This PR applies two minor tweaks:
- `tests/bench/sym/simp_1.lean`: share-common the proof term before
counting objects in `getProofSize`, so the reported size reflects the
shared representation.
- `tests/elab/sym_simp_3.lean`: use `>>` instead of `.andThen` when
composing `Sym.Simp` methods.
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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>
This PR optimizes congruence proof construction in `Sym.simp` by
avoiding
`inferType` calls on expressions that are less likely to be cached.
Instead of
inferring types of expressions like `@HAdd.hAdd Nat Nat Nat instAdd 5`,
we infer
the type of the function prefix `@HAdd.hAdd Nat Nat Nat instAdd` and
traverse
the forall telescope.
The key insight is that function prefixes are more likely shared across
many call sites
(e.g., all `Nat` additions use the same `@HAdd.hAdd Nat Nat Nat
instAdd`), so they
benefit from `inferType` caching.
Benchmark results show improvements on workloads with shared function
prefixes:
- `many_rewrites_5000`: 48.8ms → 43.1ms (-12%)
- `term_tree_5000`: 53.4ms → 30.5ms (-43%)
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.
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.
This PR ensures that `Sym.simp` checks thresholds for maximum recursion
depth and maximum number of steps. It also invokes `checkSystem`.
Additionally, this PR simplifies the main loop. Assigned metavariables
and `zetaDelta` reduction are now handled by installing `pre`/`post`
methods.
This PR adds `getMatch` and `getMatchWithExtra` for retrieving patterns
from
discrimination trees in the symbolic simulation framework.
The PR also adds uses `DiscrTree` to implement indexing in `Sym.simp`.
