This PR adds a symbol to the runtime for marking `Array`
non-linearities. This should allow users to
spot them more easily in profiles or hunt them down using a debugger.
This PR adds a new option to the function `simpHaveTelescope` in which
the `have` telescope is simplified in two passes:
* In the first pass, only the values and the body are simplified.
* In the second pass, unused declarations are eliminated.
This new mode eliminates **superlinear** behavior in the benchmark
`simp_3.lean`. Note that the kernel type checker still **exhibits**
quadratic behavior in this example, because it **does not have support**
for expanding a `have`/`let` telescope in a single step.
This PR adds two features to the message testing commands:
## `#guard_panic` command
A new `#guard_panic` command that succeeds if the nested command
produces a panic message. Unlike `#guard_msgs`, it does not check the
exact message content, only that a panic occurred.
This is useful for testing commands that are expected to panic, where
the exact panic message text may be volatile. It is particularly useful
when minimizing a panic discovered "in the wild", while ensuring the
panic behaviour is preserved.
## `substring := true` option for `#guard_msgs`
Adds a `substring := true` option to `#guard_msgs` that checks if the
docstring appears as a substring of the output (after whitespace
normalization), rather than requiring an exact match. This is useful
when you only care about part of the message.
Example:
```lean
/-- Unknown identifier -/
#guard_msgs (substring := true) in
example : α := x
```
## Refactoring
Also refactors `runAndCollectMessages` as a shared helper function used
by both `#guard_msgs` and `#guard_panic`.
🤖 Prepared with Claude Code
---------
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
This PR factors out the `have`-telescope support used in `simp`, and
implements it using the `MonadSimp` interface. The goal is to
use this nice infrastructure for both `Meta.simp` and `Sym.simp`.
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 implements `PersistentHashMap.findKeyD` and
`PersistentHashSet.findD`. The motivation is avoid two memory
allocations (`Prod.mk` and `Option.some`) when the collections contains
the key.
This PR fixes an issue where `grind` failed to prove `f ≠ 0` from `f * r
≠ 0` when using `Lean.Grind.CommSemiring`, but succeeded with
`Lean.Grind.Semiring`.
The `propagateMul` propagator handles `0 * a = 0` and `a * 0 = 0` rules
for semirings that don't have full ring support in grind. Previously,
`CommSemiring` was excluded because it uses a ring envelope for
normalization, but that approach doesn't propagate these equalities back
to the original terms. Now `CommSemiring` also uses `propagateMul`.
Reported as
https://leanprover.zulipchat.com/#narrow/channel/270676-lean4/topic/Grind.20failure.20for.20CommSemiring.2C.20not.20Semiring🤖 Prepared with Claude Code
---------
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
This PR adds `gcd_left_comm` lemmas for both `Nat` and `Int`:
- `Nat.gcd_left_comm`: `gcd m (gcd n k) = gcd n (gcd m k)`
- `Int.gcd_left_comm`: `gcd a (gcd b c) = gcd b (gcd a c)`
These lemmas establish the left-commutativity property for gcd,
complementing the existing `gcd_comm` and `gcd_assoc` lemmas.
Upstreamed from
https://github.com/leanprover-community/mathlib4/pull/33235🤖 Prepared with Claude Code
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
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 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× |
This PR adds a guard to `TagDeclarationExtension.tag` to check if the
declaration name is anonymous and return early if so. This prevents a
panic that could occur when modifiers like `meta` or `noncomputable` are
used in combination with syntax errors.
Reproducer:
```lean
public meta section
def private
```
Previously this would panic with:
```
PANIC at Lean.EnvExtension.modifyState: called on `async` extension,
must set `asyncDecl` in that case
```
This follows the same pattern as the fix in #10131 for `addDocString`
and the existing guard in `markNotMeta`.
See
https://leanprover.zulipchat.com/#narrow/channel/270676-lean4/topic/panic.20on.20doc-string/near/566110399🤖 Prepared with Claude Code
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
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`.
This PR adds discrimination tree support for the symbolic simulation
framework.
The new `DiscrTree.lean` module converts `Pattern` values into
discrimination
tree keys, treating proof/instance arguments and pattern variables as
wildcards
(`Key.star`). Motivation: efficient pattern retrieval during rewriting.
This PR adds a `with_unfolding_none` tactic that sets the transparency
mode to `.none`, in which no definitions are unfolded. This complements
the existing `with_unfolding_all` tactic and provides tactic-level
access to the `TransparencyMode.none` added in
https://github.com/leanprover/lean4/pull/11810.
🤖 Prepared with Claude Code
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
This PR adds the directory `Meta/DiscrTree` and reorganizes the code
into different files. Motivation: we are going to have new functions for
retrieving simplification theorems for the new structural simplifier.
This PR improves the performance of `getLine` by coalescing the locking
of the underlying `FILE*`.
Unfortunately we cannot use `getline` or `fgets` for this as our code
needs to handle `\0` chars
and Windows.
This PR makes `mvcgen with tac` fail if `tac` fails on one of the VCs,
just as `induction ... with tac` fails if `tac` fails on one of the
goals. The old behavior can be recovered by writing `mvcgen with try
tac` instead.
This PR adds configuration flag `Meta.Context.cacheInferType`. You can
use it to disable the `inferType` cache at `MetaM`. We use this flag to
implement `SymM` because it has its own cache based on pointer equality.
This PR adds `CongrInfo` analysis for function applications in the
symbolic simulator framework. `CongrInfo` determines how to build
congruence proofs for rewriting subterms efficiently, categorizing
functions into:
- `none`: no arguments can be rewritten (e.g., proofs)
- `fixedPrefix`: common case where implicit/instance arguments form a
fixed prefix and explicit arguments can be rewritten (e.g., `HAdd.hAdd`,
`Eq`)
- `interlaced`: rewritable and non-rewritable arguments alternate (e.g.,
`HEq`)
- `congrTheorem`: uses auto-generated congruence theorems for functions
with dependent proof arguments (e.g., `Array.eraseIdx`)
This PR changes `bv_decide`'s heuristic for what kinds of structures to
split on to also allow
splitting on structures where the fields have dependently typed widths.
For example:
```lean
structure Byte (w : Nat) where
/-- A two's complement integer value of width `w`. -/
val : BitVec w
/-- A per-bit poison mask of width `w`. -/
poison : BitVec w
```
This is to allow handling situations such as `(x : Byte 8)` where the
width becomes concrete after
splitting is done.
This PR adds an incremental variant of `shareCommon` for expressions
constructed from already-shared subterms. We use this when an expression
`e` was produced by a Lean API (e.g., `inferType`, `mkApp4`) that does
not preserve maximal sharing, but the inputs to that API were already
maximally shared. Unlike `shareCommon`, this function does not use a
local `Std.HashMap ExprPtr Expr` to track visited nodes. This is more
efficient when the number of new (unshared) nodes is small, which is the
common case when wrapping API calls that build a few constructor nodes
around shared inputs.
This PR changes the definition of the iterator combinators `takeWhileM`
and `dropWhileM` so that they use `MonadAttach`. This is only relevant
in rare cases, but makes it sometimes possible to prove such combinators
finite when the finiteness depends on properties of the monadic
predicate.
This PR fixes a bug in the new pattern matching procedure for the Sym
framework. It was not correctly handling assigned metavariables during
pattern matching.
It also improves the support for free variables.
This PR adds `BackwardRule` for efficient goal transformation via
backward chaining in `SymM`.
`BackwardRule` stores a theorem expression, precomputed pattern for
fast unification, and argument indices that become new subgoals. The
subgoal ordering lists non-dependent goals first to match the behavior
of `MetaM.apply`.
`BackwardRule.apply` unifies the goal type with the rule's pattern,
assigns the goal metavariable to the theorem application, and returns
new subgoals for unassigned arguments.
This PR makes the `FinitenessRelation` structure, which is helpful when
proving the finiteness of iterators, part of the public API. Previously,
it was marked internal and experimental.
This PR adds `num?` parameter to `mkPatternFromTheorem` to control how
many leading quantifiers are stripped when creating a pattern. This
enables matching theorems where only some quantifiers should be
converted to pattern variables.
For example, to match `mk_forall_and : (∀ x, P x) → (∀ x, Q x) → (∀ x, P
x ∧ Q x)` against a goal `∀ x, q x 0 ∧ q (f (f x)) y`, we use
`mkPatternFromTheorem ``mk_forall_and (some 5)` to create the pattern `∀
x, ?P x ∧ ?Q x`, keeping the outermost `∀` in the pattern rather than
converting it to a pattern variable.
This PR completes the new pattern matching and unification procedures
for the symbolic simulation framework using a two-phase approach.
**Phase 1 (Syntactic Matching):**
- Patterns use de Bruijn indices for expression variables and renamed
level params for universe variables
- Purely structural matching after reducible definitions are unfolded
- Universe levels treat `max`/`imax` as uninterpreted functions
- Proof arguments skipped via proof irrelevance
- Instance and binder constraints deferred to Phase 2
**Phase 2 (Pending Constraints):**
- Level constraints: structural equality with mvar assignment
- Instance constraints: `isDefEqI` (full `isDefEq` for TC synthesis)
- Expression constraints: `isDefEqS` with Miller pattern support
- Unassigned instance pattern variables synthesized via
`trySynthInstance`
**`isDefEqS` (Structural DefEq):**
- Miller pattern detection and assignment (`?m x y z := rhs` → `?m :=
fun x y z => rhs`)
- Scope checking via `maxFVar` to prevent out-of-scope assignments
- Optional zeta-delta reduction for let-declarations
- Proof irrelevance and instance delegation to `isDefEqI`
**Key optimizations:**
- `abstractFVars` skips metavariables and uses `maxFVar` for early
cutoff
- Per-pattern `ProofInstInfo` cache for fast argument classification
- Maximal sharing.
