"""Feature table and separation screen over a frozen training pool, no model calls. For every change of the pool's slice, check out its head, enumerate the candidate rows (touched functions at head plus the labelled fix site) and compute the four producers. Rows are labelled 1 at an accepted fix site, 0 on an ordinary push and null elsewhere on a positive. The screen then scores every engineered feature alone against the label (ROC-AUC) and reports the strongest feature per annotation. Repositories are the clusters: with few of them the screen is a direction, not a result, and the output says how many there are. PYTHONPATH=. .venv/bin/python benchmarks/measurements/2026-10-13-access-control-screen/table.py \\ benchmarks/valid/train/pool-train.toml --repos ~/ousast-results/valid/train/repos_hist.json --out """ from __future__ import annotations import argparse import json import subprocess import sys import tempfile import time import tomllib from collections import Counter from pathlib import Path from openultrasast.hunt import features from openultrasast.hunt.producers import compute_rows from openultrasast.hunt.runner import _full_checkout as full_checkout from openultrasast.hunt.table import FeatureTable from openultrasast.stats import separation def _git(root: Path, *args: str) -> str: return subprocess.run(["git", "-C", str(root), *args], check=True, capture_output=True, text=True).stdout def changes_of(pool: Path, slice_id: int) -> list[dict]: data = tomllib.loads(pool.read_text()) rows = next(value for value in data.values() if isinstance(value, list) and value and "changes" in value[0]) out = [] for row in rows: if int(row.get("slice", 1)) != slice_id: continue for change in row["changes"]: change = dict(change) change.setdefault("repo", row.get("repository") or row.get("repo") or row["id"]) change.setdefault("id", change["case_id"]) out.append(change) return out def rows_for(change: dict, clone: Path) -> tuple[list[dict], dict]: started = time.monotonic() with tempfile.TemporaryDirectory(prefix="ousast-table-") as temporary: root = Path(temporary) / "head" _git(clone, "worktree", "add", "--detach", str(root), change["head"]) try: if _git(root, "rev-parse", "HEAD").strip() != change["head"]: raise RuntimeError("head_mismatch") full_checkout(root) rows = compute_rows(root, change) finally: _git(clone, "worktree", "remove", "--force", str(root)) return rows, {"seconds": round(time.monotonic() - started, 2), "rows": len(rows)} def unread_rows(rows: list[dict], repos: dict[str, str]) -> int: """Rows whose file the source producer could not read although git holds a non-empty blob at head. An empty or missing file in the worktree is a checkout failure, not a feature; the first build read 150 such rows as feature-free (every positive of one repository among them) and nothing in the screen said so.""" count = 0 checked: dict[tuple[str, str, str], bool] = {} for row in rows: if row.get("provenance.source.reason") not in ("empty_source", "FileNotFoundError"): continue key = (row["repo"], row["head"], row["path"]) if key not in checked: clone = Path(repos[row["repo"]]).expanduser() size = subprocess.run( ["git", "-C", str(clone), "cat-file", "-s", f"{row['head']}:{row['path']}"], capture_output=True, text=True ) checked[key] = size.returncode == 0 and int(size.stdout.strip() or 0) > 0 count += checked[key] return count def main(argv: list[str] | None = None) -> int: parser = argparse.ArgumentParser(description=__doc__.split("\n\n")[0]) parser.add_argument("pool", type=Path) parser.add_argument("--repos", type=Path, required=True, help="JSON map repo -> local clone with history") parser.add_argument("--out", type=Path, required=True) parser.add_argument("--slice", type=int, default=1) args = parser.parse_args(argv) repos = json.loads(args.repos.read_text()) args.out.mkdir(parents=True, exist_ok=True) rows, log = [], [] for change in changes_of(args.pool, args.slice): clone = Path(repos[change["repo"]]).expanduser() try: produced, info = rows_for(change, clone) except Exception as error: # noqa: BLE001 (type only; a message can carry a path) info = {"failure": type(error).__name__} produced = [] rows.extend(produced) log.append({"id": change["id"], "repo": change["repo"], "kind": change["kind"], **info}) print(f"{change['id'][:16]} {change['kind']} {info}", flush=True) table = FeatureTable(rows) table.write_jsonl(args.out / "table.jsonl") # The instrument gate: a producer that failed on every row saw an unread tree, not a feature-free one. provenance = {name: sum(bool(row.get(f"provenance.{name}.ok")) for row in rows) for name in ("diff", "source", "semantic", "taxonomy")} print("producer rows ok:", provenance, "of", len(rows), flush=True) if rows and provenance["source"] == 0: print("the source producer read nothing: refusing to screen an unread tree", file=sys.stderr) return 2 unread = unread_rows(rows, repos) print("rows unread although git holds the file:", unread, flush=True) if unread: print("the checkout was incomplete for some rows: refusing to screen a partly unread tree", file=sys.stderr) return 2 (args.out / "log.json").write_text(json.dumps(log, indent=1)) frame = features.feature_frame(table) labelled = frame[frame["label"].isin([0, 1])] summary = { "producer_rows_ok": provenance, "table_digest": table.digest(), "rows": len(frame), "labelled": {"positive": int((labelled["label"] == 1).sum()), "negative": int((labelled["label"] == 0).sum())}, "repositories": int(labelled["repo"].nunique()), "changes": int(labelled["change_id"].nunique()), "positive_repositories": int(labelled[labelled["label"] == 1]["repo"].nunique()), "source_failures": dict(Counter(row.get("provenance.source.reason") for row in rows if not row.get("provenance.source.ok"))), "unread_rows": unread, # The recall ceiling of a diff-scoped candidate set: positive rows a label-blind enumeration would reach. "positive_rows_on_changed_line": int(labelled[(labelled["label"] == 1) & (labelled["diff.on_changed_line"] == 1)].shape[0]), "positive_rows_with_deletions": int(labelled[(labelled["label"] == 1) & (labelled["diff.deletion_count"].fillna(0) > 0)].shape[0]), } columns = [name for name in features.ENGINEERED if name in frame.columns] per_feature = separation(labelled, "label", columns) per_feature["annotation"] = [features.ENGINEERED[name][1] for name in per_feature["column"]] per_feature.to_csv(args.out / "separation.csv", index=False) features.screen(labelled).to_csv(args.out / "screen.csv", index=False) (args.out / "summary.json").write_text(json.dumps(summary, indent=1)) print(json.dumps(summary)) print(per_feature.sort_values("auc", key=lambda s: (s - 0.5).abs(), ascending=False).to_string(index=False)) return 0 if __name__ == "__main__": sys.exit(main())