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5 commits

Author SHA1 Message Date
Leonardo de Moura
d2907b5c96
feat: add contextDependent to Sym.simp Result with two-tier cache (#12996)
This PR adds per-result `contextDependent` tracking to `Sym.Simp.Result`
and splits the simplifier cache into persistent (context-independent)
and transient (context-dependent, cleared on binder entry). This
replaces the coarse `wellBehavedMethods` flag.

Key changes:
- Add `contextDependent : Bool := false` to `Result.rfl` and
`Result.step`
- Split `State.cache` into `persistentCache` and `transientCache`
- Remove `wellBehavedMethods` from `Methods`
- Replace `withoutModifyingCacheIfNotWellBehaved` with
`withFreshTransientCache`
- Change `DischargeResult` to an inductive (`.failed`/`.solved`)
- Add `dischargeAssumption` (context-dependent discharger for testing)
- Add `sym.simp.debug.cache` trace class
- Propagate `contextDependent` through all combinators (congruence,
transitivity, control flow, arrows, rewriting)
- Add `mkRflResult`/`mkRflResultCD` to avoid dynamic allocation of rfl
results
- Fix `isRfl` to ignore `contextDependent` (was silently broken by the
extra field)

Propagation invariant: when combining sub-results, `cd` is the
disjunction of ALL sub-results' flags — including `.rfl` results. If
`simp` returned `.rfl (contextDependent := true)`, it means `simp` might
take a completely different code path in another local context, so all
downstream results must be marked context-dependent.

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-20 00:22:08 +00:00
Leonardo de Moura
0e4794a1a9
test: benchmarks for lambda-telescopes (#11929) 2026-01-08 00:20:03 +00:00
Leonardo de Moura
175661b6c3
refactor: reorganize SymM and GrindM monad hierarchy (#11909)
This PR reorganizes the monad hierarchy for symbolic computation in
Lean.

## Motivation

We want a clean layering where:
1. A foundational monad (`SymM`) provides maximally shared terms and
structural/syntactic `isDefEq`
2. `GrindM` builds on this foundation, adding E-graphs, congruence
closure, and decision procedures
3. Symbolic execution / VCGen uses `GrindM` directly without introducing
a third monad

## Changes

The core symbolic computation layer still lives in `Lean.Meta.Sym`. This
monad (`SymM`) provides:
- Maximally shared terms with pointer-based equality
- Structural/syntactic `isDefEq` and matching (no reduction, predictable
cost)
- Monotonic local contexts (no `revert` or `clear`), enabling O(1)
metavariable validation
- Efficient `intro`, `apply`, and `simp` implementations

The name "Sym" reflects that this is infrastructure for symbolic
computation: symbolic simulation, verification condition generation, and
decision procedures.

### Updated hierarchy

```
Lean.Meta.Sym   -- SymM: shared terms, syntactic isDefEq, intro, apply, simp
Lean.Meta.Grind -- GrindM: E-graphs, congruence closure (extends SymM)
```

Symbolic execution is a usage pattern of `GrindM` operating on
`Grind.Goal`, not a separate monad. This keeps the API surface minimal:
users learn two monads, and VCGen is "how you use `GrindM`" (for users
that want to use `grind`) rather than a third abstraction to understand.
2026-01-06 01:12:07 +00:00
Leonardo de Moura
82f60a7ff3
feat: pre and post may return "done" in Sym.simp (#11900)
This PR adds a `done` flag to the result returned by `Simproc`s in
`Sym.simp`.

The `done` flag controls whether simplification should continue after
the result:
- `done = false` (default): Continue with subsequent simplification
steps
- `done = true`: Stop processing, return this result as final

## Use cases for `done = true`

### In `pre` simprocs
Skip simplification of certain subterms entirely:
```
def skipLambdas : Simproc := fun e =>
  if e.isLambda then return .rfl (done := true)
  else return .rfl
```

### In `post` simprocs
Perform single-pass normalization without recursive simplification:
```
def singlePassNormalize : Simproc := fun e =>
  if let some (e', h) ← tryNormalize e then
    return .step e' h (done := true)
  else return .rfl
```
With `done = true`, the result `e'` won't be recursively simplified.
2026-01-05 02:10:06 +00:00
Leonardo de Moura
f1c903ca65
feat: simplify lambdas in Sym.simp (#11898)
This PR adds support for simplifying lambda expressions in `Sym.simp`.
It is much more efficient than standard simp for very large lambda
expressions with many binders. The key idea is to generate a custom
function extensionality theorem for the type of the lambda being
simplified.

This technique is compatible with the standard `simp` tactic, and will
be ported in a separate PR.

<img width="581" height="455" alt="image"
src="https://github.com/user-attachments/assets/5911dc6c-03f0-48ed-843b-b8cb4f67ee61"
/>

### `lambda` benchmark summary

| Lambda size | MetaM (ms) | SymM (ms) | Speedup |
|-------------|------------|-----------|---------|
| 50          | 22.7       | 0.74      | ~31×    |
| 100         | 120.5      | 1.75      | ~69×    |
| 150         | 359.6      | 2.90      | ~124×   |
| 200         | 809.5      | 4.51      | ~180×   |
2026-01-05 01:00:30 +00:00