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agent: phase2-tokei-001 — first auto-accepted win from the unattended loop
Ledger row: class 5 (algorithmic) on tokei, first-byte gate table for the per-byte token matchers in perform_multi_line_analysis. Speedup median 1.107, 95% CI [1.084, 1.131] vs the banked-wins baseline, workload: 221 MB / 4360 files, single rayon thread, pinned core. Manual audit gates (pipeline covers tests+golden+bench only): - Differential fuzz, 10k mutated inputs across 200 batched runs: 0 divergences after canonicalizing tokei's benign parallel-walker output ordering (present in pristine baseline; counts identical). Fuzzer added as scripts/diff-fuzz-tokei.py. - ASan run recorded in the case study (next commit). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01EcKPWQ3MQD4NdEHwar96u2
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[agent] The hunk line counts were off. Recomputing and resubmitting:
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[agent] The hunk line counts were off. Recomputing and resubmitting:
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[agent] Patch applied — `patch_id: 4e3da7e6bd1c`. Launching the gate+bench pipeline.
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[agent] Patch applied — `patch_id: 4e3da7e6bd1c`. Launching the gate+bench pipeline.
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[agent] Still running. Polling again.
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[agent] Still running. Polling again.
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[agent] **Verdict: `accepted`** — ledger row written for `phase2-tokei-001`.
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## Attempt summary
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| **Run ID** | `phase2-tokei-001` |
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| **Target / hotspot** | tokei — `LanguageType::parse_lines` 55.89% Ir / 62% branches / 44% branch-misses + `__memcmp_avx2_movbe` 9.37% Ir |
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| **Playbook class** | 5 (algorithmic — precomputed lookup table tier) |
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| **Patch** | `4e3da7e6bd1c`: 256-entry first-byte "interesting bytes" table in `SharedMatchers` (superset of all quote/comment token start+end first bytes, plus `\`), gating the five per-byte token matchers in `perform_multi_line_analysis`; `parse_context` still consulted on gated bytes so semantics are exactly preserved |
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| **Verdict** | **accepted** |
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| **Speedup (median)** | 1.1071× (~+10.7%) |
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| **Speedup 95% CI** | **[1.0836, 1.1310]** — CI lower bound +8.4%, clear of the 2% accept threshold |
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Measured on the tokei benchmark workload (`tokei --sort code corpora/tokei/input`), interleaved A/B vs pristine-rebuilt baseline, all equivalence gates green (upstream tests, golden replay, diff-fuzz, sanitizers — no FP/concurrency/unsafe surface touched, so no human-review routing triggered).
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The hypothesis predicted 5–12% median; the measured +10.7% landed inside that band. Notably, this also satisfies the outstanding Phase 2 exit criterion of at least one auto-accepted win from the unattended loop. One attempt was requested; stopping here.
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[result] turns=21 cost_usd=4.614901
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#!/usr/bin/env python3
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"""Differential fuzz for phase2-tokei-001: pristine vs candidate tokei
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must produce byte-identical output on mutated source inputs targeting
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the patched code path (quote/comment token scanning).
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Seeds: files from the pinned corpus (many languages). Mutations focus on
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quote/comment structure: inserting/deleting/duplicating quote chars,
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comment openers/closers, backslashes, and random bytes; plus boundary
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slices. Deterministic RNG for reproducibility.
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"""
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import random
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import subprocess
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import sys
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from pathlib import Path
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ROOT = Path("/home/user/peltier.io")
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BASE = ROOT / "targets/tokei/baseline/release/tokei"
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CAND = ROOT / "targets/tokei/candidate-4e3da7e6bd1c/release/tokei"
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CORPUS = ROOT / "corpora/tokei/input/copy1"
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WORK = Path(sys.argv[1]) if len(sys.argv) > 1 else Path("/tmp/difffuzz")
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ITERS = int(sys.argv[2]) if len(sys.argv) > 2 else 10000
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TOKENS = [
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b'"', b"'", b'`', b'"""', b"'''", b"/*", b"*/", b"//", b"#", b"--",
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b"<!--", b"-->", b"(*", b"*)", b"{-", b"-}", b"\\", b"\\\\", b'\\"',
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b"r#\"", b"\"#", b"=begin", b"=end", b"'''", b'f"""', b"%{", b"}",
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]
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def mutate(data: bytes, rng: random.Random) -> bytes:
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ops = rng.randrange(1, 6)
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b = bytearray(data)
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for _ in range(ops):
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if not b:
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b = bytearray(rng.choice(TOKENS))
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continue
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op = rng.randrange(5)
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pos = rng.randrange(len(b) + 1)
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if op == 0: # insert a token
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b[pos:pos] = rng.choice(TOKENS)
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elif op == 1 and len(b) > 2: # delete a slice
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end = min(len(b), pos + rng.randrange(1, 8))
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del b[pos:end]
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elif op == 2: # flip to a random byte
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if pos < len(b):
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b[pos] = rng.randrange(256)
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elif op == 3: # duplicate a slice
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end = min(len(b), pos + rng.randrange(1, 32))
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b[end:end] = b[pos:end]
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else: # newline injection (line-structure stress)
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b[pos:pos] = b"\n"
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return bytes(b)
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def canonicalize(payload: bytes) -> str:
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"""Parse tokei JSON and sort every list so benign output-order
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nondeterminism (parallel walker arrival order) doesn't count as a
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divergence; counts/stats still must match exactly."""
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import json
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def norm(o):
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if isinstance(o, dict):
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return {k: norm(v) for k, v in sorted(o.items())}
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if isinstance(o, list):
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return sorted((norm(v) for v in o), key=lambda x: json.dumps(x, sort_keys=True))
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return o
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return json.dumps(norm(json.loads(payload)), sort_keys=True)
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def run(binary: Path, d: Path) -> tuple[str, bytes, int]:
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r = subprocess.run(
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[str(binary), "--sort", "code", "--output", "json", str(d)],
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capture_output=True, env={"RAYON_NUM_THREADS": "1", "PATH": "/usr/bin:/bin"},
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)
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try:
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canon = canonicalize(r.stdout)
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except Exception as e: # unparseable output is always a divergence candidate
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canon = f"UNPARSEABLE:{e}:{r.stdout[:200]!r}"
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return canon + f"||rc={r.returncode}", r.stdout, r.returncode
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def main() -> int:
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rng = random.Random(0xB16B00B5)
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seeds = sorted(CORPUS.rglob("*"))
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seeds = [p for p in seeds if p.is_file() and p.stat().st_size < 200_000][:400]
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if not seeds:
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print("no seeds found", file=sys.stderr)
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return 2
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WORK.mkdir(parents=True, exist_ok=True)
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fdir = WORK / "case"
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divergences = 0
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done = 0
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# Batch: mutate BATCH files per tokei invocation (tokei scans a dir),
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# keeping each seed's extension so language detection stays realistic.
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BATCH = 50
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while done < ITERS:
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if fdir.exists():
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for f in fdir.iterdir():
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f.unlink()
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fdir.mkdir(exist_ok=True)
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for j in range(min(BATCH, ITERS - done)):
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seed = rng.choice(seeds)
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name = f"m{done + j}{seed.suffix or '.txt'}"
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(fdir / name).write_bytes(mutate(seed.read_bytes(), rng))
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a_canon, a_raw, a_rc = run(BASE, fdir)
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b_canon, b_raw, b_rc = run(CAND, fdir)
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if a_canon != b_canon:
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divergences += 1
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keep = WORK / f"divergence-{done}"
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fdir.rename(keep)
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(keep / "_baseline.out").write_bytes(a_raw + f"\nrc={a_rc}".encode())
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(keep / "_candidate.out").write_bytes(b_raw + f"\nrc={b_rc}".encode())
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print(f"DIVERGENCE at batch starting {done}; inputs+outputs kept in {keep}")
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done += BATCH
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if done % 1000 == 0:
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print(f"{done}/{ITERS} mutated files, {divergences} divergences", flush=True)
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print(f"done: {done} mutated files across {done // BATCH} runs, {divergences} divergences")
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return 1 if divergences else 0
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if __name__ == "__main__":
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sys.exit(main())
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