[AZ-432] [AZ-433] [AZ-434] [AZ-435] Add NFT-RES-01..04 resilience scenarios

Batch 86: 4 NFT-RES blackbox scenarios + 4 helper evaluators + 74 unit
tests + directory-layout registration.

* AZ-432 NFT-RES-01: 30 s IMU-only fallback drift bound (AC-3.5 + AC-NEW-7);
  two sub-cases (no_imu ≤100m, good_imu_combined_factor ≤50m).
* AZ-433 NFT-RES-02: companion mid-flight reboot (AC-5.2 + AC-5.3); resume
  ≤30s + first-emission accuracy ≤100m.
* AZ-434 NFT-RES-03: 100-iteration Monte Carlo envelope (AC-NEW-4);
  iteration-count + master-seed determinism + envelope ratio ≥0.95.
  Canonical-param by default; E2E_NFT_RES_03_FULL_MATRIX=1 unlocks matrix.
* AZ-435 NFT-RES-04: 35s blackout+spoof escalation ladder (AC-NEW-8);
  AC-1 (cov-2d→fix-degrade ≤500ms) + AC-2 (failsafe→999+STATUSTEXT
  ≤500ms) + AC-ORDER (strict ordering).

Verdict: PASS_WITH_WARNINGS (0 Critical, 0 High, 0 Medium, 5 Low).
F5 documents intentional threshold duplication with blackout_spoof
evaluator (prevents contract drift between FT-N-04 and NFT-RES-04).

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
Oleksandr Bezdieniezhnykh
2026-05-17 17:09:04 +03:00
parent 23640a784f
commit 330893be5c
15 changed files with 3325 additions and 0 deletions
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"""NFT-RES-03 — 100-iteration Monte Carlo statistical envelope (AZ-434 / AC-NEW-4).
Tier-1 OR Tier-2. The runner orchestrates 100 Derkachi replays with
seeded perturbations (gain noise, IMU bias, frame-drop, outlier
injection) and supplies this scenario with a captured fixture
containing per-iteration per-frame ``(error_m, cov_semi_major_m)``
pairs. The scenario validates:
* AC-1 — iteration_count ≥ 100.
* AC-2 — same master_seed yields bit-identical iteration outcomes
(verified by re-evaluating the same fixture twice and comparing
``determinism_fingerprint``).
* AC-3 — global aggregate envelope:
``count(error_m ≤ 1.96 × cov_semi_major_m) / total ≥ 0.95``.
* AC-4 — parameterization: SHOULD run only one canonical
parameterization per CI invocation by default; full-matrix mode
gated behind ``E2E_NFT_RES_03_FULL_MATRIX=1``. The scenario uses
``fc_adapter`` + ``vio_strategy`` fixtures so the harness param
matrix decides which combinations to run.
Production dependency surfaced to AZ-595: the
``E2E_NFT_RES_03_FIXTURE`` env var names a JSON file with shape:
{
"master_seed": <int>,
"iterations": [
{
"iteration_id": "iter-001",
"iteration_seed": <int>,
"samples": [{"error_m": <f>, "cov_semi_major_m": <f>}, ...]
},
...
]
}
The harness MAY emit the fixture with a single canonical parameterization
per CI invocation by default — ``E2E_NFT_RES_03_FULL_MATRIX=1``
unlocks the full 100 × N_params expansion.
"""
from __future__ import annotations
import json
import os
from pathlib import Path
import pytest
from runner.helpers import monte_carlo_envelope_evaluator as mce
NFT_RES_03_FIXTURE_ENV_VAR = "E2E_NFT_RES_03_FIXTURE"
NFT_RES_03_DEFAULT_FIXTURE_NAME = "nft_res_03_monte_carlo.json"
NFT_RES_03_FULL_MATRIX_ENV_VAR = "E2E_NFT_RES_03_FULL_MATRIX"
NFT_RES_03_CANONICAL_FC = "ardupilot"
NFT_RES_03_CANONICAL_VIO = "okvis2"
@pytest.mark.scenario_id("nft-res-03")
@pytest.mark.traces_to("AC-NEW-4,AC-1,AC-2,AC-3,AC-4")
def test_nft_res_03_monte_carlo(
fc_adapter: str,
vio_strategy: str,
evidence_dir, # type: ignore[no-untyped-def]
run_id: str,
nfr_recorder, # type: ignore[no-untyped-def]
sitl_replay_ready: bool,
) -> None:
"""AC-1 (iteration count) + AC-2 (determinism) + AC-3 (envelope) + AC-4 (param)."""
if not _full_matrix_enabled() and (
fc_adapter != NFT_RES_03_CANONICAL_FC
or vio_strategy != NFT_RES_03_CANONICAL_VIO
):
pytest.skip(
f"NFT-RES-03 AC-4: by default runs only canonical "
f"({NFT_RES_03_CANONICAL_FC}, {NFT_RES_03_CANONICAL_VIO}); "
f"set {NFT_RES_03_FULL_MATRIX_ENV_VAR}=1 to enable the "
f"100 × N_params full-matrix expansion."
)
if not sitl_replay_ready:
pytest.skip(
"NFT-RES-03 requires `E2E_SITL_REPLAY_DIR` to point at a "
"prepared SITL replay fixture (AZ-595) carrying N≥100 "
"Monte Carlo iterations. Pure-logic AC-1 + AC-2 + AC-3 "
"covered by "
"e2e/_unit_tests/helpers/test_monte_carlo_envelope_evaluator.py."
)
fixture_path = _resolve_fixture_path()
if not fixture_path.is_file():
pytest.fail(
f"NFT-RES-03: fixture not found at {fixture_path}. "
f"`{NFT_RES_03_FIXTURE_ENV_VAR}` env var must point at a JSON "
"file with the schema documented in the scenario docstring. "
"Production dependency: AZ-595."
)
payload = json.loads(fixture_path.read_text())
master_seed, iterations = _parse_payload(payload, fixture_path)
report1 = mce.evaluate(iterations, master_seed=master_seed)
report2 = mce.evaluate(iterations, master_seed=master_seed)
fingerprint = mce.determinism_fingerprint(report1)
fingerprint2 = mce.determinism_fingerprint(report2)
out_base = (
evidence_dir
/ "nft-res-03"
/ f"{fc_adapter}-{vio_strategy}"
)
mce.write_csv_evidence(out_base.with_suffix(".csv"), report1)
mce.write_per_iteration_csv(
out_base.with_name(out_base.name + "-per-iter").with_suffix(".csv"),
report1,
)
nfr_recorder.record_metric(
"nft_res_03.iteration_count", float(report1.iteration_count), ac_id="AC-1"
)
nfr_recorder.record_metric(
"nft_res_03.total_samples", float(report1.total_samples)
)
if report1.envelope_ratio is not None:
nfr_recorder.record_metric(
"nft_res_03.envelope_ratio", float(report1.envelope_ratio), ac_id="AC-3"
)
nfr_recorder.record_metric(
"nft_res_03.master_seed", float(report1.master_seed)
)
assert report1.passes_iteration_count, (
f"AC-1: iteration_count={report1.iteration_count} < required "
f"{report1.min_iteration_count}"
)
assert fingerprint == fingerprint2, (
f"AC-2: determinism fingerprint differs across two evaluations of the "
f"same fixture: {fingerprint} vs {fingerprint2}"
)
assert report1.passes_envelope, (
f"AC-3: envelope ratio = {report1.envelope_ratio} < budget "
f"{report1.envelope_ratio_budget} "
f"(covered={report1.covered_samples}/{report1.total_samples})"
)
def _full_matrix_enabled() -> bool:
return os.environ.get(NFT_RES_03_FULL_MATRIX_ENV_VAR, "").strip() in {"1", "true", "yes"}
def _resolve_fixture_path() -> Path:
raw = os.environ.get(NFT_RES_03_FIXTURE_ENV_VAR, "").strip()
from runner.helpers import sitl_observer
root = sitl_observer.replay_dir()
if not raw:
if root is None:
return Path(f"<{NFT_RES_03_FIXTURE_ENV_VAR}-unset>")
return root / NFT_RES_03_DEFAULT_FIXTURE_NAME
path = Path(raw)
if not path.is_absolute() and root is not None:
path = root / path
return path
def _parse_payload(
payload: object, fixture_path: Path
) -> tuple[int, list[mce.IterationOutcome]]:
if not isinstance(payload, dict):
pytest.fail(
f"NFT-RES-03: fixture {fixture_path} must be a JSON object; "
f"got top-level type={type(payload).__name__}"
)
try:
master_seed = int(payload["master_seed"])
except (KeyError, TypeError, ValueError) as exc:
pytest.fail(
f"NFT-RES-03: fixture {fixture_path} missing/invalid "
f"'master_seed': {exc}"
)
raw_iters = payload.get("iterations")
if not isinstance(raw_iters, list) or not raw_iters:
pytest.fail(
f"NFT-RES-03: fixture {fixture_path} 'iterations' must be a "
f"non-empty list"
)
parsed: list[mce.IterationOutcome] = []
for idx, entry in enumerate(raw_iters):
if not isinstance(entry, dict):
pytest.fail(
f"NFT-RES-03: iterations[{idx}] in {fixture_path} must be "
f"an object; got {type(entry).__name__}"
)
iter_id = str(entry.get("iteration_id") or f"iter-{idx:03d}")
try:
seed = int(entry["iteration_seed"])
except (KeyError, TypeError, ValueError) as exc:
pytest.fail(
f"NFT-RES-03: iterations[{idx}].iteration_seed in "
f"{fixture_path} must be int: {exc}"
)
raw_samples = entry.get("samples")
if not isinstance(raw_samples, list):
pytest.fail(
f"NFT-RES-03: iterations[{idx}].samples in {fixture_path} "
f"must be a list of objects"
)
samples: list[mce.FrameSample] = []
for j, s in enumerate(raw_samples):
if not isinstance(s, dict):
pytest.fail(
f"NFT-RES-03: iterations[{idx}].samples[{j}] in "
f"{fixture_path} must be an object"
)
try:
samples.append(
mce.FrameSample(
error_m=float(s["error_m"]),
cov_semi_major_m=float(s["cov_semi_major_m"]),
)
)
except (KeyError, TypeError, ValueError) as exc:
pytest.fail(
f"NFT-RES-03: iterations[{idx}].samples[{j}] in "
f"{fixture_path} shape invalid: {exc}"
)
parsed.append(
mce.IterationOutcome(
iteration_id=iter_id,
iteration_seed=seed,
samples=tuple(samples),
)
)
return master_seed, parsed