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 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 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 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.
This PR implements `instantiateRevBetaS`, which is similar to
`instantiateRevS` but beta-reduces nested applications whose function
becomes a lambda after substitution.
For example, if `e` contains a subterm `#0 a` and we apply the
substitution `#0 := fun x => x + 1`, then `instantiateRevBetaS` produces
`a + 1` instead of `(fun x => x + 1) a`.
This is useful when applying theorems. For example, when applying
`Exists.intro`:
```lean
Exists.intro.{u} {α : Sort u} {p : α → Prop} (w : α) (h : p w) : Exists p
```
to a goal of the form `∃ x : Nat, p x ∧ q x`, we create metavariables
`?w` and `?h`. With `instantiateRevBetaS`, the type of `?h` becomes `p
?w ∧ q ?w` instead of `(fun x => p x ∧ q x) ?w`.
This PR introduces a fast pattern matching and unification module for
the symbolic simulation framework (`Sym`). The design prioritizes
performance by using a two-phase approach:
**Phase 1 (Syntactic Matching)**
- Patterns use de Bruijn indices for expression variables and renamed
level params (`_uvar.0`, `_uvar.1`, ...) for universe variables
- Matching is purely structural after reducible definitions are unfolded
during preprocessing
- Universe levels treat `max` and `imax` as uninterpreted functions (no
AC reasoning)
- Binders and term metavariables are deferred to Phase 2
**Phase 2 (Pending Constraints)** [WIP]
- Handles binders (Miller patterns) and metavariable unification
- Converts remaining de Bruijn variables to metavariables
- Falls back to `isDefEq` when necessary
**Key design decisions:**
- Preprocessing unfolds reducible definitions and performs beta/zeta
reduction
- Kernel projections are expected to be folded as projection
applications before matching
- Assignment conflicts are deferred to pending rather than invoking
`isDefEq` inline
- `instantiateRevS` ensures maximal sharing of result expressions
**TODO:**
- Skip instance arguments during matching, synthesize later
- Skip proof arguments (proof irrelevance)
- Implement `processPending` for Phase 2 constraints
