# Determinism Benchmark (cross-scanner) — Stable (2025-11)

Source: advisory “23-Nov-2025 - Benchmarking Determinism in Vulnerability Scoring”. This doc captures the runnable harness pattern and expected outputs for task BENCH-DETERMINISM-401-057.

## Goal
- Measure determinism rate, order-invariance, and CVSS delta σ across scanners when fed identical SBOM+VEX inputs with frozen feeds.

## Minimal harness (Python excerpt)
```python
# run_bench.py (excerpt) — deterministic JSON hashing
def canon(obj):
    return json.dumps(obj, sort_keys=True, separators=(',', ':')).encode()

def shas(b):
    return hashlib.sha256(b).hexdigest()

for sbom, vex in zip(SBOMS, VEXES):
    for scanner, tmpl in SCANNERS.items():
        for mode in ("canonical", "shuffled"):
            for i in range(10):
                if mode == "shuffled":
                    sb, vx = shuffle(sbom), shuffle(vex)
                out = run(tmpl.format(sbom=sb, vex=vx))
                norm = normalize(out)  # purl, vuln id, base_cvss, effective
                blob = canon({"scanner": scanner, "sbom": sbom,
                              "vex": vex, "findings": norm})
                results.append({
                    "hash": shas(blob), "mode": mode,
                    "run": i, "scanner": scanner, "sbom": sbom
                })
```

## Inputs
- 3–5 SBOMs (CycloneDX 1.6 / SPDX 3.0.1) + matching VEX docs covering affected/not_affected/fixed.
- Feeds bundle: vendor DBs (NVD, GHSA, OVAL) hashed and frozen.
- Policy: single normalization profile (e.g., prefer vendor scores, CVSS v3.1).
- Reachability dataset (optional combined run): `tests/reachability/samples-public` corpus; graphs produced via `stella graph lift` for each language sample; runtime traces optional.

## Metrics
- Determinism rate = identical_hash_runs / total_runs (20 per scanner/SBOM).
- Order-invariance failures (# distinct hashes between canonical vs shuffled).
- CVSS delta σ vs reference; VEX stability (σ_after ≤ σ_before).

## Deliverables
- Harness at `src/Bench/StellaOps.Bench/Determinism` (offline-friendly mock scanner included).
- `results/*.csv` with per-run hashes plus `summary.json` determinism rate.
- `results/inputs.sha256` listing SBOM, VEX, and config hashes (deterministic ordering).
- `bench/reachability/dataset.sha256` listing reachability corpus inputs (graphs, runtime traces) when running combined bench.
- CI target `bench:determinism` producing determinism% and σ per scanner; optional `bench:reachability` to recompute graph hash and runtime hit stability.

## Links
- Source advisory: `docs/product-advisories/23-Nov-2025 - Benchmarking Determinism in Vulnerability Scoring.md`
- Sprint task: BENCH-DETERMINISM-401-057 (SPRINT_0401_0001_0001_reachability_evidence_chain.md)

---

## How to run (local)

```sh
cd src/Bench/StellaOps.Bench/Determinism

# Run determinism bench (uses built-in mock scanner by default; defaults to 10 runs)
python run_bench.py --sboms inputs/sboms/*.json --vex inputs/vex/*.json \
  --config configs/scanners.json --shuffle --output results

# Reachability dataset (optional)
python run_reachability.py --graphs ../reachability/graphs/*.json \
  --runtime ../reachability/runtime/*.ndjson.gz --output results-reach.csv
```

Outputs are written to `results.csv` (determinism) and `results-reach.csv` (reachability stability) plus SHA manifests.

## How to run (CI)

- Workflow `.gitea/workflows/bench-determinism.yml` calls `scripts/bench/determinism-run.sh`, which runs the harness with the bundled mock scanner and uploads `out/bench-determinism/**` (results, manifests, summary). Set `DET_EXTRA_INPUTS` to include frozen feed bundles in `inputs.sha256`.
- Optional `bench:reachability` target (future) will replay reachability corpus, recompute graph hashes, and compare against expected `dataset.sha256`.
- CI fails when `determinism_rate` < `BENCH_DETERMINISM_THRESHOLD` (defaults to 0.95; set via env in the workflow).

## Offline/air-gap workflow

1. Place feeds bundle, SBOMs, VEX, and reachability corpus under `offline/inputs/` with matching `inputs.sha256` and `dataset.sha256`.
2. Run `./offline_run.sh --inputs offline/inputs --outputs offline/results` to execute both benches without network.
3. Verify hashes: `sha256sum -c offline/inputs/inputs.sha256` and `sha256sum -c offline/inputs/dataset.sha256`.
4. Store outputs plus manifests in Offline Kit; include DSSE envelope if signing is enabled (`./sign_results.sh`).

## Notes
- Keep file ordering deterministic (lexicographic) when generating manifests.
- Do not pull live feeds during bench runs; use frozen bundles only.
- For reachability runs, require symbol manifest availability; otherwise mark missing symbols and fail the run.