| name | dev-testing |
| description | MUST USE for testing, QA, regression protection, and release verification — unit, integration, API, contract, Playwright E2E, CI, security-scan, coverage, and TDD strategy. Triggers: write tests, regression test, Playwright, E2E, contract test, coverage, CI flake, TDD, test, testing, QA, 테스트, 회귀 테스트, 품질 게이트. |
| metadata | {"short-description":"Testing and QA router: strategy, harness choice, CI gates, TDD, and coverage.","keywords":"test, testing, TDD, coverage, regression, e2e, playwright, contract test, CI, property-based, mutation","last-verified":"2026-07-02"} |
Testing & QA
Balance: ~40% Backend/API, ~40% Frontend/E2E (Playwright), ~20% Cross-cutting (CI, Security, TDD, Coverage) -- directional guidance, not a hard ratio.
Scope: test harnesses, fixtures, mock policy, runners, Playwright, CI gates, coverage. Root-cause analysis and debugging playbooks → dev-debugging.
This skill activates by change surface when work needs verification depth, regression coverage, or a reproducible test harness.
C0/C1 work (small local patches): See dev §0.0 Work Classifier + §0.1 Patch Fast-Path before reading references.
Modular References
| File | When to Read | What It Covers |
|---|
references/core/crud-test-matrix.md | When choosing verification depth for a classified task, or testing a CRUD slice | Risk-tier minimums, per-operation negatives, UI smoke rule |
references/edge-first-testing.md | New unit/service/integration tests for features (skip for regression/contract tests) | Edge-first principle, test order by change type, 11-class edge matrix |
references/backend-testing.md | Backend/API testing | Supertest patterns, DB fixtures, auth mocking |
references/ci-pipeline.md | CI configuration | GitHub Actions, gates, caching, parallelism |
references/load-testing.md | Performance/load testing, C3+ production readiness | k6/Locust, test types, measure→profile→verify, CI gates |
references/ml-evaluation.md | ML model/LLM evaluation, quality gates | LLM-as-judge, RAGAS, DeepEval, CI eval gate, regression detection. CI eval gates are dataset-versioned + regression-based: pin prompts/models/retrieval config, preserve traces, calibrate judges on golden examples, fail only on meaningful regressions or safety failures |
When tests depend on current external API behavior, provider docs, CI service
behavior, test-environment versions, dependency audit evidence, or recorded
mock/fixture sources, read the active search skill and follow its
source-fetch and evidence-status rules.
1. Test Strategy
1.1 Models
| Model | Best For | Emphasis |
|---|
| Test Pyramid | monoliths, libraries | speed, isolation |
| Testing Trophy | modern web apps, REST backends | confidence-to-cost |
| Test Honeycomb | microservices, async systems | boundary verification |
1.2 Recommended Trophy Distribution
| Layer | Default Share | Typical Tools |
|---|
| Static analysis | base layer | tsc, ESLint, mypy, Ruff |
| Unit | ~25% | Vitest, Jest, pytest |
| Integration | ~50% | Supertest, httpx, Testcontainers |
| Contract | ~10% | Pact, OpenAPI validators, Schemathesis |
| E2E | ~10% | Playwright |
| Manual / exploratory | ~5% | human review |
1.3 Risk-First Priorities
- auth / session / permission boundaries
- money movement, quota, credits
- data mutation and irreversible actions
- file upload / parsing / external webhooks
- shared API contracts used by frontend clients
- error paths, retries, rollback behavior
1.4 Harness Selector
| Problem | Primary Harness | Avoid |
|---|
| pure business rule | unit / service test | browser test |
| route + middleware + serialization | API integration test | mocking the route itself |
| DB query / migration / transaction | real DB integration test | fake repository for SQL correctness |
| frontend consuming backend JSON | contract test | manual-only verification |
| rendered critical flow | Playwright smoke | asserting internal React state |
| rendered artifact (visual correctness) | render-grounding loop (dev-pabcd C-RENDER-GROUNDING-01) | static parse / tsc alone |
1.5 General Rules
- Write tests for new features, bug fixes, refactors, and behavior changes.
- Prefer one behavioral concern per test.
- Use factories / builders for setup; avoid repeated inline blobs.
- A fast real dependency beats a mock. A mock beats an untested branch.
- If the failure is mysterious, delegate methodology to
dev-debugging, then return here for the regression harness.
- STRICT (TEST-ANTI-FLAKE-01): A time-based flake is a bug. Do not use sleep-based synchronization, retry-as-fix, or green-on-retry acceptance without a deterministic cause and harness correction.
- Verification depth follows
dev §3 DEV-VERIFY-FLOOR-01; CRUD per-operation negative coverage is owned by references/core/crud-test-matrix.md.
1.5a Limited-Oracle / Score-Objective Evaluation
When the real evaluator is scarce, paid, rate-limited, or opaque and local tests are
proxy metrics for a score/objective, apply §9.5 (single owner of GATE-ORACLE-VALIDITY-01,
GATE-PREFIX-HORIZON-01, GATE-INVARIANT-EV-01, GATE-HOLDOUT-LEAKAGE-01,
GATE-AGREEMENT-STATS-01). Pairs with dev-pabcd §10 Optimization-Loop Meta-Rules.
1.6 Property-Based & Mutation Testing (verified 2026-07-02)
| Technique | Use for | Default tools | When |
|---|
| Property-based | Pure logic, parsers, serializers, state machines, API invariants | fast-check (TS), Hypothesis (Python) | DEFAULT for invariant-heavy code |
| Mutation | Judging test-suite strength on critical domain logic, validators, security branches | Stryker (JS/TS), mutmut (Python) | Selective, after stable unit/property tests — not every PR |
- Vitest 4 is the current runner baseline: Browser Mode is stable (visual regression via
toMatchScreenshot, Playwright trace generation, expect.schemaMatching).
2. Backend & API Testing
Deep reference: references/backend-testing.md
2.1 Coverage Map
| Layer | Verify | TypeScript Default | Python Default |
|---|
| Service layer | validation, orchestration, domain errors | Vitest | pytest |
| API layer | status, envelope, middleware, auth | Supertest | httpx / ASGITransport |
| Repository layer | SQL / ORM correctness | Testcontainers + real DB | Testcontainers + real DB |
| Background jobs | idempotency, retry, dead-letter | Vitest + fake clock | pytest + monkeypatch |
2.2 Mock Strategy Hierarchy
real deterministic dependency
→ Testcontainers / ephemeral infra
→ recorded responses / thin fake
→ manual stub / fake
→ framework mock as last resort
2.3 Service & API Patterns
Mock dependencies at service boundaries. Use Supertest/httpx for route-level integration tests. Match response envelope shape from backend contracts.
2.4 Database Truth with Testcontainers
Use a real database when verifying migrations, transactions, unique constraints, foreign keys, query translation, and performance-sensitive SQL. Use Testcontainers for real DB truth in correctness-sensitive persistence tests. Start container in beforeAll/fixture setup, capture connection URI.
2.5 Fixture / Seed Synchronization
- Prefer builders / factories over copied JSON snapshots.
- Keep shared contract examples in
fixtures/contracts/ or equivalent.
- Seed data should expose stable IDs used by Playwright smoke flows.
- If frontend mocks drift from backend fixtures, write or update a contract test first.
3. Contract Testing
Contract tests protect the frontend↔backend boundary. They sit between API tests and browser tests.
Rule: Playwright proves the experience. Contract tests prove the shared shape.
3.1 Contract-Stable Surface
- response envelope:
success, data, error, meta
- error taxonomy: HTTP status + machine-readable
error.code
- pagination fields, auth headers, cookie behavior
requestId propagation- nullability, timestamps, enums, money serialization
3.2 Contract Options
| Style | Best For | Tooling |
|---|
| consumer-driven contract | rapidly changing frontend/backend teams | Pact |
| schema-first contract | OpenAPI-led backends | OpenAPI validators, Schemathesis |
| type-level contract | TS monorepos | shared types / codegen |
| full-stack smoke | final user confidence | Playwright |
3.3 Consumer Contract — TypeScript (Pact / PactV4)
PactV4 (aliased Pact) is the current interface and supports Pact Specification v4;
treat PactV3 as the legacy spec-v3 API. Workflow:
- Define interaction: provider state + request + expected response (matchers for flexible matching)
- Execute test against Pact mock server
- Assert consumer expectations
- Pact file auto-writes to
pacts/ → publish to broker → provider verifies
See references/backend-testing.md for a full example.
3.4 Schema Verification
Use schema-based API testing (Schemathesis) to verify OpenAPI/GraphQL contract
compliance. (Dredd is legacy/inactive — do not adopt for new projects.)
3.5 Rules
- Contract tests are strongly recommended for parallel FE/BE, public APIs, and cross-team contracts.
- E2E success does not replace provider verification.
- Store golden examples near the contract, not inside one app only.
- If the shape is intentionally breaking, update the contract first, then all consumers.
4. Playwright Browser Testing
Use Playwright after API and contract tests are already trustworthy. Browser tests should validate rendered flows, accessibility-critical interactions, and real integration seams that lower layers cannot prove alone.
Helper Scripts Available:
scripts/with_server.py - Manages server lifecycle (supports multiple servers)
Run scripts with --help first — treat as black boxes to avoid context window pollution.
4.1 Decision Tree: Choosing Your Approach
User task → Static HTML? → Read file → find selectors → write Playwright script
→ Dynamic app? → Server running? → No: `python scripts/with_server.py --help`
→ Yes: Recon-then-action (navigate → screenshot → selectors → act)
4.2 Example: Using with_server.py
python scripts/with_server.py --server "npm run dev" --port 5173 -- python your_automation.py
python scripts/with_server.py \
--server "cd backend && python server.py" --port 3000 \
--server "cd frontend && npm run dev" --port 5173 \
-- python your_automation.py
4.3 Reconnaissance-Then-Action Pattern
- Wait for an explicit app-ready signal or locator assertion → 2. Screenshot/inspect DOM → 3. Identify selectors → 4. Execute actions
4.4 Best Practices
- Use bundled scripts as black boxes — run
--help first, invoke directly.
- Use
sync_playwright() for synchronous scripts; always close the browser.
- Prefer locator-based interactions and web-first assertions:
expect(page.get_by_role("button", name="Save")).to_be_visible(), then click() on that locator.
- Prefer user-facing locators, especially
get_by_role() with an accessible name. Use get_by_label(), get_by_placeholder(), or get_by_test_id() when role/name cannot express the target.
- Avoid
networkidle, hard sleeps, and wait_for_timeout() in tests. Wait on observable app-ready signals, locator actions, or expect() assertions.
- AI-authored tests (DEFAULT): Playwright MCP / Test Agents (planner/generator/healer) are generation-and-repair aids only — final acceptance still requires deterministic locators, web-first assertions, traces, and a human-readable failure artifact.
4.5 Reference Files
- examples/ - Examples showing common patterns:
element_discovery.py - Discovering buttons, links, and inputs on a pagestatic_html_automation.py - Using file:// URLs for local HTMLconsole_logging.py - Capturing console logs during automation
4.6 Browser Testing Rules
- Run contract tests and API tests first for broken-data bugs.
- Use Playwright for rendered truth, not as a replacement for service tests.
- Prefer one smoke flow per critical path over many brittle micro-flows.
- If a failure looks like data-shape drift, go back to §2 Backend & API Testing or §3 Contract Testing.
5. CI Pipeline Integration
Full workflow templates: references/ci-pipeline.md
5.1 Pipeline Order
quality (lint / typecheck)
→ unit + integration tests
→ contract tests
→ Playwright E2E
→ security scan
→ coverage aggregation + artifacts
5.2 Pipeline Template
Structure CI jobs in dependency chain: quality → backend-tests → contract-tests → e2e
Key configuration:
concurrency.cancel-in-progress: true — avoid wasted runsstrategy.fail-fast: false — for matrix builds- Shard large suites:
--shard=${{ matrix.shard }}/N
- Install Playwright deps:
npx playwright install --with-deps chromium
See references/ci-pipeline.md for full GitHub Actions and GitLab CI templates.
5.3 Matrix & Parallelization
| Dimension | When to Use |
|---|
| Node / Python version matrix | packages, SDKs, shared libraries |
| OS matrix | native modules, CLI behavior |
| shard matrix | large suites exceeding CI budget |
npx vitest run --shard=1/4
npx playwright test --shard=1/4 --workers=4
pytest -n auto --dist=loadgroup
5.4 Flaky Test Remediation
| Symptom | First Fix |
|---|
| passes locally, fails in CI | deterministic seeds, containerized deps, explicit waits |
| order-dependent failure | reset shared state in fixtures |
| green on retry only | remove wall-clock / random assumptions |
| screenshot noise | stable CI image, mask dynamic regions |
| Protocol: detect → quarantine if blocking → assign owner → reinstate after repeated green runs. | |
5.5 Rules
- Do not let Playwright be the only blocking job.
- Contract tests should run before browser tests.
- Upload artifacts for failures: coverage, junit, traces, screenshots.
- Fail the build on broken thresholds, not only test exit codes.
6. TDD Enforcement Mode
When ENFORCE_TDD=true is set in project instructions or explicitly requested, this section becomes mandatory.
6.1 RED → GREEN → REFACTOR
- RED — write the failing test first and verify it fails for the right reason.
- GREEN — write the minimum implementation to pass.
- REFACTOR — clean up after green, then rerun the affected suite.
6.2 Self-Audit Checklist
| Check | Pass Criteria |
|---|
| Test written before implementation? | test file added / updated before or with code |
| Failure observed before fix? | red state was actually executed |
| Behavior-focused assertions? | checks outputs, side effects, contracts |
| Regression locked in? | failing case is now protected by a persistent test |
6.3 Vertical Tracer-Bullet TDD
Prefer one behavior test → minimal implementation → next behavior. Slice by something
a user, caller, or consuming module can observe, not by horizontal layers such as "DB",
"API", then "UI". Assert through public interfaces and durable contracts. Retire shallow
scaffolding tests when a stronger interface or acceptance test covers the same promise.
6.4 Default Style
| Style | Best For |
|---|
| London / mockist | orchestration-heavy boundaries |
| Chicago / classicist | domain logic and transforms |
| Hybrid | most production code |
| Default to Hybrid: mock external systems, keep internal collaboration real unless it becomes too slow or unstable. | |
6.5 Boundary with dev-debugging
dev-testing owns the regression harness and enforcement loop.dev-debugging owns root-cause methodology once a failure is mysterious or multi-layered.- After
dev-debugging isolates the cause, come back here to lock it in with tests.
6.6 AI-Assisted Development Regressions
When an AI writes and reviews its own code, it carries the same assumptions into both steps. Automated tests break this feedback loop.
Common AI Regression Patterns
| Pattern | Description | Test Strategy |
|---|
| Sandbox/production mismatch | Fix applied to one code path, not both | Assert same response shape in both modes |
| SELECT clause omission | New field in response but missing from DB query | Assert all required fields are present and defined |
| Error state leakage | Error set but stale data not cleared | Assert state cleanup on error transitions |
| Missing rollback | Optimistic UI update without recovery on failure | Assert state restoration after simulated API error |
Regression Naming Convention
Name regression tests with BUG-R{N} convention. Assert all required fields with a loop.
Sandbox-Mode API Testing
When the project supports a sandbox/mock mode, use it for fast DB-free regression testing:
- Force sandbox mode in test setup:
process.env.SANDBOX_MODE = 'true'
- Assert sandbox responses match the same contract as production responses.
- Treat sandbox/production parity as a high-priority regression target.
- In sandbox/spike mode, write tests for bugs found — coverage grows organically. For production refactors, see §1.5 (tests required for behavior changes).
6.7 Test-Induced Production Defense Detection
Rule: Do not add production defensive code solely to satisfy unrealistic tests. A production guard is allowed only when the invalid state can occur at a real boundary or represents an explicit domain rule.
| Production change smell | Likely test problem | Required action |
|---|
Internal if (!x) return added after unit test fails | Test fixture omitted required field | Fix fixture factory or test boundary validation |
| Required field made optional to satisfy test | Test is using invalid domain object | Restore required type and update test data |
| Catch-all added so test passes | Test expects silence instead of failure | Assert typed error or user-visible failure |
| Production default added for impossible state | Test bypassed constructor/parser | Use real constructor/parser in test |
| Private helper exported only for test | Test is coupled to implementation | Test public behavior or move helper to test support |
| Sleep/retry added only for test flake | Test lacks deterministic synchronization | Wait on observable condition or fake clock |
NODE_ENV === "test" branch added | Test-only production behavior | Remove branch; improve test harness |
Required questions before adding a guard:
- Is the input from an untrusted boundary? → If yes, validate at that boundary
- Can this state happen in production? → If no, fix the test
- What contract allows this value? → Cite schema/type/domain rule
- Would this hide a real bug? → If yes, fail fast instead
Banned patterns: process.env.NODE_ENV === "test" branches, silent fallbacks for impossible internal state, making required types optional for mocks, exporting internals only for tests.
Allowed guards: Boundary validation (process/network/user/file boundary), backward compatibility (documented old schema), security checks, domain invariants, observed production bug regressions, external dependency adapters.
7. Accessibility Testing
Component Level
Page Level
CI Pipeline
- Gate order (verified 2026-07-02): component axe (jest-axe/vitest-axe) → page axe
(@axe-core/playwright) → keyboard/focus/manual checks. Blocking gate = zero
serious/critical axe violations + targeted manual checks.
- Lighthouse a11y score (≥90) is an advisory route-level smoke signal, NOT the blocking
gate — Lighthouse itself separates automated scoring from required manual checks.
- Pa11y: page-level scanning for WCAG AA violations
- Run a11y tests on EVERY page route, not just the homepage
Observability Verification
Verify trace propagation in integration tests. Assert that spans appear for critical paths. Check structured log format matches the schema in dev-backend/references/core/observability.md.
8. Security Testing
→ Delegated: threat modeling and secure design policy belong to dev-security.
This section covers the automated test hooks and CI gates that enforce those rules.
8.1 Minimum Security Stack
fast local checks
→ Semgrep / CodeQL gate
→ dependency audit
→ auth / validation regression tests
8.2 Dependency Scanning Commands
npm audit --audit-level=high
pip-audit --strict --desc
8.3 Semgrep Gate
The returntocorp/semgrep-action wrapper is deprecated (stated by the repo itself) —
run Semgrep natively in CI:
semgrep:
runs-on: ubuntu-latest
container: semgrep/semgrep
steps:
- uses: actions/checkout@v4
- run: semgrep ci --config p/default --config p/javascript --config p/typescript --config p/python
(Open-source alternative engine: Opengrep, the LGPL-2.1 community fork — see
dev-security/references/static-analysis.md.)
8.4 Security Regressions
Test missing auth (expect 401) and verify error.code matches contract for every auth-protected endpoint.
8.5 Rules
- dependency audit in CI
- Semgrep or equivalent SAST
- auth / permission regression tests
- validation tests for malicious or malformed input
- a blocking rule for high / critical dependency findings
9. Coverage & Quality Gates
9.1 Suggested Thresholds
These are project/risk-based, not universal minimums. Adjust for your context.
| Metric | Suggested Floor | Ideal |
|---|
| Line coverage | 70% | 85%+ |
| Branch coverage | 60% | 80%+ |
| Function coverage | 80% | 90%+ |
| Diff coverage | 80% | 90%+ |
9.2 Outcome Metrics
| Metric | Target |
|---|
| Defect detection rate | > 80% |
| Mean time to detect | < 1 CI run |
| Test signal-to-noise | > 95% |
| Contract drift rate | near 0 |
9.3 Coverage Workflow
- generate coverage reports
npm test -- --coverage
npx vitest run --coverage
pytest --cov --cov-report=xml
- review by priority: auth, payment, mutations, upload, contracts first
- write targeted tests for the gaps
- publish artifacts and fail the merge when thresholds drop
9.4 Quality Gate Checklist
9.5 Limited-Oracle / Score-Objective Evaluation
Use these rules when the true evaluator is scarce, paid, rate-limited, or opaque and
local checks are only proxy metrics for a score/objective. PABCD loop response to
repeated candidate deaths is owned by dev-pabcd §10 Optimization-Loop Meta-Rules.
- STRICT (GATE-ORACLE-VALIDITY-01): When the true evaluator/oracle is rate-limited
(limited submissions, paid runs) and local metrics are proxies, evaluator validity is a
prerequisite gate. Before trusting the proxy for accept/reject, quantify historical
divergence: cases where the proxy said better/equal but the oracle said worse. A proxy
with known optimistic bias must not be the sole acceptance evidence.
- DEFAULT (GATE-PREFIX-HORIZON-01): Replay-based evidence (recorded logs, scripted
opponents) is prefix-valid only; it stops being valid when the candidate diverges from
the recorded trajectory. Candidates that diverge early need live adversarial evaluation
through a modeled opponent/environment, not replays. State the divergence turn/point
when citing replay evidence.
- DEFAULT (GATE-INVARIANT-EV-01): Every hard invariant in an acceptance gate (a metric
that must not regress) needs an expected-value justification: protected value versus the
candidate-space it vetoes. If a hard invariant vetoes 3+ consecutive candidates that
target strictly larger gains, downgrade it to a soft cost and re-justify or remove.
- DEFAULT (GATE-HOLDOUT-LEAKAGE-01): Fixed evaluation sets become training data
under adaptive reuse. Rotate or quarantine repeatedly used sets, keep a blind final
set, and treat repeated score-driven tuning on the same instances as leakage risk.
Grounding: Blum and Hardt, "The Ladder: A Reliable Leaderboard for Machine
Learning Competitions" (arXiv:1502.04585), and Dwork et al., "The reusable holdout:
Preserving validity in adaptive data analysis" (arXiv:1506.02629).
- HEURISTIC (GATE-AGREEMENT-STATS-01): For proxy-vs-oracle validation, report
agreement statistics that expose error shape: sign-discordance, bias, and worst-case
error. Correlation alone is not enough; Bland-Altman style agreement analysis is the
grounding model.
Grounding: observed in a 14-discard optimization plateau where a prefix-only replay gate
and a hard draw-protection invariant locked a 3.5/8 score.
10. Pre-Flight Test Checklist
10.1 Change-Type Routing
10.2 Harness Readiness
10.3 Contract & Data Integrity
10.4 CI & Reporting
10.5 Final Rule (risk-tier)
Verification intensity follows the work class (dev §0.0 / references/core/crud-test-matrix.md):
for C2 UI work, one focused smoke (manual click-through or one Playwright run) plus targeted
checks IS a complete story; for C3/C4 or release-sensitive work, a single smoke is not enough —
run the affected suites and required negatives. Manual/Playwright smoke is a risk-tier rule,
not a universal blocker.
unit / service
→ API integration
→ contract verification
→ Playwright smoke
→ CI gate + coverage + security scan
