AILang/design/models/rc-uniqueness.md

# RC + Uniqueness — memory model whitepaper

## Dual allocator — RC canonical, Boehm parity oracle

AILang ships two allocator backends with an asymmetric role:

- **RC is canonical.** `--alloc=rc` is the CLI default for
  `ail build` and `ail run` (see [pipeline](pipeline.md)). The
  runtime AILang's [memory model](../contracts/memory-model.md)
  (RC + uniqueness inference) is designed for. New examples,
  benches, and corpus tests run under RC unless they explicitly
  pin GC.
- **Boehm stays as a parity oracle.** `--alloc=gc` remains
  reachable. Its load-bearing job is differential diagnosis: when
  RC produces a segfault, refcount underflow, or wrong stdout, the
  GC build of the same module is the cheap "memory bug or logic
  bug?" probe. The end-to-end suite includes per-example
  parity tests that run both backends and assert byte-identical
  stdout — those tests are what make the oracle real.
- **`--alloc=bump`** is unchanged: a leak-only bench instrument,
  not a production target.

Full Boehm retirement (drop libgc, remove the gc backend) reopens
when the parity oracle stops paying its keep — concretely, when a
few iter families ship without the gc arm catching anything that
the rc arm did not already catch. Until then, the cost of
keeping libgc as a build dependency is accepted in exchange for
diagnostic leverage. The
[RC + uniqueness memory model](../contracts/memory-model.md), built
on the [language constraints](../contracts/language-constraints.md),
holds as the specification of the canonical runtime; the rest of
this section documents the Boehm half, retained as the oracle.

**Choice: Boehm-Demers-Weiser conservative GC.** The simplest
working option:

- Replace `malloc(...)` with `GC_malloc(...)` in every IR site
  (currently `lower_ctor`'s ADT box, `lower_lambda`'s env block
  and closure pair).
- Replace the IR-level `declare ptr @malloc(i64)` with
  `declare ptr @GC_malloc(i64)`.
- Add `-lgc` to the `clang` link command (in
  `crates/ail/src/main.rs`'s `Build` / `Run` paths).
- No language-level change. No AST change. No schema change.

Rationale:

- **Mature.** Boehm has been the default conservative GC for
  decades. Linux distros ship it as `libgc` / `libgc-dev` /
  `gc` (Arch).
- **No language work.** Conservative scan of the C stack handles
  AILang's stack frames without LLVM stack-map infrastructure
  (which is its own multi-iter design).
- **Single-iter integration.** Lift-and-shift of the four
  allocation sites; all existing tests must still pass with
  identical output.

Trade-offs accepted:

- **Conservative over-retention.** A user-supplied `Int` field
  whose value happens to coincide with a heap address will pin
  that allocation. In practice, vanishingly rare for typical
  values; survivable.
- **Pause time non-deterministic.** Boehm uses stop-the-world
  mark-sweep. For LLM-author-written stdlib code at MVP scale,
  pause times are not the bottleneck.
- **Build-time dependency.** `libgc` must be installed on the
  build host. Users without it get a link-time error from
  clang, not a silent failure.

## Per-fn arena via stack `alloca`

This optimisation is layered on top of Boehm in its simplest form.
`ailang-codegen` runs an escape-analysis pre-pass over every fn
body (and every lifted lambda thunk body); allocations the pass
proves do not outlive the fn frame are lowered to LLVM `alloca`
instead of `@GC_malloc`. Allocations that may escape continue to
use `@GC_malloc`. The Boehm collector is still linked and
unchanged; this is purely an optimisation above the floor.

**Allocation mechanism: LLVM `alloca`** (not a heap arena). Stack
allocation matches the "freed at fn return" lifetime exactly,
needs no malloc/free pair, and integrates with LLVM's existing
optimiser (mem2reg / SROA may further promote the alloca'd box
to registers if the box is small and its uses are simple). No
new runtime is introduced; no language-level change; no AST or
schema change.

**Escape rule (conservative).** A `Term::Ctor` or `Term::Lam`
allocation is non-escaping iff (1) it is the value of a
`Term::Let { name = X, value = ALLOC, body = B }`, and (2) the
body `B` does not let any value derived from `X` flow past the
fn frame. "Derived from" follows two propagation rules:
- A `Term::Match` whose scrutinee is a `Var` referring to a
  tainted name propagates taint to every pattern-bound name in
  every arm. (Pattern bindings hold field projections of the
  scrutinee, which live inside the same allocation.)
- A `Term::Let { name = Y, value = Var(t), ... }` where `t` is
  tainted makes `Y` tainted in the let's body.

A tainted name "escapes" if it appears in any of: the tail
position of `B`, the arg list of any `Term::App` / `Term::Do`,
the field list of a `Term::Ctor`, or the free-var capture set of
a `Term::Lam`. The closure-pair-callee position of `Term::App`
where the callee is a bare `Var` to the tainted name is NOT an
escape (calling locally is fine).

**What this is not.** Not a region-inference system. Not
flow-sensitive within an arm. Not field-sensitive (pattern
bindings are tainted wholesale). Precision can be improved later;
correctness is the priority for this iter. A pessimistic answer
(claiming an allocation escapes when it does not) only loses
optimisation, never correctness.

**Codegen integration.** Three sites in
`ailang-codegen/src/lib.rs`:
- `lower_ctor` — ADT box.
- `lower_lambda` env block (when there are captures).
- `lower_lambda` closure pair (always 16 bytes).

Each site queries the per-fn `non_escape: BTreeSet<usize>` (raw
pointer addresses of `Term::Ctor` / `Term::Lam` AST nodes flagged
as non-escaping). On a hit the emitter writes
`alloca i8, i64 <size>, align 8`; on a miss it writes
`call ptr @GC_malloc(i64 <size>)`. The rest of the lowering (tag
store, field stores, closure-pair packing) is identical.

The closure-pair and its env share an escape verdict — they have
parallel lifetimes. If the closure pair is non-escaping, the env
is too.

## Memory model — RC + Uniqueness with LLM-author annotations

**The GC bench (`bench/run.sh`) showed
Boehm contributing a substantial fraction of runtime on allocation-heavy workloads
that hold the heap fully live (bench notes in JOURNAL). The
mainstream "RC + inference" position is extended with mandatory
LLM-author mode annotations (`borrow` / `own`), explicit `clone`,
first-class `reuse-as`, and `drop-iterative` data attrs.**

The cost of GC is structurally in the allocate path — Boehm's
`GC_malloc` is structurally slower than a bump pointer, and the bench
workloads exercised allocate cost without collection cost.
Tracing GC's irreducible variability cannot be tuned away; RC's
costs are bounded and analysable per program point. A corpus
committed to one memory model is expensive to switch — pre-
stdlib is the cheapest moment to commit.

**Choice.** AILang's canonical [memory model](../contracts/memory-model.md)
is reference counting with static uniqueness inference **and
explicit LLM-author annotations on fn signatures**, in the lineage
of Lean 4 / Roc / Koka. Boehm becomes a transitional allocator (see
the dual-allocator section above) and is retired when the RC pipeline
matches the bump-allocator floor within an acceptable margin (target
1.3× on `bench/run.sh`).

**Workload scope of the 1.3× target.** The 1.3× target was
calibrated on the original `bench/run.sh` corpus: linear list
sum (`bench_list_sum`) and tree walk (`bench_tree_walk`) — uniform
single-allocation-per-step workloads where one inc/dec pair
amortises against one allocation. The corpus was later extended
with `bench_closure_chain` (closure-pair allocation: each step
allocates *two* heap objects, the closure cell and its captured
env struct) and `bench_hof_pipeline` (poly-ADT + indirect
dispatch). The closure-chain fixture measures wider than the 1.3×
linear/tree target: each step pays two allocs and two decs against
one bump-pointer bump, doubling the allocation tax on closure
construction (current ratio recorded in JOURNAL bench entries).
This is a representational cost of the closure-pair layout,
not a defect in the RC implementation; a future slab/pool
allocator for fixed-shape pair cells (a Boehm-retirement follow-up)
would compress this ratio without changing semantics.

The 1.3× retirement target therefore applies to the linear /
tree / poly-ADT subset of the corpus. Closure-heavy workloads are
tracked under a wider band (the closure-chain baseline records its rc/bump ratio as the `rc_over_bump` reference value with ±15% tolerance) and
are explicitly excluded from the Boehm-retirement gate until a
slab/pool answer ships. The
[memory model](../contracts/memory-model.md)'s RC commitment is
unchanged; what is scoped is the *quantitative* retirement criterion,
not the choice of memory model.

The architecture has two layers:

1. **Inference.** A post-typecheck pass produces a per-node
   uniqueness side table. Codegen uses it to elide inc/dec
   wherever provably redundant.
2. **LLM-author annotations.** Fn signatures carry mandatory
   `(borrow T)` / `(own T)` mode markers. Authors mark
   sharing-vs-consumption explicitly. The compiler verifies
   rather than guesses.

The combination plays to what LLMs are good at (writing slightly
more annotation per definition) and avoids what compilers are
bad at (proving sharing absent in the face of recursion +
closures + match).

## The LLM-aware sharpening

A mainstream RC implementation (think Lean 4 in default mode)
infers everything from naked AST plus a few optional hints. The
inference is conservative; whatever it can't prove unique becomes
shared and pays runtime inc/dec. AILang exploits its target
audience to push that conservative ceiling higher.

Five mechanisms.

**(1) Mandatory `(borrow T)` / `(own T)` on fn signatures.**

```
(fn list_length
  (type (fn-type (params (borrow (List Int))) (ret (con Int))))
  ...)

(fn sum_list_consume
  (type (fn-type (params (own (List Int))) (ret (con Int))))
  ...)
```

`(borrow T)` declares the parameter is read-only and lives at
most until the call returns; the caller still owns it; the
callee performs no inc/dec on it. `(own T)` declares ownership
transfer; the callee consumes the value and is responsible for
its end-of-life. The declaration is structural (visible in JSON)
and binding (the typechecker rejects bodies that contradict it).

For a Lean 4 / Roc author this is all *optional* and inferred
when omitted. AILang makes it mandatory because the LLM author
can carry the cognitive cost trivially, and the compiler gains a
precise contract at every call site instead of a probabilistic
guess.

**(2) Linear-by-default consumption with explicit `(clone X)`**
(the `Term::Clone` schema entry lives in
[Data model](../contracts/data-model.md)).

In bodies, every binder is consumed by exactly one `own`-mode
use. If the LLM writes:

```
(let p (expensive_fn x)
  (let r1 (consume_a p)        ; consume_a takes (own); consumes p
    (let r2 (consume_b p)      ; ERROR: p already consumed
      ...)))
```

the compiler emits a structured non-linear-use diagnostic with
concrete `suggested_rewrites`:

- "make consume_a borrow": refactor consume_a's signature, no
  body change at the call site;
- "explicit clone": insert `(clone p)` at the first use;
- "fuse traversal": replace the two separate calls with a fused fn.

The LLM picks one. There is no implicit clone — sharing always
costs visible source.

**(3) Reuse hints as first-class.**

```
(fn map_inc
  (type (fn-type (params (own (List Int))) (ret (own (List Int)))))
  (params xs)
  (body
    (match xs
      (case Nil Nil)
      (case (Cons h t)
        (reuse-as xs (term-ctor List Cons (app + h 1) (app map_inc t)))))))
```

`(reuse-as SRC NEW-CTOR)` asks the codegen to allocate `NEW-CTOR`
in `SRC`'s memory slot. Compiler verifies: `SRC` is owned, this
is its last use, sizes match. On a hit: no malloc, no free — the
box is overwritten in place. On a miss: structured diagnostic
explains which precondition failed; the LLM either adjusts the
surrounding code or removes the hint.

This matches Lean 4 / Roc reuse analysis but lifts it from
"compiler-inferred when possible" to "author-asserted, compiler-
verified". The LLM applies it everywhere it expects to fire and
lets the compiler bounce the request when it can't.

**(4) `(drop-iterative)` annotation on data declarations.**

```
(data Tree (vars a)
  (ctor Leaf)
  (ctor Node a (Tree a) (Tree a))
  (drop-iterative))
```

When the refcount of a `Tree` value reaches zero, the synthesised
dec-on-zero traversal is iterative (worklist + heap-allocated
stack) instead of recursive. Avoids stack overflow on deep
structures. The LLM adds the annotation where appropriate; the
compiler refuses to emit recursive dec-cascade on annotated types.

**(5) Structured compiler diagnostics with `suggested_rewrites`.**

Every RC-mode error (use-after-consume, mode-mismatch,
reuse-as-fail, drop-cascade-too-deep) emits a JSON object
containing the failure kind, the source span, and a list of
concrete rewrite suggestions in form-A AILang. The LLM consumes
these without prose-parsing. This is the missing half of the
LLM-as-author story: the language spec defines not only what
compiles, but what the compiler tells the author when it doesn't.

## Inference algorithm

Post-typecheck, post-`lift_letrecs` (see [pipeline](pipeline.md)),
pre-codegen pass over the elaborated module. For each `Term` node that produces or binds a
boxed value, the pass computes a uniqueness flag:

- **Unique:** at this program point, the reference is the only
  outstanding reference to its referent.
- **Shared:** there may be multiple outstanding references.

A reference is *unique* if every path from its allocation to the
current program point passes through exactly one binding. The
inference is a forward dataflow over the AST. The annotations
(`borrow` / `own`) provide the inter-fn contract; the
inference fills in intra-fn detail.