feat(pair-corpus-honesty): reject improve rounds that regress any provenance profile on holdout

Task 6.3.

- improve/evolve.py: evaluate_profiles and profile_regressions score the
  holdout pair split per provenance profile every round; a drop in pair
  pass rate or Youden beyond --profile-tolerance rejects the round with
  reason profile_regression:<profile>; profiles under
  --min-holdout-pairs are reported, not gated; journal records both.
- cli improve: --pair-catalog, --no-pair-gate, --profile-tolerance,
  --min-holdout-pairs; a missing catalog fails loud instead of skipping
  the gate.

Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
This commit is contained in:
Marius Ciepluch
2026-09-05 10:45:43 +02:00
co-authored by Claude Fable 5.1
parent 25fa7aa7e1
commit 9e7aef6a6b
4 changed files with 217 additions and 3 deletions
+29
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@@ -130,6 +130,19 @@ def main(argv: list[str] | None = None) -> int:
"--ruleset-dir", type=Path, default=DEFAULT_RULESET_DIR, help="ruleset directory to improve (default: the bundled ruleset)"
)
improve.add_argument("--dry-run", action="store_true", help="run rounds against a throwaway ledger; never touch the target's ledger")
improve.add_argument(
"--pair-catalog",
type=Path,
default=DEFAULT_CATALOG,
help="pair catalog whose holdout split gates every round per provenance profile",
)
improve.add_argument(
"--no-pair-gate", action="store_true", help="skip the per-profile holdout clause (faster; not for accepted ledgers)"
)
improve.add_argument(
"--profile-tolerance", type=float, default=0.0, help="allowed per-profile drop in pair_correct/Youden before rejecting"
)
improve.add_argument("--min-holdout-pairs", type=int, default=5, help="profiles with fewer holdout pairs are reported, not gated")
pairs = subparsers.add_parser(
"pairs",
@@ -164,6 +177,9 @@ def main(argv: list[str] | None = None) -> int:
journal=args.journal,
ruleset_dir=args.ruleset_dir,
dry_run=args.dry_run,
pair_catalog=None if args.no_pair_gate else args.pair_catalog,
profile_tolerance=args.profile_tolerance,
min_holdout_pairs=args.min_holdout_pairs,
)
if args.command == "pairs":
return _pairs(
@@ -718,9 +734,17 @@ def _improve(
journal: Path | None,
ruleset_dir: Path,
dry_run: bool,
pair_catalog: Path | None = None,
profile_tolerance: float = 0.0,
min_holdout_pairs: int = 5,
) -> int:
if not manifest_path.exists() or not manifest_path.is_file():
raise SystemExit(f"benchmark manifest is not a file: {manifest_path}")
pair_cases: tuple[object, ...] = ()
if pair_catalog is not None:
if not pair_catalog.is_file():
raise SystemExit(f"pair catalog is not a file: {pair_catalog} (pass --no-pair-gate to skip the per-profile holdout clause)")
pair_cases = select_split(load_pair_catalog(pair_catalog), "holdout")
manifest = load_benchmark_manifest(manifest_path)
target = resolve_benchmark_source(manifest_path, manifest)
policy = load_policy()
@@ -746,6 +770,9 @@ def _improve(
max_rounds=max_rounds,
recall_floor=recall_floor,
fp_ceiling=fp_ceiling,
pair_cases=pair_cases,
profile_tolerance=profile_tolerance,
min_holdout_pairs=min_holdout_pairs,
)
_print_improve_outcomes(outcomes, manifest_path, target, ledger_path, dry_run=dry_run)
return 0
@@ -793,6 +820,8 @@ def _print_improve_outcomes(outcomes: list[RoundOutcome], manifest_path: Path, t
f"fp {outcome.fp_before:.2%}->{outcome.fp_after:.2%} "
f"score {outcome.score_before}->{outcome.score_after} | edits: {edits}"
)
if outcome.profile_regressions or outcome.profiles_under_minimum:
print(f" profiles: regressed={outcome.profile_regressions or '-'} under_minimum={outcome.profiles_under_minimum or '-'}")
print(f"rounds={len(outcomes)} accepted={len(accepted)}")
if dry_run:
print("dry_run=true (no ledger written)")
+96 -3
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@@ -14,7 +14,7 @@ feasibility constraint that is never folded into the reward.
from __future__ import annotations
import tempfile
from collections.abc import Mapping
from collections.abc import Mapping, Sequence
from dataclasses import dataclass, field
from pathlib import Path
@@ -44,6 +44,62 @@ class RoundOutcome:
score_after: int = 0
matched_before: int = 0
matched_after: int = 0
profile_regressions: list[str] = field(default_factory=list)
profiles_under_minimum: list[str] = field(default_factory=list)
per_profile_before: dict[str, dict[str, float]] = field(default_factory=dict)
per_profile_after: dict[str, dict[str, float]] = field(default_factory=dict)
MAX_PROFILES = 4
def evaluate_profiles(
pair_cases: Sequence[object],
rules: tuple[PatternRule, ...],
) -> dict[str, dict[str, float]]:
"""Pair-corpus metrics per provenance profile under ``rules`` (holdout split, no inventory sidecar)."""
from ..pairs import PairCase, evaluate_catalog
cases = [case for case in pair_cases if isinstance(case, PairCase)]
if not cases:
return {}
result = evaluate_catalog(cases, ruleset=rules, inventory_sidecar=False)
return {
profile: {
"pairs": float(metrics.pairs),
"pair_correct": float(metrics.pair_correct),
"pair_pass_rate": metrics.pair_pass_rate,
"youden": metrics.youden,
}
for profile, metrics in result.per_profile.items()
}
def profile_regressions(
before: dict[str, dict[str, float]],
after: dict[str, dict[str, float]],
*,
tolerance: float = 0.0,
min_pairs: int = 5,
) -> tuple[list[str], list[str]]:
"""(regressed profiles, profiles under the minimum).
A profile regresses when its pair pass rate or Youden drops by more than ``tolerance``
(both are rates in [-1, 1], so one tolerance applies to both).
"""
regressed: list[str] = []
small: list[str] = []
for profile in sorted(set(before) | set(after)):
old = before.get(profile, {"pairs": 0.0, "pair_correct": 0.0, "pair_pass_rate": 0.0, "youden": 0.0})
new = after.get(profile, old)
if old["pairs"] < min_pairs:
small.append(profile)
continue
old_rate = old.get("pair_pass_rate", old["pair_correct"] / old["pairs"] if old["pairs"] else 0.0)
new_rate = new.get("pair_pass_rate", new["pair_correct"] / new["pairs"] if new["pairs"] else 0.0)
if new_rate < old_rate - tolerance or new["youden"] < old["youden"] - tolerance:
regressed.append(profile)
return regressed, small
def build_rule_signals(result: BenchmarkResult) -> list[dict[str, object]]:
@@ -90,6 +146,9 @@ def run_round(
policy: dict[str, CwePolicy] | None = None,
recall_floor: float = 0.9,
fp_ceiling: float = 0.1,
pair_cases: Sequence[object] | None = None,
profile_tolerance: float = 0.0,
min_holdout_pairs: int = 5,
) -> RoundOutcome:
policy = policy if policy is not None else load_policy()
rounds = load_journal(journal_path)
@@ -128,13 +187,37 @@ def run_round(
accepted = (
after.recall >= recall_floor and after.fp_rate < fp_ceiling and after.score >= before.score and after.matched >= before.matched
)
profiles_before: dict[str, dict[str, float]] = {}
profiles_after: dict[str, dict[str, float]] = {}
regressed: list[str] = []
small: list[str] = []
if accepted and pair_cases:
# pair-corpus-honesty Req 7.2: a change may not help one provenance profile by hurting another.
profiles_before = evaluate_profiles(pair_cases, before_rules)
profiles_after = evaluate_profiles(pair_cases, after_rules)
if len(profiles_before) > MAX_PROFILES:
raise ValueError(f"at most {MAX_PROFILES} provenance profiles are supported; got {sorted(profiles_before)}")
regressed, small = profile_regressions(profiles_before, profiles_after, tolerance=profile_tolerance, min_pairs=min_holdout_pairs)
if regressed:
accepted = False
if accepted:
write_rule_ledger(ledger_path, candidate)
reason = "accepted"
elif regressed:
reason = f"profile_regression:{regressed[0]}" # every regressed profile is listed in profile_regressions
else:
reason = "reverted" # ledger_path untouched -> byte-for-byte revert
_record(journal_path, round_index, edits, reason, before, after)
return _outcome(round_index, accepted=accepted, reason=reason, edits=edits, before=before, after=after)
_record(journal_path, round_index, edits, "accepted" if accepted else "reverted", before, after, reason, regressed, small)
outcome = _outcome(round_index, accepted=accepted, reason=reason, edits=edits, before=before, after=after)
return RoundOutcome(
**{
**outcome.__dict__,
"profile_regressions": regressed,
"profiles_under_minimum": small,
"per_profile_before": profiles_before,
"per_profile_after": profiles_after,
}
)
def run_improvement(
@@ -148,6 +231,9 @@ def run_improvement(
max_rounds: int = 5,
recall_floor: float = 0.9,
fp_ceiling: float = 0.1,
pair_cases: Sequence[object] | None = None,
profile_tolerance: float = 0.0,
min_holdout_pairs: int = 5,
) -> list[RoundOutcome]:
"""Run improvement rounds until convergence (no new proposals) or ``max_rounds``."""
outcomes: list[RoundOutcome] = []
@@ -161,6 +247,9 @@ def run_improvement(
policy=policy,
recall_floor=recall_floor,
fp_ceiling=fp_ceiling,
pair_cases=pair_cases,
profile_tolerance=profile_tolerance,
min_holdout_pairs=min_holdout_pairs,
)
outcomes.append(outcome)
if outcome.reason == "no_proposals":
@@ -246,6 +335,8 @@ def _record(
before: _Eval,
after: _Eval,
reason: str = "",
profile_regressions: list[str] | None = None,
profiles_under_minimum: list[str] | None = None,
) -> None:
append_round(
journal_path,
@@ -253,6 +344,8 @@ def _record(
"round": round_index,
"outcome": outcome,
"reason": reason or outcome,
"profile_regressions": list(profile_regressions or []),
"profiles_under_minimum": list(profiles_under_minimum or []),
"edits": [
{"key": e.key(), "lever": e.lever, "rule_id": e.rule_id, "from": e.from_status, "to": e.to_status, "rationale": e.rationale}
for e in edits
+9
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@@ -58,3 +58,12 @@ def test_improve_rejects_missing_manifest(tmp_path: Path) -> None:
with pytest.raises(SystemExit):
main(["improve", str(tmp_path / "nope.toml")])
def test_improve_fails_loud_when_pair_catalog_is_missing(tmp_path: Path) -> None:
import pytest
_, ruleset_dir = _scaffold(tmp_path)
manifest = tmp_path / "bench.toml"
with pytest.raises(SystemExit, match="pair catalog"):
main(["improve", str(manifest), "--ruleset-dir", str(ruleset_dir), "--dry-run", "--pair-catalog", str(tmp_path / "missing.toml")])
+83
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@@ -168,3 +168,86 @@ def test_build_rule_signals_separates_miss_and_fp() -> None:
signals = build_rule_signals(result)
assert {s["signal"] for s in signals} == {"miss", "fp"}
assert {s["rule_id"] for s in signals} == {"sqli", "noisy"}
# ---- pair-corpus-honesty: per-profile holdout clause (Req 7.2-7.4) ----------
def _pair(tmp_path: Path, name: str, vuln_src: str, fixed_src: str, rule_id: str, sink: str, *, provenance: str):
from openultrasast.benchmark import ExpectedFinding
from openultrasast.pairs import PairCase
vuln = tmp_path / f"{name}-vuln.py"
fixed = tmp_path / f"{name}-fixed.py"
vuln.write_text(vuln_src)
fixed.write_text(fixed_src)
return PairCase(
name=name,
slice="github",
language="python",
origin="test",
vuln_file=vuln,
fixed_file=fixed,
relpath="app.py",
expected=(
ExpectedFinding(
cwe="CWE-95",
vulnerability_class="x",
path="app.py",
evidence="",
rule_id=rule_id,
sink=sink,
mechanism="source_reaches_sink",
),
),
min_recall=1.0,
fix_policy="silent",
provenance=provenance,
split="holdout",
)
def test_round_rejects_when_a_profile_regresses_on_holdout(tmp_path: Path) -> None:
repo = tmp_path / "repo"
repo.mkdir()
(repo / "app.py").write_text("def f(x):\n return eval(x)\ndef g():\n print('hello')\n")
ruleset_dir = _ruleset_dir(tmp_path, [_rule("good-eval", r"\beval\s*\("), _rule("noisy-print", r"\bprint\s*\(")])
_, manifest = _manifest(tmp_path, _expected("good-eval"))
ledger = tmp_path / "rule_policy.json"
journal = tmp_path / "journal.json"
# The agent profile's holdout pair is only detected by the rule the round wants to shadow.
agent_pairs = [
_pair(tmp_path, f"agent{i}", "def h(y):\n print(y)\n", "def h(y):\n return y\n", "noisy-print", "print", provenance="agent")
for i in range(5)
]
outcome = run_round(repo, manifest, ledger_path=ledger, journal_path=journal, ruleset_dir=ruleset_dir, pair_cases=agent_pairs)
assert not outcome.accepted
assert outcome.reason == "profile_regression:agent"
assert outcome.profile_regressions == ["agent"]
assert outcome.per_profile_before["agent"]["pair_correct"] == 5.0 and outcome.per_profile_after["agent"]["pair_correct"] == 0.0
assert not ledger.exists()
assert json.loads(journal.read_text())[0]["profile_regressions"] == ["agent"]
def test_round_accepts_when_profiles_hold_and_reports_small_profiles(tmp_path: Path) -> None:
repo = tmp_path / "repo"
repo.mkdir()
(repo / "app.py").write_text("def f(x):\n return eval(x)\ndef g():\n print('hello')\n")
ruleset_dir = _ruleset_dir(tmp_path, [_rule("good-eval", r"\beval\s*\("), _rule("noisy-print", r"\bprint\s*\(")])
_, manifest = _manifest(tmp_path, _expected("good-eval"))
ledger = tmp_path / "rule_policy.json"
journal = tmp_path / "journal.json"
human_pairs = [
_pair(tmp_path, f"h{i}", "def h(y):\n return eval(y)\n", "def h(y):\n return y\n", "good-eval", "eval", provenance="human")
for i in range(5)
]
tiny_agent = [
_pair(tmp_path, "a0", "def h(y):\n print(y)\n", "def h(y):\n return y\n", "noisy-print", "print", provenance="agent")
]
outcome = run_round(
repo, manifest, ledger_path=ledger, journal_path=journal, ruleset_dir=ruleset_dir, pair_cases=human_pairs + tiny_agent
)
assert outcome.accepted and outcome.reason == "accepted"
assert outcome.profile_regressions == []
assert outcome.profiles_under_minimum == ["agent"] # one pair: reported, not gated
assert ledger.exists()