4852df51fc
DESIGN.md: - CLI block: add `ail run`. - Smoke-test list: add list_map.ail.json (the dogfood example). JOURNAL: append Iter 9 entry covering the dogfood result, two friction points surfaced (single-arg fn-type pretty-print parens; absence of a sequencing operator), the `ail run` CLI helper, and a ranked Iter 10 plan with three candidates (polymorphism, `;`, GC). Tentative pick is (2) `;` next, (1) polymorphism for Iter 11. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
288 lines
11 KiB
Markdown
288 lines
11 KiB
Markdown
# AILang — design decisions
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This document records the core decisions for AILang. It is my contract with
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myself across future iterations. Prefer cuts over growth.
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## Goal
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AILang is a programming language for LLM authors. It compiles to LLVM IR.
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Performance: native, no GC for the MVP.
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Optimised for:
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- **Machine readability** over human ergonomics. The source is structured.
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- **Local reasoning.** Every definition carries its full type and effects.
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- **Provability.** Pure core language, explicit effects, optional refinements.
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- **Robustness against hallucinations.** Symbols are hashable; tools can verify
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existence without spending context window.
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## Project ecosystem
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AILang is not just a language but an ecosystem. The language on its own is
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only valuable when its surroundings make it usable, checkable, and
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extensible for its target user (LLM authors). The repo therefore contains
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several equally important components — none of them optional, all of them
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evolving in lockstep with the language:
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- **Language core** (`crates/ailang-core`, `crates/ailang-check`,
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`crates/ailang-codegen`): AST, type system, codegen.
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- **CLI** (`crates/ail`): toolchain for tooling consumers — `manifest`,
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`describe`, `deps`, `check`, `build`, etc., preferably with `--json` for
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machine consumption.
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- **Examples** (`examples/`): canonical `.ail.json` programs. They are
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specification anchors, not demos — the E2E suite hangs off them.
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- **Agents** (`agents/`): specialised sub-prompts (implementer,
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architect, tester, debugger) that form the project's own LLM tooling.
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They are a versioned part of the repo. See `agents/README.md`.
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- **Docs** (`docs/`): DESIGN.md (what and why), JOURNAL.md (history).
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- **Tests**: unit tests per crate plus E2E in `crates/ail/tests/e2e.rs`. Every
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new compiler path needs a test, otherwise the feature does not count as done.
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When the language grows, these components grow with it. New tools that
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strengthen the LLM tooling (e.g. `ail diff`, IR snapshot diffs, new agents)
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explicitly belong in the ecosystem inventory of this section and are added
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here as soon as they are established.
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## Project language: English
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All in-tree content is written in English: source code (identifiers,
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comments, string literals, CLI help), design documents, the journal, agent
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prompts, READMEs, commit messages, examples, and `CLAUDE.md`. The live
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conversation between user and me stays German for ergonomic reasons;
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everything that lands in git is English. This keeps diffs and tooling output
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uniform and matches the audience for AILang (LLM authors), for whom English
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is the default.
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## Decision 1: source = data, not text
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A module is a JSON object with a fixed schema. There is no parser for
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free-form text. Typos in identifiers turn into hash-lookup errors that the
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compiler proposes a fix for directly.
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A textual form exists (`.ail`, S-expression-like), but only as a
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bidirectional projection of the JSON form. It is intended for human reviews
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and diffs.
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**Canonical format:** `.ail.json` with deterministic key order.
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## Decision 2: content-addressed definitions
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Every top-level definition has a `hash` value (BLAKE3 over canonical JSON
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without the `hash` field itself). References between definitions go primarily
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by name — names are for readability. The hash is the canonical identity.
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Advantages:
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- Refactoring by adding new defs, not by in-place change. Old versions stay
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callable until manually removed.
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- Caching of typecheck results and codegen per hash.
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- Diffs show exactly which def has changed.
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## Decision 3: pure core language + algebraic effects
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The default is total, pure functions. Effects are declared as a set in the
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function type: `(Int) -> Int ![IO]`. The effect set is row-polymorphic
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(`![IO | r]`). In the MVP only the effects `IO` and `Diverge` (for infinite
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loops) are wired up.
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This is the most important LLM property: when I read a function, I can trust
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its signature without reading the body.
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## Decision 4: Hindley-Milner + optional refinements
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MVP: HM with let-polymorphism. All types are inferable, but at the top level
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they must always be explicitly annotated (for local reasoning).
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Later: refinement annotations that escalate to SMT. `(i: Int | i >= 0)`. They
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are reserved in the AST from the start, but in the MVP they are simply passed
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through as opaque strings.
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## Decision 5: emit LLVM IR as text
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Instead of `inkwell` or `llvm-sys`: AILang produces `.ll` files as strings
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and hands them to `clang` for linking.
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Rationale:
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- The LLVM IR text syntax is largely stable across versions.
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- No build dependency on a specific libllvm version.
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- Generated code is trivially inspectable, which makes debugging much easier.
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- An LLM can read the generated IR directly, which is harder with opaque
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library calls.
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Trade-off: no inline optimisations through the LLVM API. We rely on
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`clang -O2` as the standard pipeline.
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## Mangling scheme (Iter 5c)
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All AILang functions are mangled to `@ail_<module>_<def>` — even in the
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single-module case. Constants likewise (`@ail_<module>_<const>`). Global
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string literals carry a short hint for readability:
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`@.str_<module>_<hint>_<idx>` (e.g. `@.str_sum_fmt_int_0`). The entry point
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is a `define i32 @main()` trampoline (C / LLVM ABI) that calls
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`@ail_<entry-module>_main()`. `source_filename` exists exactly once per
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workspace and carries the entry-module name (`<entry-module>.ail`).
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## Convention: qualified cross-module references (Iter 5b)
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Cross-module calls use **no** new AST node. Instead, a `Term::Var { name }`
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with exactly one dot in the name is a qualified reference: `<prefix>.<def>`.
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- `<prefix>` is an import alias (`import { module: "X", as: "<prefix>" }`)
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or, when imported without an alias, the module name itself.
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- `<def>` is the name of a top-level definition in the target module.
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- Def names MUST NOT contain a dot — the typechecker reports
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`invalid-def-name` with `ctx: { "reason": "contains-dot" }`.
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- The workspace loader (Iter 5a) finds all reachable modules; the
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typechecker (Iter 5b, `check_workspace`) resolves dotted names through the
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import map. Diagnostic codes: `unknown-module` (prefix not imported),
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`unknown-import` (module found, def not).
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Hash stability: no new AST node, no renamed fields — all previous module
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hashes stay bit-identical.
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## Data model (MVP)
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### Module
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```jsonc
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{
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"schema": "ailang/v0",
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"name": "<id>",
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"imports": [{ "module": "<id>", "as": "<id>" }],
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"defs": [Def...]
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}
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```
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### Def
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`kind ∈ { "fn", "type", "effect", "const" }`. In the MVP only `fn` and `const`.
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```jsonc
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{
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"kind": "fn",
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"name": "<id>",
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"type": Type,
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"params": ["<id>"...],
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"body": Term,
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"doc": "<optional string>"
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}
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```
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### Term (expression)
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```jsonc
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{ "t": "lit", "lit": { "kind": "int" | "bool" | "unit", "value": ... } }
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{ "t": "var", "name": "<id>" }
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{ "t": "app", "fn": Term, "args": [Term...] }
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{ "t": "let", "name": "<id>", "value": Term, "body": Term }
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{ "t": "if", "cond": Term, "then": Term, "else": Term }
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{ "t": "do", "op": "<eff>/<op>", "args": [Term...] }
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{ "t": "ctor", "type": "<id>", "ctor": "<id>", "args": [Term...] }
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{ "t": "match", "scrutinee": Term, "arms": [Arm...] }
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{ "t": "lam",
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"params": ["<id>"...],
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"paramTypes": [Type...],
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"retType": Type,
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"effects": ["<id>"...],
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"body": Term }
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```
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In the MVP, `do` is only a direct call to a built-in effect op (no handler).
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A `lam` term constructs an anonymous function value; free variables of
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its body are captured from the enclosing scope (see Iter 8 closure
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conversion in JOURNAL).
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### Type
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```jsonc
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{ "k": "con", "name": "Int" }
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{ "k": "con", "name": "Bool" }
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{ "k": "con", "name": "Unit" }
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{ "k": "fn", "params": [Type...], "ret": Type, "effects": ["IO"...] }
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{ "k": "var", "name": "a" }
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{ "k": "forall", "vars": ["a"...], "body": Type }
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```
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## Pipeline
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```
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.ail.json ─┐
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├─ load + validate schema
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├─ resolve names + assign hashes
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├─ typecheck (HM, effect rows)
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├─ lower to MIR (SSA-like, named SSA values)
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├─ emit LLVM IR (.ll)
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└─ clang -O2 *.ll -o binary
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```
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## CLI
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```
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ail check <module.ail.json> — loads, validates, typechecks
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ail manifest <module.ail.json> — table: name :: type !effects [hash]
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ail describe <module> <name> — detail of a definition
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ail render <module> — JSON → pretty-print
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ail parse <module.ail> — pretty-print → JSON (for bootstrapping)
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ail emit-ir <module> — writes .ll
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ail build <module> — full pipeline → binary
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ail run <module> — build + execute (tempdir), passthrough exit code
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```
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## Verification and correctness (across cycles)
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1. **Snapshot tests** for the pretty-printer and IR emit. The diff makes
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regressions visible immediately.
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2. **Property tests** for the JSON ↔ pretty-print roundtrip.
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3. **End-to-end tests** for `examples/` with expected program output.
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4. **Hash stability**: a test ensures the same def always produces the same
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hash.
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5. **CI pin** of the outputs in `tests/expected/`.
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## What is not (yet) supported
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Snapshot of the boundary at the end of Iter 8. Items move out of this list
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as iterations land; the JOURNAL records the exact iteration.
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- No effect handlers — only the built-in IO and Diverge ops.
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- No refinements / SMT escalation.
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- No polymorphism in inference. `Type::Forall` is parseable but the
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typechecker rejects polymorphic uses inside a body (`PolymorphicNot
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Supported`). Generic functions must be monomorphised by the author
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via separate top-level defs.
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- No cross-module ADTs. ADTs are local to a module; ctor names must be
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unique within their module but may collide across modules.
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- No visibility rules in imports. Every top-level def of an imported module
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is reachable; there is no `pub` / `priv`.
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- No GC. ADT boxes, lambda envs, and closure pairs all leak. Acceptable
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for current example programs; required before any longer-running
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program.
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What **is** supported (and used as the smoke test for the pipeline):
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- Int, Bool, Unit, **Str** as primitive types.
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- `if`, `let`, function calls, recursion.
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- Effects on function signatures, with `do op(args)` for direct effect
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ops (`io/print_int`, `io/print_bool`, `io/print_str`).
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- **ADTs + flat pattern matching** (Iter 3). Sub-patterns of a Ctor
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pattern are restricted to `Var` / `Wild`.
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- **Imports + qualified cross-module references** via dotted names
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(Iter 5).
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- **First-class function references** (Iter 7). A top-level fn name (or
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qualified `prefix.def`) used as a `Term::Var` is a fn-value.
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- **Anonymous lambdas with capture** (Iter 8). `Term::Lam` constructs a
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closure that captures any free variables of its body from the
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enclosing scope. All fn-values share a single ABI: a `ptr` to a
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closure pair `{ thunk_ptr, env_ptr }`. Top-level fns get an auto-
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generated adapter and a static closure pair (env = null) so they
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remain passable as values without heap overhead.
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Pipeline regression smoke tests:
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- `examples/sum.ail.json` → prints 55 (recursion, arithmetic).
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- `examples/list.ail.json` → prints 42 (ADTs + match).
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- `examples/hof.ail.json` → prints 42 (first-class fn-refs, indirect call).
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- `examples/closure.ail.json` → prints 42 (lambda capturing a let-bound var).
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- `examples/list_map.ail.json` → prints 2/4/6 (ADTs + closure + recursive
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HOF + IO; the dogfood smoke test).
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