArray::Scalar`] of that result.
+    ///
+    /// If this is an ndarray, `mapping` will be applied to the elements of the ndarray. A new
+    /// ndarray of the results will be created and returned as a [`ScalarOrNDArray::NDArray`].
+    pub fn map<'a, G, Mapping>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, 'a>,
+        ret_dtype: BasicTypeEnum<'ctx>,
+        mapping: Mapping,
+    ) -> Result<ScalarOrNDArray<'ctx>, String>
+    where
+        G: CodeGenerator + ?Sized,
+        Mapping: FnOnce(
+            &mut G,
+            &mut CodeGenContext<'ctx, 'a>,
+            BasicValueEnum<'ctx>,
+        ) -> Result<BasicValueEnum<'ctx>, String>,
+    {
+        ScalarOrNDArray::broadcasting_starmap(
+            generator,
+            ctx,
+            &[*self],
+            ret_dtype,
+            |generator, ctx, scalars| mapping(generator, ctx, scalars[0]),
+        )
+    }
+}
--- a/nac3core/src/codegen/values/ndarray/matmul.rs
+++ b/nac3core/src/codegen/values/ndarray/matmul.rs
@ -0,0 +1,323 @@
+use std::cmp::max;
+
+use nac3parser::ast::Operator;
+
+use super::{NDArrayOut, NDArrayValue, RustNDIndex};
+use crate::{
+    codegen::{
+        expr::gen_binop_expr_with_values,
+        irrt,
+        stmt::gen_for_callback_incrementing,
+        types::ndarray::NDArrayType,
+        values::{
+            ArrayLikeValue, ArraySliceValue, TypedArrayLikeAccessor, TypedArrayLikeAdapter,
+            UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
+        },
+        CodeGenContext, CodeGenerator,
+    },
+    toplevel::helper::arraylike_flatten_element_type,
+    typecheck::{magic_methods::Binop, typedef::Type},
+};
+
+/// Perform `np.einsum("...ij,...jk->...ik", in_a, in_b)`.
+///
+/// `dst_dtype` defines the dtype of the returned ndarray.
+fn matmul_at_least_2d<'ctx, G: CodeGenerator>(
+    generator: &mut G,
+    ctx: &mut CodeGenContext<'ctx, '_>,
+    dst_dtype: Type,
+    (in_a_ty, in_a): (Type, NDArrayValue<'ctx>),
+    (in_b_ty, in_b): (Type, NDArrayValue<'ctx>),
+) -> NDArrayValue<'ctx> {
+    assert!(in_a.ndims >= 2, "in_a (which is {}) must be >= 2", in_a.ndims);
+    assert!(in_b.ndims >= 2, "in_b (which is {}) must be >= 2", in_b.ndims);
+
+    let lhs_dtype = arraylike_flatten_element_type(&mut ctx.unifier, in_a_ty);
+    let rhs_dtype = arraylike_flatten_element_type(&mut ctx.unifier, in_b_ty);
+
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let llvm_dst_dtype = ctx.get_llvm_type(generator, dst_dtype);
+
+    // Deduce ndims of the result of matmul.
+    let ndims_int = max(in_a.ndims, in_b.ndims);
+    let ndims = llvm_usize.const_int(ndims_int, false);
+
+    // Broadcasts `in_a.shape[:-2]` and `in_b.shape[:-2]` together and allocate the
+    // destination ndarray to store the result of matmul.
+    let (lhs, rhs, dst) = {
+        let in_lhs_ndims = llvm_usize.const_int(in_a.ndims, false);
+        let in_lhs_shape = TypedArrayLikeAdapter::from(
+            ArraySliceValue::from_ptr_val(
+                in_a.shape().base_ptr(ctx, generator),
+                in_lhs_ndims,
+                None,
+            ),
+            |_, _, val| val.into_int_value(),
+            |_, _, val| val.into(),
+        );
+        let in_rhs_ndims = llvm_usize.const_int(in_b.ndims, false);
+        let in_rhs_shape = TypedArrayLikeAdapter::from(
+            ArraySliceValue::from_ptr_val(
+                in_b.shape().base_ptr(ctx, generator),
+                in_rhs_ndims,
+                None,
+            ),
+            |_, _, val| val.into_int_value(),
+            |_, _, val| val.into(),
+        );
+        let lhs_shape = TypedArrayLikeAdapter::from(
+            ArraySliceValue::from_ptr_val(
+                ctx.builder.build_array_alloca(llvm_usize, ndims, "").unwrap(),
+                ndims,
+                None,
+            ),
+            |_, _, val| val.into_int_value(),
+            |_, _, val| val.into(),
+        );
+        let rhs_shape = TypedArrayLikeAdapter::from(
+            ArraySliceValue::from_ptr_val(
+                ctx.builder.build_array_alloca(llvm_usize, ndims, "").unwrap(),
+                ndims,
+                None,
+            ),
+            |_, _, val| val.into_int_value(),
+            |_, _, val| val.into(),
+        );
+        let dst_shape = TypedArrayLikeAdapter::from(
+            ArraySliceValue::from_ptr_val(
+                ctx.builder.build_array_alloca(llvm_usize, ndims, "").unwrap(),
+                ndims,
+                None,
+            ),
+            |_, _, val| val.into_int_value(),
+            |_, _, val| val.into(),
+        );
+
+        // Matmul dimension compatibility is checked here.
+        irrt::ndarray::call_nac3_ndarray_matmul_calculate_shapes(
+            generator,
+            ctx,
+            &in_lhs_shape,
+            &in_rhs_shape,
+            ndims,
+            &lhs_shape,
+            &rhs_shape,
+            &dst_shape,
+        );
+
+        let lhs = in_a.broadcast_to(generator, ctx, ndims_int, &lhs_shape);
+        let rhs = in_b.broadcast_to(generator, ctx, ndims_int, &rhs_shape);
+
+        let dst = NDArrayType::new(generator, ctx.ctx, llvm_dst_dtype, ndims_int)
+            .construct_uninitialized(generator, ctx, None);
+        dst.copy_shape_from_array(generator, ctx, dst_shape.base_ptr(ctx, generator));
+        unsafe {
+            dst.create_data(generator, ctx);
+        }
+
+        (lhs, rhs, dst)
+    };
+
+    let len = unsafe {
+        lhs.shape().get_typed_unchecked(
+            ctx,
+            generator,
+            &llvm_usize.const_int(ndims_int - 1, false),
+            None,
+        )
+    };
+
+    let at_row = i64::try_from(ndims_int - 2).unwrap();
+    let at_col = i64::try_from(ndims_int - 1).unwrap();
+
+    let dst_dtype_llvm = ctx.get_llvm_type(generator, dst_dtype);
+    let dst_zero = dst_dtype_llvm.const_zero();
+
+    dst.foreach(generator, ctx, |generator, ctx, _, hdl| {
+        let pdst_ij = hdl.get_pointer(ctx);
+
+        ctx.builder.build_store(pdst_ij, dst_zero).unwrap();
+
+        let indices = hdl.get_indices::<G>();
+        let i = unsafe {
+            indices.get_unchecked(ctx, generator, &llvm_usize.const_int(at_row as u64, true), None)
+        };
+        let j = unsafe {
+            indices.get_unchecked(ctx, generator, &llvm_usize.const_int(at_col as u64, true), None)
+        };
+
+        let num_0 = llvm_usize.const_int(0, false);
+        let num_1 = llvm_usize.const_int(1, false);
+
+        gen_for_callback_incrementing(
+            generator,
+            ctx,
+            None,
+            num_0,
+            (len, false),
+            |generator, ctx, _, k| {
+                // `indices` is modified to index into `a` and `b`, and restored.
+                unsafe {
+                    indices.set_unchecked(
+                        ctx,
+                        generator,
+                        &llvm_usize.const_int(at_row as u64, true),
+                        i,
+                    );
+                    indices.set_unchecked(
+                        ctx,
+                        generator,
+                        &llvm_usize.const_int(at_col as u64, true),
+                        k.into(),
+                    );
+                }
+                let a_ik = unsafe { lhs.data().get_unchecked(ctx, generator, &indices, None) };
+
+                unsafe {
+                    indices.set_unchecked(
+                        ctx,
+                        generator,
+                        &llvm_usize.const_int(at_row as u64, true),
+                        k.into(),
+                    );
+                    indices.set_unchecked(
+                        ctx,
+                        generator,
+                        &llvm_usize.const_int(at_col as u64, true),
+                        j,
+                    );
+                }
+                let b_kj = unsafe { rhs.data().get_unchecked(ctx, generator, &indices, None) };
+
+                // Restore `indices`.
+                unsafe {
+                    indices.set_unchecked(
+                        ctx,
+                        generator,
+                        &llvm_usize.const_int(at_row as u64, true),
+                        i,
+                    );
+                    indices.set_unchecked(
+                        ctx,
+                        generator,
+                        &llvm_usize.const_int(at_col as u64, true),
+                        j,
+                    );
+                }
+
+                // x = a_[...]ik * b_[...]kj
+                let x = gen_binop_expr_with_values(
+                    generator,
+                    ctx,
+                    (&Some(lhs_dtype), a_ik),
+                    Binop::normal(Operator::Mult),
+                    (&Some(rhs_dtype), b_kj),
+                    ctx.current_loc,
+                )?
+                .unwrap()
+                .to_basic_value_enum(ctx, generator, dst_dtype)?;
+
+                // dst_[...]ij += x
+                let dst_ij = ctx.builder.build_load(pdst_ij, "").unwrap();
+                let dst_ij = gen_binop_expr_with_values(
+                    generator,
+                    ctx,
+                    (&Some(dst_dtype), dst_ij),
+                    Binop::normal(Operator::Add),
+                    (&Some(dst_dtype), x),
+                    ctx.current_loc,
+                )?
+                .unwrap()
+                .to_basic_value_enum(ctx, generator, dst_dtype)?;
+                ctx.builder.build_store(pdst_ij, dst_ij).unwrap();
+
+                Ok(())
+            },
+            num_1,
+        )
+    })
+    .unwrap();
+
+    dst
+}
+
+impl<'ctx> NDArrayValue<'ctx> {
+    /// Perform [`np.matmul`](https://numpy.org/doc/stable/reference/generated/numpy.matmul.html).
+    ///
+    /// This function always return an [`NDArrayValue`]. You may want to use
+    /// [`NDArrayValue::split_unsized`] to handle when the output could be a scalar.
+    ///
+    /// `dst_dtype` defines the dtype of the returned ndarray.
+    #[must_use]
+    pub fn matmul<G: CodeGenerator>(
+        &self,
+        generator: &mut G,
+        ctx: &mut CodeGenContext<'ctx, '_>,
+        self_ty: Type,
+        (other_ty, other): (Type, Self),
+        (out_dtype, out): (Type, NDArrayOut<'ctx>),
+    ) -> Self {
+        // Sanity check, but type inference should prevent this.
+        assert!(self.ndims > 0 && other.ndims > 0, "np.matmul disallows scalar input");
+
+        // If both arguments are 2-D they are multiplied like conventional matrices.
+        //
+        // If either argument is N-D, N > 2, it is treated as a stack of matrices residing in the
+        // last two indices and broadcast accordingly.
+        //
+        // If the first argument is 1-D, it is promoted to a matrix by prepending a 1 to its
+        // dimensions. After matrix multiplication the prepended 1 is removed.
+        //
+        // If the second argument is 1-D, it is promoted to a matrix by appending a 1 to its
+        // dimensions. After matrix multiplication the appended 1 is removed.
+
+        let new_a = if self.ndims == 1 {
+            // Prepend 1 to its dimensions
+            self.index(generator, ctx, &[RustNDIndex::NewAxis, RustNDIndex::Ellipsis])
+        } else {
+            *self
+        };
+
+        let new_b = if other.ndims == 1 {
+            // Append 1 to its dimensions
+            other.index(generator, ctx, &[RustNDIndex::Ellipsis, RustNDIndex::NewAxis])
+        } else {
+            other
+        };
+
+        // NOTE: `result` will always be a newly allocated ndarray.
+        // Current implementation cannot do in-place matrix muliplication.
+        let mut result =
+            matmul_at_least_2d(generator, ctx, out_dtype, (self_ty, new_a), (other_ty, new_b));
+
+        // Postprocessing on the result to remove prepended/appended axes.
+        let mut postindices = vec![];
+        let zero = ctx.ctx.i32_type().const_zero();
+
+        if self.ndims == 1 {
+            // Remove the prepended 1
+            postindices.push(RustNDIndex::SingleElement(zero));
+        }
+
+        if other.ndims == 1 {
+            // Remove the appended 1
+            postindices.push(RustNDIndex::Ellipsis);
+            postindices.push(RustNDIndex::SingleElement(zero));
+        }
+
+        if !postindices.is_empty() {
+            result = result.index(generator, ctx, &postindices);
+        }
+
+        match out {
+            NDArrayOut::NewNDArray { .. } => result,
+            NDArrayOut::WriteToNDArray { ndarray: out_ndarray } => {
+                let result_shape = result.shape();
+                out_ndarray.assert_can_be_written_by_out(generator, ctx, result_shape);
+
+                out_ndarray.copy_data_from(generator, ctx, result);
+                out_ndarray
+            }
+        }
+    }
+}
--- a/nac3core/src/codegen/values/ndarray/mod.rs
+++ b/nac3core/src/codegen/values/ndarray/mod.rs
--- a/nac3core/src/codegen/values/ndarray/nditer.rs
+++ b/nac3core/src/codegen/values/ndarray/nditer.rs
@ -0,0 +1,178 @@
+use inkwell::{
+    types::{BasicType, IntType},
+    values::{BasicValueEnum, IntValue, PointerValue},
+    AddressSpace,
+};
+
+use super::{NDArrayValue, ProxyValue};
+use crate::codegen::{
+    irrt,
+    stmt::{gen_for_callback, BreakContinueHooks},
+    types::{ndarray::NDIterType, structure::StructField},
+    values::{ArraySliceValue, TypedArrayLikeAdapter},
+    CodeGenContext, CodeGenerator,
+};
+
+#[derive(Copy, Clone)]
+pub struct NDIterValue<'ctx> {
+    value: PointerValue<'ctx>,
+    parent: NDArrayValue<'ctx>,
+    indices: ArraySliceValue<'ctx>,
+    llvm_usize: IntType<'ctx>,
+    name: Option<&'ctx str>,
+}
+
+impl<'ctx> NDIterValue<'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> {
+        <Self as ProxyValue>::Type::is_representable(value.get_type(), llvm_usize)
+    }
+
+    /// Creates an [`NDArrayValue`] from a [`PointerValue`].
+    #[must_use]
+    pub fn from_pointer_value(
+        ptr: PointerValue<'ctx>,
+        parent: NDArrayValue<'ctx>,
+        indices: ArraySliceValue<'ctx>,
+        llvm_usize: IntType<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> Self {
+        debug_assert!(Self::is_representable(ptr, llvm_usize).is_ok());
+
+        Self { value: ptr, parent, indices, llvm_usize, name }
+    }
+
+    /// 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: &G,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> IntValue<'ctx> {
+        irrt::ndarray::call_nac3_nditer_has_element(generator, ctx, *self)
+    }
+
+    /// 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: &G, ctx: &CodeGenContext<'ctx, '_>) {
+        irrt::ndarray::call_nac3_nditer_next(generator, ctx, *self);
+    }
+
+    fn element_field(
+        &self,
+        ctx: &CodeGenContext<'ctx, '_>,
+    ) -> StructField<'ctx, PointerValue<'ctx>> {
+        self.get_type().get_fields(ctx.ctx).element
+    }
+
+    /// Get pointer to the current element.
+    #[must_use]
+    pub fn get_pointer(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
+        let elem_ty = self.parent.dtype;
+
+        let p = self.element_field(ctx).get(ctx, self.as_base_value(), self.name);
+        ctx.builder
+            .build_pointer_cast(p, elem_ty.ptr_type(AddressSpace::default()), "element")
+            .unwrap()
+    }
+
+    /// Get the value of the current element.
+    #[must_use]
+    pub fn get_scalar(&self, ctx: &CodeGenContext<'ctx, '_>) -> BasicValueEnum<'ctx> {
+        let p = self.get_pointer(ctx);
+        ctx.builder.build_load(p, "value").unwrap()
+    }
+
+    fn nth_field(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields(ctx.ctx).nth
+    }
+
+    /// Get the index of the current element if this ndarray were a flat ndarray.
+    #[must_use]
+    pub fn get_index(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.nth_field(ctx).get(ctx, self.as_base_value(), self.name)
+    }
+
+    /// Get the indices of the current element.
+    #[must_use]
+    pub fn get_indices<G: CodeGenerator + ?Sized>(
+        &self,
+    ) -> TypedArrayLikeAdapter<'ctx, G, IntValue<'ctx>> {
+        TypedArrayLikeAdapter::from(
+            self.indices,
+            |_, _, val| val.into_int_value(),
+            |_, _, val| val.into(),
+        )
+    }
+}
+
+impl<'ctx> ProxyValue<'ctx> for NDIterValue<'ctx> {
+    type Base = PointerValue<'ctx>;
+    type Type = NDIterType<'ctx>;
+
+    fn get_type(&self) -> Self::Type {
+        NDIterType::from_type(self.as_base_value().get_type(), self.llvm_usize)
+    }
+
+    fn as_base_value(&self) -> Self::Base {
+        self.value
+    }
+}
+
+impl<'ctx> From<NDIterValue<'ctx>> for PointerValue<'ctx> {
+    fn from(value: NDIterValue<'ctx>) -> Self {
+        value.as_base_value()
+    }
+}
+
+impl<'ctx> NDArrayValue<'ctx> {
+    /// Iterate through every element in the ndarray.
+    ///
+    /// `body` has access to [`BreakContinueHooks`] to short-circuit and [`NDIterValue`] to
+    /// get properties of the current iteration (e.g., the current element, indices, etc.)
+    ///
+    /// Note: The caller is recommended to call `llvm.stacksave` and `llvm.stackrestore` before and
+    /// after invoking this function respectively. See [`NDIterType::construct`] for an explanation
+    /// on why this is suggested.
+    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>,
+            NDIterValue<'ctx>,
+        ) -> Result<(), String>,
+    {
+        gen_for_callback(
+            generator,
+            ctx,
+            Some("ndarray_foreach"),
+            |generator, ctx| {
+                Ok(NDIterType::new(generator, ctx.ctx).construct(generator, ctx, *self))
+            },
+            |generator, ctx, nditer| Ok(nditer.has_element(generator, ctx)),
+            |generator, ctx, hooks, nditer| body(generator, ctx, hooks, nditer),
+            |generator, ctx, nditer| {
+                nditer.next(generator, ctx);
+                Ok(())
+            },
+        )
+    }
+}
--- a/nac3core/src/codegen/values/ndarray/shape.rs
+++ b/nac3core/src/codegen/values/ndarray/shape.rs
@ -0,0 +1,152 @@
+use inkwell::values::{BasicValueEnum, IntValue};
+
+use crate::{
+    codegen::{
+        stmt::gen_for_callback_incrementing,
+        types::{ListType, TupleType},
+        values::{
+            ArraySliceValue, ProxyValue, TypedArrayLikeAccessor, TypedArrayLikeAdapter,
+            TypedArrayLikeMutator, UntypedArrayLikeAccessor,
+        },
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::{Type, 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_seq_ty, input_seq): (Type, BasicValueEnum<'ctx>),
+) -> impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>> {
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+    let zero = llvm_usize.const_zero();
+    let one = llvm_usize.const_int(1, false);
+
+    // The result `list` to return.
+    match &*ctx.unifier.get_ty_immutable(input_seq_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])`
+
+            let input_seq = ListType::from_unifier_type(generator, ctx, input_seq_ty)
+                .map_value(input_seq.into_pointer_value(), None);
+
+            let len = input_seq.load_size(ctx, None);
+            // TODO: Find a way to remove this mid-BB allocation
+            let result = ctx.builder.build_array_alloca(llvm_usize, len, "").unwrap();
+            let result = TypedArrayLikeAdapter::from(
+                ArraySliceValue::from_ptr_val(result, len, None),
+                |_, _, val| val.into_int_value(),
+                |_, _, val| val.into(),
+            );
+
+            // Load all the `int32`s from the input_sequence, cast them to `SizeT`, and store them into `result`
+            gen_for_callback_incrementing(
+                generator,
+                ctx,
+                None,
+                zero,
+                (len, false),
+                |generator, ctx, _, i| {
+                    // Load the i-th int32 in the input sequence
+                    let int = unsafe {
+                        input_seq.data().get_unchecked(ctx, generator, &i, None).into_int_value()
+                    };
+
+                    // Cast to SizeT
+                    let int =
+                        ctx.builder.build_int_s_extend_or_bit_cast(int, llvm_usize, "").unwrap();
+
+                    // Store
+                    unsafe { result.set_typed_unchecked(ctx, generator, &i, int) };
+
+                    Ok(())
+                },
+                one,
+            )
+            .unwrap();
+
+            result
+        }
+
+        TypeEnum::TTuple { .. } => {
+            // 2. A tuple of ints; e.g., `np.empty((600, 800, 3))`
+
+            let input_seq = TupleType::from_unifier_type(generator, ctx, input_seq_ty)
+                .map_value(input_seq.into_struct_value(), None);
+
+            let len = input_seq.get_type().num_elements();
+
+            let result = generator
+                .gen_array_var_alloc(
+                    ctx,
+                    llvm_usize.into(),
+                    llvm_usize.const_int(u64::from(len), false),
+                    None,
+                )
+                .unwrap();
+            let result = TypedArrayLikeAdapter::from(
+                result,
+                |_, _, val| val.into_int_value(),
+                |_, _, val| val.into(),
+            );
+
+            for i in 0..input_seq.get_type().num_elements() {
+                // Get the i-th element off of the tuple and load it into `result`.
+                let int = input_seq.load_element(ctx, i).into_int_value();
+                let int = ctx.builder.build_int_s_extend_or_bit_cast(int, llvm_usize, "").unwrap();
+
+                unsafe {
+                    result.set_typed_unchecked(
+                        ctx,
+                        generator,
+                        &llvm_usize.const_int(u64::from(i), false),
+                        int,
+                    );
+                }
+            }
+
+            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_seq.into_int_value();
+
+            let len = one;
+            let result = generator.gen_array_var_alloc(ctx, llvm_usize.into(), len, None).unwrap();
+            let result = TypedArrayLikeAdapter::from(
+                result,
+                |_, _, val| val.into_int_value(),
+                |_, _, val| val.into(),
+            );
+            let int =
+                ctx.builder.build_int_s_extend_or_bit_cast(input_int, llvm_usize, "").unwrap();
+
+            // Storing into result[0]
+            unsafe {
+                result.set_typed_unchecked(ctx, generator, &zero, int);
+            }
+
+            result
+        }
+
+        _ => panic!("encountered unknown sequence type: {}", ctx.unifier.stringify(input_seq_ty)),
+    }
+}
--- a/nac3core/src/codegen/values/ndarray/view.rs
+++ b/nac3core/src/codegen/values/ndarray/view.rs
@ -0,0 +1,154 @@
+use std::iter::{once, repeat_n};
+
+use inkwell::values::{IntValue, PointerValue};
+use itertools::Itertools;
+
+use crate::codegen::{
+    irrt,
+    stmt::gen_if_callback,
+    types::ndarray::NDArrayType,
+    values::{
+        ndarray::{NDArrayValue, RustNDIndex},
+        ArrayLikeValue, ArraySliceValue, ProxyValue, TypedArrayLikeAccessor, TypedArrayLikeAdapter,
+    },
+    CodeGenContext, CodeGenerator,
+};
+
+impl<'ctx> NDArrayValue<'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. Otherwise, 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 {
+        let ndims = self.ndims;
+
+        if ndims < ndmin {
+            // Extend the dimensions with np.newaxis.
+            let indices = repeat_n(RustNDIndex::NewAxis, (ndmin - ndims) as usize)
+                .chain(once(RustNDIndex::Ellipsis))
+                .collect_vec();
+            self.index(generator, ctx, &indices)
+        } else {
+            *self
+        }
+    }
+
+    /// Create a reshaped view on this ndarray like
+    /// [`np.reshape()`](https://numpy.org/doc/stable/reference/generated/numpy.reshape.html).
+    ///
+    /// 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: &impl TypedArrayLikeAccessor<'ctx, G, IntValue<'ctx>>,
+    ) -> Self {
+        assert_eq!(new_shape.element_type(ctx, generator), self.llvm_usize.into());
+
+        // 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 dst_ndarray = NDArrayType::new(generator, ctx.ctx, self.dtype, new_ndims)
+            .construct_uninitialized(generator, ctx, None);
+        dst_ndarray.copy_shape_from_array(generator, ctx, new_shape.base_ptr(ctx, generator));
+
+        // Resolve negative indices
+        let size = self.size(generator, ctx);
+        let dst_ndims = self.llvm_usize.const_int(dst_ndarray.get_type().ndims(), false);
+        let dst_shape = dst_ndarray.shape();
+        irrt::ndarray::call_nac3_ndarray_reshape_resolve_and_check_new_shape(
+            generator,
+            ctx,
+            size,
+            dst_ndims,
+            dst_shape.as_slice_value(ctx, generator),
+        );
+
+        gen_if_callback(
+            generator,
+            ctx,
+            |generator, ctx| Ok(self.is_c_contiguous(generator, ctx)),
+            |generator, ctx| {
+                // Reshape is possible without copying
+                dst_ndarray.set_strides_contiguous(generator, ctx);
+                dst_ndarray.store_data(ctx, self.data().base_ptr(ctx, generator));
+
+                Ok(())
+            },
+            |generator, ctx| {
+                // Reshape is impossible without copying
+                unsafe {
+                    dst_ndarray.create_data(generator, ctx);
+                }
+                dst_ndarray.copy_data_from(generator, ctx, *self);
+
+                Ok(())
+            },
+        )
+        .unwrap();
+
+        dst_ndarray
+    }
+
+    /// Create a transposed view on this ndarray like
+    /// [`np.transpose(<ndarray>, <axes> = None)`](https://numpy.org/doc/stable/reference/generated/numpy.transpose.html).
+    ///
+    /// * `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<PointerValue<'ctx>>,
+    ) -> Self {
+        assert!(
+            axes.is_none_or(|axes| axes.get_type().get_element_type() == self.llvm_usize.into())
+        );
+
+        // Define models
+        let transposed_ndarray = self.get_type().construct_uninitialized(generator, ctx, None);
+
+        let axes = if let Some(axes) = axes {
+            let num_axes = self.llvm_usize.const_int(self.ndims, false);
+
+            // `axes = nullptr` if `axes` is unspecified.
+            let axes = ArraySliceValue::from_ptr_val(axes, num_axes, None);
+
+            Some(TypedArrayLikeAdapter::from(
+                axes,
+                |_, _, val| val.into_int_value(),
+                |_, _, val| val.into(),
+            ))
+        } else {
+            None
+        };
+
+        irrt::ndarray::call_nac3_ndarray_transpose(
+            generator,
+            ctx,
+            *self,
+            transposed_ndarray,
+            axes.as_ref(),
+        );
+
+        transposed_ndarray
+    }
+}
--- 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/codegen/values/tuple.rs
+++ b/nac3core/src/codegen/values/tuple.rs
@ -0,0 +1,85 @@
+use inkwell::{
+    types::IntType,
+    values::{BasicValue, BasicValueEnum, StructValue},
+};
+
+use super::ProxyValue;
+use crate::codegen::{types::TupleType, CodeGenContext};
+
+#[derive(Copy, Clone)]
+pub struct TupleValue<'ctx> {
+    value: StructValue<'ctx>,
+    llvm_usize: IntType<'ctx>,
+    name: Option<&'ctx str>,
+}
+
+impl<'ctx> TupleValue<'ctx> {
+    /// Checks whether `value` is an instance of `tuple`, returning [Err] if `value` is not an
+    /// instance.
+    pub fn is_representable(
+        value: StructValue<'ctx>,
+        _llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        TupleType::is_representable(value.get_type())
+    }
+
+    /// Creates an [`TupleValue`] from a [`StructValue`].
+    #[must_use]
+    pub fn from_struct_value(
+        value: StructValue<'ctx>,
+        llvm_usize: IntType<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> Self {
+        debug_assert!(Self::is_representable(value, llvm_usize).is_ok());
+
+        Self { value, llvm_usize, name }
+    }
+
+    /// Stores a value into the tuple element at the given `index`.
+    pub fn store_element(
+        &mut self,
+        ctx: &CodeGenContext<'ctx, '_>,
+        index: u32,
+        element: impl BasicValue<'ctx>,
+    ) {
+        assert_eq!(element.as_basic_value_enum().get_type(), unsafe {
+            self.get_type().type_at_index_unchecked(index)
+        });
+
+        let new_value = ctx
+            .builder
+            .build_insert_value(self.value, element, index, self.name.unwrap_or_default())
+            .unwrap();
+        self.value = new_value.into_struct_value();
+    }
+
+    /// Loads a value from the tuple element at the given `index`.
+    pub fn load_element(&self, ctx: &CodeGenContext<'ctx, '_>, index: u32) -> BasicValueEnum<'ctx> {
+        ctx.builder
+            .build_extract_value(
+                self.value,
+                index,
+                &format!("{}[{{i}}]", self.name.unwrap_or("tuple")),
+            )
+            .unwrap()
+    }
+}
+
+impl<'ctx> ProxyValue<'ctx> for TupleValue<'ctx> {
+    type Base = StructValue<'ctx>;
+    type Type = TupleType<'ctx>;
+
+    fn get_type(&self) -> Self::Type {
+        TupleType::from_type(self.as_base_value().get_type(), self.llvm_usize)
+    }
+
+    fn as_base_value(&self) -> Self::Base {
+        self.value
+    }
+}
+
+impl<'ctx> From<TupleValue<'ctx>> for StructValue<'ctx> {
+    fn from(value: TupleValue<'ctx>) -> Self {
+        value.as_base_value()
+    }
+}
--- a/nac3core/src/codegen/values/utils/mod.rs
+++ b/nac3core/src/codegen/values/utils/mod.rs
@ -0,0 +1,3 @@
+pub use slice::*;
+
+mod slice;
--- a/nac3core/src/codegen/values/utils/slice.rs
+++ b/nac3core/src/codegen/values/utils/slice.rs
@ -0,0 +1,231 @@
+use inkwell::{
+    types::IntType,
+    values::{IntValue, PointerValue},
+};
+
+use nac3parser::ast::Expr;
+
+use crate::{
+    codegen::{
+        types::{structure::StructField, utils::SliceType},
+        values::ProxyValue,
+        CodeGenContext, CodeGenerator,
+    },
+    typecheck::typedef::Type,
+};
+
+/// An IRRT representation of an (unresolved) slice.
+#[derive(Copy, Clone)]
+pub struct SliceValue<'ctx> {
+    value: PointerValue<'ctx>,
+    int_ty: IntType<'ctx>,
+    llvm_usize: IntType<'ctx>,
+    name: Option<&'ctx str>,
+}
+
+impl<'ctx> SliceValue<'ctx> {
+    /// Checks whether `value` is an instance of `ContiguousNDArray`, returning [Err] if `value` is
+    /// not an instance.
+    pub fn is_representable(
+        value: PointerValue<'ctx>,
+        llvm_usize: IntType<'ctx>,
+    ) -> Result<(), String> {
+        <Self as ProxyValue<'ctx>>::Type::is_representable(value.get_type(), llvm_usize)
+    }
+
+    /// Creates an [`SliceValue`] from a [`PointerValue`].
+    #[must_use]
+    pub fn from_pointer_value(
+        ptr: PointerValue<'ctx>,
+        int_ty: IntType<'ctx>,
+        llvm_usize: IntType<'ctx>,
+        name: Option<&'ctx str>,
+    ) -> Self {
+        debug_assert!(Self::is_representable(ptr, llvm_usize).is_ok());
+
+        Self { value: ptr, int_ty, llvm_usize, name }
+    }
+
+    fn start_defined_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().start_defined
+    }
+
+    pub fn load_start_defined(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.start_defined_field().get(ctx, self.value, self.name)
+    }
+
+    fn start_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().start
+    }
+
+    pub fn load_start(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.start_field().get(ctx, self.value, self.name)
+    }
+
+    pub fn store_start(&self, ctx: &CodeGenContext<'ctx, '_>, value: Option<IntValue<'ctx>>) {
+        match value {
+            Some(start) => {
+                self.start_defined_field().set(
+                    ctx,
+                    self.value,
+                    ctx.ctx.bool_type().const_all_ones(),
+                    self.name,
+                );
+                self.start_field().set(ctx, self.value, start, self.name);
+            }
+
+            None => self.start_defined_field().set(
+                ctx,
+                self.value,
+                ctx.ctx.bool_type().const_zero(),
+                self.name,
+            ),
+        }
+    }
+
+    fn stop_defined_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().stop_defined
+    }
+
+    pub fn load_stop_defined(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.stop_defined_field().get(ctx, self.value, self.name)
+    }
+
+    fn stop_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().stop
+    }
+
+    pub fn load_stop(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.stop_field().get(ctx, self.value, self.name)
+    }
+
+    pub fn store_stop(&self, ctx: &CodeGenContext<'ctx, '_>, value: Option<IntValue<'ctx>>) {
+        match value {
+            Some(stop) => {
+                self.stop_defined_field().set(
+                    ctx,
+                    self.value,
+                    ctx.ctx.bool_type().const_all_ones(),
+                    self.name,
+                );
+                self.stop_field().set(ctx, self.value, stop, self.name);
+            }
+
+            None => self.stop_defined_field().set(
+                ctx,
+                self.value,
+                ctx.ctx.bool_type().const_zero(),
+                self.name,
+            ),
+        }
+    }
+
+    fn step_defined_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().step_defined
+    }
+
+    pub fn load_step_defined(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.step_defined_field().get(ctx, self.value, self.name)
+    }
+
+    fn step_field(&self) -> StructField<'ctx, IntValue<'ctx>> {
+        self.get_type().get_fields().step
+    }
+
+    pub fn load_step(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
+        self.step_field().get(ctx, self.value, self.name)
+    }
+
+    pub fn store_step(&self, ctx: &CodeGenContext<'ctx, '_>, value: Option<IntValue<'ctx>>) {
+        match value {
+            Some(step) => {
+                self.step_defined_field().set(
+                    ctx,
+                    self.value,
+                    ctx.ctx.bool_type().const_all_ones(),
+                    self.name,
+                );
+                self.step_field().set(ctx, self.value, step, self.name);
+            }
+
+            None => self.step_defined_field().set(
+                ctx,
+                self.value,
+                ctx.ctx.bool_type().const_zero(),
+                self.name,
+            ),
+        }
+    }
+}
+
+impl<'ctx> ProxyValue<'ctx> for SliceValue<'ctx> {
+    type Base = PointerValue<'ctx>;
+    type Type = SliceType<'ctx>;
+
+    fn get_type(&self) -> Self::Type {
+        Self::Type::from_type(self.value.get_type(), self.int_ty, self.llvm_usize)
+    }
+
+    fn as_base_value(&self) -> Self::Base {
+        self.value
+    }
+}
+
+impl<'ctx> From<SliceValue<'ctx>> for PointerValue<'ctx> {
+    fn from(value: SliceValue<'ctx>) -> Self {
+        value.as_base_value()
+    }
+}
+
+/// A slice represented in compile-time by `start`, `stop` and `step`, all held as LLVM values.
+// TODO: Rename this to CTConstSlice
+#[derive(Debug, Copy, Clone)]
+pub struct RustSlice<'ctx> {
+    int_ty: IntType<'ctx>,
+    start: Option<IntValue<'ctx>>,
+    stop: Option<IntValue<'ctx>>,
+    step: Option<IntValue<'ctx>>,
+}
+
+impl<'ctx> RustSlice<'ctx> {
+    /// Generate LLVM IR for an [`ExprKind::Slice`] and convert it into a [`RustSlice`].
+    #[allow(clippy::type_complexity)]
+    pub fn from_slice_expr<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>, String> {
+        let mut value_mapper = |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)?
+                        .map(|value| {
+                            value.to_basic_value_enum(ctx, generator, ctx.primitives.int32)
+                        })
+                        .unwrap()?;
+
+                    Some(value_expr.into_int_value())
+                }
+            })
+        };
+
+        let start = value_mapper(lower)?;
+        let stop = value_mapper(upper)?;
+        let step = value_mapper(step)?;
+
+        Ok(RustSlice { int_ty: ctx.ctx.i32_type(), start, stop, step })
+    }
+
+    /// Write the contents to an LLVM [`SliceValue`].
+    pub fn write_to_slice(&self, ctx: &CodeGenContext<'ctx, '_>, dst_slice_ptr: SliceValue<'ctx>) {
+        assert_eq!(self.int_ty, dst_slice_ptr.int_ty);
+
+        dst_slice_ptr.store_start(ctx, self.start);
+        dst_slice_ptr.store_stop(ctx, self.stop);
+        dst_slice_ptr.store_step(ctx, self.step);
+    }
+}
--- a/nac3core/src/lib.rs
+++ b/nac3core/src/lib.rs
@ -1,10 +1,4 @@
-#![deny(
-    future_incompatible,
-    let_underscore,
-    nonstandard_style,
-    rust_2024_compatibility,
-    clippy::all
-)]
+#![deny(future_incompatible, let_underscore, nonstandard_style, clippy::all)]
 #![warn(clippy::pedantic)]
 #![allow(
    dead_code,
@ -27,3 +21,5 @@ 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
@ -6,7 +6,7 @@ use std::{
 };

 use inkwell::values::{BasicValueEnum, FloatValue, IntValue, PointerValue, StructValue};
-use itertools::{chain, izip, Itertools};
+use itertools::{izip, Itertools};
 use parking_lot::RwLock;

 use nac3parser::ast::{Constant, Expr, Location, StrRef};
@ -452,10 +452,10 @@ pub fn parse_type_annotation<T>(
                            type_vars.len()
                        )]));
                    }
-                    let fields = chain(
-                        fields.iter().map(|(k, v, m)| (*k, (*v, *m))),
-                        methods.iter().map(|(k, v, _)| (*k, (*v, false))),
-                    )
+                    let fields = fields
+                        .iter()
+                        .map(|(k, v, m)| (*k, (*v, *m)))
+                        .chain(methods.iter().map(|(k, v, _)| (*k, (*v, false))))
                        .collect();
                    Ok(unifier.add_ty(TypeEnum::TObj { obj_id, fields, params: VarMap::default() }))
                } else {
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Sebastien Bourdeauducq	8322d457c6	standalone/demo: numpy2 compatibility	2025-01-04 15:30:24 +08:00
Sebastien Bourdeauducq	e480081e4b	update dependencies	2025-01-04 10:28:41 +08:00
David Mak	12fddc3533	[core] codegen/ndarray: Make ndims non-optional Now that everything is ported to use strided impl, dynamic-ndim ndarray instances do not exist anymore.	2025-01-03 15:43:08 +08:00
David Mak	3ac1083734	[core] codegen: Reimplement np_dot() for scalars and 1D Based on `693b7f37`: core/ndstrides: implement np_dot() for scalars and 1D	2025-01-03 15:43:08 +08:00
David Mak	66b8a5e01d	[core] codegen/ndarray: Reimplement matmul Based on `73c2203b`: core/ndstrides: implement general matmul	2025-01-03 15:43:06 +08:00
David Mak	ebbadc2d74	[core] codegen: Reimplement ndarray cmpop Based on `56cccce1`: core/ndstrides: implement cmpop	2025-01-03 15:15:13 +08:00
David Mak	a2f1b25fd8	[core] codegen: Reimplement ndarray unary op Based on `bb992704`: core/ndstrides: implement unary op	2025-01-03 15:15:12 +08:00
David Mak	59f19e29df	[core] codegen: Reimplement ndarray binop Based on `9e40c834`: core/ndstrides: implement binop	2025-01-03 15:15:12 +08:00
David Mak	6cbba8fdde	[core] codegen: Reimplement builtin funcs to support strided ndarrays Based on `7f3c4530`: core/ndstrides: update builtin_fns to use ndarray with strides	2025-01-03 15:15:12 +08:00
David Mak	e6dab25a57	[core] codegen/ndarray: Add NDArrayOut, broadcast_map, map Based on `fbfc0b29`: core/ndstrides: add NDArrayOut, broadcast_map and map	2025-01-03 15:15:11 +08:00
David Mak	2dc5e79a23	[core] codegen/ndarray: Implement subscript assignment Based on `5bed394e`: core/ndstrides: implement subscript assignment Overlapping is not handled. Currently it has undefined behavior.	2025-01-03 15:15:11 +08:00
David Mak	dcde1d9c87	[core] codegen/values/ndarray: Add more ScalarOrNDArray utils Based on `f731e604`: core/ndstrides: add more ScalarOrNDArray and NDArrayObject utils	2025-01-03 15:15:10 +08:00
David Mak	7375983e0c	[core] codegen/ndarray: Implement np_transpose without axes argument Based on `052b67c8`: core/ndstrides: implement np_transpose() (no axes argument) The IRRT implementation knows how to handle axes. But the argument is not in NAC3 yet.	2025-01-03 15:15:08 +08:00
David Mak	43e440d2fd	[core] codegen/ndarray: Reimplement broadcasting Based on `9359ed96`: core/ndstrides: implement broadcasting & np_broadcast_to()	2025-01-03 15:14:59 +08:00
David Mak	8d975b5ff3	[core] codegen/ndarray: Implement np_reshape Based on `926e7e93`: core/ndstrides: implement np_reshape()	2025-01-03 14:56:16 +08:00
David Mak	aae41eef6a	[core] toplevel: Add view functions category Based on `9e0f636d`: core: categorize np_{transpose,reshape} as 'view functions'	2025-01-03 14:47:59 +08:00
David Mak	132ba1942f	[core] toplevel: Implement np_size Based on `2c1030d1`: core/ndstrides: implement np_size()	2025-01-03 14:16:29 +08:00
David Mak	12358c57b1	[core] codegen/ndarray: Implement np_{shape,strides} Based on `40c24486`: core/ndstrides: implement np_shape() and np_strides() These functions are not important, but they are handy for debugging. `np.strides()` is not an actual NumPy function, but `ndarray.strides` is used.	2025-01-03 13:58:47 +08:00
David Mak	9ffa2d6552	[core] codegen/ndarray: Reimplement np_{copy,fill} Based on `18db85fa`: core/ndstrides: implement ndarray.fill() and .copy()	2025-01-03 13:58:47 +08:00
David Mak	acb437919d	[core] codegen/ndarray: Reimplement np_{eye,identity} Based on `fa047d50`: core/ndstrides: implement np_identity() and np_eye()	2025-01-03 13:58:47 +08:00
David Mak	fadadd7505	[core] codegen/ndarray: Reimplement np_array() Based on `8f0084ac`: core/ndstrides: implement np_array() It also checks for inconsistent dimensions if the input is a list. e.g., rejecting `[[1.0, 2.0], [3.0]]`. However, currently only `np_array(<input>, copy=False)` and `np_array (<input>, copy=True)` are supported. In NumPy, copy could be false, true, or None. Right now, NAC3's `np_array(<input>, copy=False)` behaves like NumPy's `np.array(<input>, copy=None)`.	2025-01-03 13:58:47 +08:00
David Mak	26f1428739	[core] codegen: Refactor len() Based on `54a842a9`: core/ndstrides: implement len(ndarray) & refactor len()	2025-01-03 13:58:47 +08:00
David Mak	5880f964bb	[core] codegen/ndarray: Reimplement np_{zeros,ones,full,empty} Based on `792374fa`: core/ndstrides: implement np_{zeros,ones,full,empty}.	2025-01-03 13:58:47 +08:00
David Mak	7d02f5833d	[core] codegen: Implement Tuple{Type,Value}	2025-01-03 13:58:47 +08:00
David Mak	822f9d33f8	[core] codegen: Refactor ListType to use derive(StructFields)	2025-01-03 13:58:47 +08:00
David Mak	805a9d23b3	[core] codegen: Add derive(Copy, Clone) to TypedArrayLikeAdapter	2025-01-03 13:58:46 +08:00
David Mak	1ffe2fcc7f	[core] irrt: Minor reformat	2025-01-03 13:26:51 +08:00
David Mak	2f0847d77b	[core] codegen/types: Refactor ProxyType - Add alloca_type() function to obtain the type that should be passed into a `build_alloca` call - Provide default implementations for raw_alloca and array_alloca - Add raw_alloca_var and array_alloca_var to distinguish alloca instructions placed at the front of the function vs at the current builder location	2024-12-30 17:00:17 +08:00
David Mak	dc9efa9e8c	[core] codegen/ndarray: Use IRRT for size() and indexing operations Also refactor some usages of call_ndarray_calc_size with ndarray.size().	2024-12-30 16:58:33 +08:00
David Mak	3c0ce3031f	[core] codegen: Update raw_alloca to return PointerValue Better match the expected behavior of alloca.	2024-12-30 16:51:34 +08:00
David Mak	d5e8df070a	[core] Minor improvements to IRRT and add missing documentation	2024-12-30 16:51:17 +08:00
David Mak	dc413dfa43	[core] codegen: Refactor TypedArrayLikeAdapter to use fn Allows for greater flexibility when TypedArrayLikeAdapter is used with custom value types.	2024-12-30 16:50:22 +08:00
David Mak	19122e2905	[core] codegen: Rename classes/functions for consistency - ContiguousNDArrayFields -> ContiguousNDArrayStructFields - ndarray/nditer: Add _field suffix to field accessors	2024-12-30 16:50:18 +08:00
David Mak	318371a509	[core] irrt: Minor cleanup	2024-12-30 14:13:48 +08:00
David Mak	35e3042435	[core] Refactor/Remove redundant and unused constructs - Use ProxyValue.name where necessary - Remove NDArrayValue::ptr_to_{shape,strides} - Remove functions made obsolete by ndstrides - Remove use statement for ndarray::views as it only contain an impl block. - Remove class_names field in Resolvers of test sources	2024-12-30 14:13:48 +08:00
David Mak	0e5940c49d	[meta] Refactor itertools::{chain,enumerate,repeat_n} with std equiv	2024-12-30 14:13:48 +08:00
David Mak	fbf0053c24	[core] irrt/string: Minor cleanup - Refactor __nac3_str_eq to always return bool - Use `get_usize_dependent_function_name` to get IRRT func name	2024-12-30 14:04:42 +08:00
Sébastien Bourdeauducq	456aefa6ee	clean up duplicate include	2024-12-30 13:03:31 +08:00
ram	49a7469b4a	use memcmp for string comparison Co-authored-by: ram <RAMTEJ001@e.ntu.edu.sg> Co-committed-by: ram <RAMTEJ001@e.ntu.edu.sg>	2024-12-30 13:02:09 +08:00
Sebastien Bourdeauducq	1531b6cc98	cargo: update dependencies	2024-12-13 19:42:01 +08:00
Sebastien Bourdeauducq	9bbc40bbfa	flake: update dependencies	2024-12-13 19:41:52 +08:00
Sebastien Bourdeauducq	790e56d106	msys2: update	2024-12-13 19:39:39 +08:00
David Mak	a00eb7969e	[core] codegen: Implement matrix_power Last of the functions that need to be ported over to strided-ndarray.	2024-12-13 15:23:31 +08:00
David Mak	27a6f47330	[core] codegen: Implement construction of unsized ndarrays Partially based on `f731e604`: core/ndstrides: add more ScalarOrNDArray and NDArrayObject utils.	2024-12-13 15:23:31 +08:00
David Mak	061747c67b	[core] codegen: Implement NDArrayValue::atleast_nd Based on `9cfa2622`: core/ndstrides: add NDArrayObject::atleast_nd.	2024-12-13 15:23:31 +08:00
David Mak	dc91d9e35a	[core] codegen: Implement ScalarOrNDArray and use it in indexing Based on `8f9d2d82`: core/ndstrides: implement ndarray indexing.	2024-12-13 15:23:31 +08:00
David Mak	438943ac6f	[core] codegen: Implement indexing for NDArray Based on `8f9d2d82`: core/ndstrides: implement ndarray indexing The functionality for `...` and `np.newaxis` is there in IRRT, but there is no implementation of them for @kernel Python expressions because of M-Labs/nac3#486.	2024-12-13 15:23:31 +08:00
lyken	678e56c95d	[core] irrt: rename NDIndex to NDIndexInt Unfortunately the name `NDIndex` is used in later commits. Renaming this typedef to `NDIndexInt` to avoid amending. `NDIndexInt` will be removed anyway when ndarray strides is completed.	2024-12-13 15:23:31 +08:00
lyken	fdfc80ca5f	[core] codegen: Implement Slice{Type,Value}, RustSlice Based on `01c96396`: core/irrt: add Slice and Range and part of `8f9d2d82`: core/ndstrides: implement ndarray indexing. Needed for implementing general ndarray indexing. Currently IRRT slice and range have nothing to do with NAC3's slice and range. The IRRT slice and range are currently there to implement ndarray specific features. However, in the future their definitions may be used to replace that of NAC3's. (NAC3's range is a [i32 x 3], IRRT's range is a proper struct. NAC3 does not have a slice struct).	2024-12-13 15:23:31 +08:00
David Mak	8b3429d62a	[artiq] Reimplement get_obj_value for strided ndarray Based on `7ef93472`: artiq: reimplement get_obj_value to use ndarray with strides	2024-12-13 15:23:31 +08:00
David Mak	f4c5038b95	[artiq] codegen: Reimplement polymorphic_print for strided ndarray Based on `2a6ee503`: artiq: reimplement polymorphic_print for ndarray	2024-12-13 15:23:31 +08:00
David Mak	ddd16738a6	[core] codegen: implement ndarray iterator NDIter Based on `50f960ab`: core/ndstrides: implement ndarray iterator NDIter A necessary utility to iterate through all elements in a possibly strided ndarray.	2024-12-13 15:23:31 +08:00
David Mak	44c49dc102	[artiq] codegen: Reimplement polymorphic_print for strided ndarray Based on `2a6ee503`: artiq: reimplement polymorphic_print for ndarray	2024-12-13 15:23:31 +08:00
David Mak	e4bd376587	[core] codegen: Implement ContiguousNDArray Fixes compatibility with linalg algorithms. matrix_power is missing due to the need for indexing support.	2024-12-13 15:23:29 +08:00
David Mak	44498f22f6	[core] codegen: Implement NDArray functions from `a0a1f35b`	2024-12-13 15:22:11 +08:00
David Mak	110416d07a	[core] codegen/irrt: Add IRRT functions for strided-ndarray	2024-12-13 15:22:11 +08:00
David Mak	08a7d01a13	[core] Add itemsize and strides to NDArray struct Temporarily disable linalg ndarray tests as they are not ported to work with strided-ndarray.	2024-12-13 15:22:09 +08:00
David Mak	3cd36fddc3	[core] codegen/types: Add check_struct_type_matches_fields Shorthand for checking if a type is representable by a StructFields instance.	2024-12-12 11:40:44 +08:00
David Mak	56a7a9e03d	[core] codegen: Add helper functions for create+call functions Replacement for various FnCall methods from legacy ndstrides implementation.	2024-12-12 11:30:36 +08:00
David Mak	574ae40f97	[core] codegen: Add call_memcpy_generic_array Replacement for Instance<Ptr>::copy_from from legacy ndstrides implementation.	2024-12-12 11:30:36 +08:00
David Mak	aa293b6bea	[core] codegen: Add type_aligned_alloca	2024-12-12 11:30:35 +08:00
David Mak	eb4b881690	[core] Expose {types,values}::ndarray modules Allows better encapsulation of members in these modules rather than allowing them to leak into types/values mod.	2024-12-12 11:30:14 +08:00
David Mak	3d0a1d281c	[core] Expose irrt::ndarray	2024-12-10 12:49:49 +08:00
David Mak	ad67a99c8f	[core] codegen: Cleanup builtin_fns.rs - Unpack tuples directly in function argument - Replace Vec parameters with slices - Replace unwrap-transform with map-unwrap	2024-12-10 12:49:49 +08:00
David Mak	8e2b50df21	[core] codegen/ndarray: Cleanup - Remove redundant size param - Add *_fields functions and docs	2024-12-09 13:01:08 +08:00
David Mak	06092ad29b	[core] Move alloca and map_value of ProxyType to implementations These functions may not be invokable by the same set of parameters as some classes has associated states.	2024-12-09 12:51:50 +08:00
David Mak	d62c6b95fd	[core] codegen/types: Rename StructField::set_from_value	2024-12-09 12:51:50 +08:00
David Mak	95e29d9997	[core] codegen: Move ndarray type/value as a separate module	2024-12-09 12:51:46 +08:00
David Mak	536ed2146c	[meta] Remove all mentions of build_int_cast build_int_cast performs signed extension or truncation depending on the source and target int lengths. This is usually not what we want - We want zero-extension instead. Replace all instances of build_int_cast with build_int_z_extend_or_bit_cast to fix this issue.	2024-12-09 12:51:39 +08:00
David Mak	d484d44d95	[standalone] linalg: Fix function name in error message	2024-12-09 12:09:57 +08:00
David Mak	ac978864f2	[meta] Apply clippy suggestions	2024-12-09 12:08:41 +08:00
David Mak	95254f8464	[meta] Update Cargo dependencies	2024-12-09 12:08:41 +08:00
occheung	964945d244	string_store: update embedding map after compilation	2024-12-03 16:45:46 +08:00
occheung	ae09a0d444	exceptions: preallocate in NAC3 instead	2024-12-03 16:45:05 +08:00
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