b626c6d326
This PR adds support for simp/equational spec theorems in the SymM-based `mvcgen'` tactic, catching up with a feature that the original `mvcgen` has supported for a long time. Users can write `@[spec] theorem : get (m := StateT σ m) = fun s => pure (s, s) := rfl` instead of manually specifying equivalent Hoare triples. The equational form is more concise and natural for specs that simply unfold definitions. The universe level normalization (`normalizeLevelsExpr`) applied in `work` and the backward rule constructors is a workaround; ideally this should be integrated into `preprocessMVar`/`preprocessExpr` in the SymM framework so all users benefit. Changes: - Add `SpecTheoremKind` to distinguish triple vs simp specs in `SpecTheoremNew` - Add `mkSpecTheoremNewFromSimpDecl?` to create spec entries from equational lemmas, filtering no-op equations - Add `mkBackwardRuleFromSimpSpec` to build backward rules via `Eq.mpr`/`congrArg`, with instance synthesis, projection reduction, and `unfoldReducible` on the RHS - Migrate simp theorems from `SimpTheorems` database during `migrateSpecTheoremsDatabase` - Normalize universe levels so structural matching in `BackwardRule.apply` succeeds when `max u v` vs `max v u` arise from different code paths - Simplify `mkSpecContext` by removing the mock `simp` context construction - Use `mkBackwardRuleFromExpr` instead of `mkAuxLemma` for triple specs, since the proof may contain free variables from the goal context - Add `AddSubCancelSimp` benchmark case and test exercising the simp spec code path - Change `AddSubCancel` spec proofs from `mvcgen` to `mvcgen'` (dogfooding) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> |
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| .. | ||
| build | ||
| mergeSort | ||
| mvcgen | ||
| qsort | ||
| size | ||
| sym | ||
| .gitignore | ||
| accumulate_profile.py | ||
| arith_eval.ml | ||
| binarytrees.ghc-6.hs | ||
| binarytrees.ocaml-2.ml | ||
| binarytrees.st.hs | ||
| binarytrees.st.mlton-2.sml | ||
| binarytrees.st.sml | ||
| binarytrees.st.swift | ||
| binarytrees.swift | ||
| binarytrees5.ml | ||
| binarytrees5_multicore.ml | ||
| compile.sh | ||
| const_fold.hs | ||
| const_fold.ml | ||
| const_fold.sml | ||
| const_fold.swift | ||
| cross.yaml | ||
| dag_hassorry_issue.lean | ||
| dag_hassorry_issue.lean.args | ||
| dag_hassorry_issue.lean.expected.out | ||
| delayed_assign.lean | ||
| deriv.hs | ||
| deriv.ml | ||
| deriv.sml | ||
| deriv.swift | ||
| flake.lock | ||
| flake.nix | ||
| full-stdlib.exec.yaml | ||
| ghc-gc.py | ||
| lean-gc.py | ||
| Makefile | ||
| mlkit-gc.py | ||
| ocaml-gc.py | ||
| perf.py | ||
| qsort.hs | ||
| qsort.ml | ||
| qsort.sml | ||
| qsort.swift | ||
| rbmap.hs | ||
| rbmap.ml | ||
| rbmap.sml | ||
| rbmap.swift | ||
| rbmap2.lean | ||
| rbmap3.lean | ||
| rbmap500k.lean | ||
| rbmap_checkpoint.hs | ||
| rbmap_checkpoint.ml | ||
| rbmap_checkpoint.sml | ||
| rbmap_checkpoint.swift | ||
| rbmap_checkpoint2.lean | ||
| rbmap_checkpoint2.sml | ||
| rbmap_checkpoint_cpp_lean3.cpp | ||
| rbmap_checkpoint_cpp_std.cpp | ||
| rbmap_cpp_lean3.cpp | ||
| rbmap_cpp_std.cpp | ||
| README.md | ||
| report.py | ||
| run.sh | ||
| speedcenter.yaml | ||
| states35.lean | ||
| test_single.sh | ||
| unionfind_clean.lean | ||
Lean Benchmark Suites
This folder contains multiple small Lean programs for benchmarking used by two separate benchmark suites based on the temci benchmarking tool:
- The light-weight "Speedcenter" suite benchmarks the current build of Lean. It can be used for quick comparisons on the cmdline and powers the Lean Speedcenter website.
- The heavy-weight "Cross" suite benchmarks multiple Lean configurations and other functional compilers against each other and generates CSV and HTML reports from that. It was created for the paper "Counting Immutable Beans - Reference Counting Optimized for Purely Functional Programming" (IFL19).
Speedcenter Suite
Requirements:
- A local Lean build in
../../build/release. Build at least thebintarget. - temci. Using Nix, open a nix-shell in the project
root directory to add a compatible version to your PATH. Alternatively, try
pip3 install git+https://github.com/parttimenerd/temci.git.
To execute the suite and save the results in base.yaml, run (in this folder)
temci exec --config speedcenter.yaml --out base.yaml
Other interesting exec flags:
- use
--runs Nto modify the default number of 10 runs per benchmark - use
--included_blocks fastto excluded slow benchmarks like the stdlib benchmark. You can replacefastwith any benchmark name or label inspeedcenter.exec.yaml.
If you have multiple saved result files, you can compare them with
temci report --config speedcenter.yaml report1.yaml report2.yaml ...
Cross Suite
We recommend using Nix for building/obtaining all Lean variants and used compilers in a reproducible way. After installing Nix, running the benchmarks is as easy as
nix develop
make
This will record 50 runs for each benchmark configuration (this can be changed with runs in cross.yaml),
generate results in report_lean.csv and report_cross.csv, and print them to stdout in a tabulated format.
It will also generate HTML reports in report/ comparing the time-based benchmarks.
In order to reduce noise in the benchmarking data, you may instead want to try calling make inside a
temci shell:
temci short shell --sudo --preset usable --cpuset_active make
Using root powers, this will temporarily configure your machine similarly to the LLVM benchmarking recommendations and move all your other processes to a single CPU core.