Evaluation for fp-lean

One entry point, ./cli.py, which runs and/or plots an experiment. The logic is split across three modules:

• bench.py — runner primitives: domain types, tool dispatch, dataset walk, deterministic sampling, and the parallel runner.
• plot.py — pure analysis over a runresults directory: parses raw records and emits plots + LaTeX.
• lib.py — shared helpers (system specs, plotting/formatting utilities).

Running benchmarks

./cli.py <config-name> --run [--guid latest] [--nproblems N] [--runs 2]
         [--timeout-sec 600] [--memout-mb 16000] [--nproc 4]

Writes one jsonl file per datapoint into runresults/<guid>/. Default --guid is latest. An existing runresults/<guid>/ is wiped before a new run.

Each jsonl record contains raw fields only: stdout, stderr, returncode, wall_elapsed_ms, is_timeout, is_memout, is_exception. No derived fields — those are computed at plot time.

Alongside the records, --run also writes manifest.json (run parameters, git hash, timestamp) and config.tex / triple.tex (LaTeX macros for the paper).

Plotting

./cli.py <plot-name> --plot [--guid latest] [--outdir DIR]

Reads every jsonl in runresults/<guid>/, parses the raw data (computes is_unsat, is_sat, and the solver-specific elapsed_ms), and writes the plot plus cactus.tex to runresults/<guid>/plots/<plot-name>/ (unless --outdir).

--run and --plot may be combined to do both in one invocation.

Configurations and plots

Defined in cli.py:

• cactus — both solvers × --runs × a deterministically sampled subset of datasets/FP/ (seed = bench.SEED). Produces a cactus plot, geomean-averaged over runs.

Solvers

Two: bitwuzla (external binary) and fplean (lean-based). Paths in bench.py (BITWUZLA_PATH, FPLEAN_PATH).

Dataset

datasets/FP.tar.zst — extract with

tar --use-compress-program=unzstd -xf datasets/FP.tar.zst -C datasets/

before running. Expected layout: datasets/FP/<family>/<problem>.smt2.