This PR adds an API for building symbolic simulation engines and
verification
condition generators that leverage `grind`. The API wraps `Sym`
operations to
work with `grind`'s `Goal` type, enabling lightweight symbolic execution
while
carrying `grind` state for discharge steps.
New operations on `Goal`:
- `mkGoal`: create a `Goal` from an `MVarId`
- `introN`, `intros`: introduce binders
- `apply`: apply backward rules
- `simp`, `simpIgnoringNoProgress`: simplify using `Sym.Simp`
- `internalize`, `internalizeAll`: add hypotheses to the E-graph
- `grind`: attempt to close the goal using `grind`
- `assumption`: close by matching a hypothesis
A new test demonstrates the API on a stateful program with conditionals,
using `grind` to discharge arithmetic side conditions.
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 `intro` (and its variants) for `SymM`. These versions
do not use reduction or infer types, and ensure expressions are
maximally shared.
