ai-training/.cursor/skills/test-spec/phases/03-data-validation-gate.md

Phase 3: Test Data & Expected Results Validation Gate (HARD GATE)

Role: Professional Quality Assurance Engineer Goal: Ensure every test scenario produced in Phase 2 has concrete, sufficient test data. Remove tests that lack data. Verify final coverage stays above 75%. Constraints: This phase is MANDATORY and cannot be skipped.

Step 1 — Build the requirements checklist

Scan blackbox-tests.md, performance-tests.md, resilience-tests.md, security-tests.md, and resource-limit-tests.md. For every test scenario, classify its shape (input/output or behavioral) and extract:

Input/output tests:

#	Test Scenario ID	Test Name	Required Input Data	Required Expected Result	Result Quantifiable?	Comparison Method	Input Provided?	Expected Result Provided?
1	[ID]	[name]	[data description]	[what system should output]	[Yes/No]	[exact/tolerance/pattern/threshold]	[Yes/No]	[Yes/No]

Behavioral tests:

#	Test Scenario ID	Test Name	Trigger Condition	Observable Behavior	Pass/Fail Criterion	Quantifiable?
1	[ID]	[name]	[e.g., service receives SIGTERM]	[e.g., drain logs emitted, port closed]	[e.g., drain completes ≤30s]	[Yes/No]

Present both tables to the user.

Step 2 — Ask user to provide missing test data AND expected results

For each row where Input Provided? is No OR Expected Result Provided? is No, ask the user:

Option A — Provide the missing items: Supply what is missing:

• Missing input data: Place test data files in _docs/00_problem/input_data/ or indicate the location.
• Missing expected result: Provide the quantifiable expected result for this input. Update _docs/00_problem/input_data/expected_results/results_report.md with a row mapping the input to its expected output. If the expected result is complex, provide a reference CSV file in _docs/00_problem/input_data/expected_results/. Use .cursor/skills/test-spec/templates/expected-results.md for format guidance.

Expected results MUST be quantifiable — the test must be able to programmatically compare actual vs expected. Examples:

• "3 detections with bounding boxes [(x1,y1,x2,y2), ...] ± 10px"
• "HTTP 200 with JSON body matching expected_response_01.json"
• "Processing time < 500ms"
• "0 false positives in the output set"

Option B — Skip this test: If you cannot provide the data or expected result, this test scenario will be removed from the specification.

BLOCKING: Wait for the user's response for every missing item.

Step 3 — Validate provided data and expected results

For each item where the user chose Option A:

Input data validation:

1. Verify the data file(s) exist at the indicated location
2. Verify quality: data matches the format, schema, and constraints described in the test scenario (e.g., correct image resolution, valid JSON structure, expected value ranges)
3. Verify quantity: enough data samples to cover the scenario (e.g., at least N images for a batch test, multiple edge-case variants)

Expected result validation:

4. Verify the expected result exists in input_data/expected_results/results_report.md or as a referenced file in input_data/expected_results/
5. Verify quantifiability: the expected result can be evaluated programmatically — it must contain at least one of:
   • Exact values (counts, strings, status codes)
   • Numeric values with tolerance (e.g., ± 10px, ≥ 0.85)
   • Pattern matches (regex, substring, JSON schema)
   • Thresholds (e.g., < 500ms, ≤ 5% error rate)
   • Reference file for structural comparison (JSON diff, CSV diff)
6. Verify completeness: the expected result covers all outputs the test checks (not just one field when the test validates multiple)
7. Verify consistency: the expected result is consistent with the acceptance criteria it traces to

If any validation fails, report the specific issue and loop back to Step 2 for that item.

Step 4 — Remove tests without data or expected results

For each item where the user chose Option B:

1. Warn the user: ⚠️ Test scenario [ID] "[Name]" will be REMOVED from the specification due to missing test data or expected result.
2. Remove the test scenario from the respective test file
3. Remove corresponding rows from traceability-matrix.md
4. Update test-data.md to reflect the removal

Save action: Write updated files under TESTS_OUTPUT_DIR:

• test-data.md
• Affected test files (if tests removed)
• traceability-matrix.md (if tests removed)

Step 5 — Final coverage check

After all removals, recalculate coverage:

1. Count remaining test scenarios that trace to acceptance criteria
2. Count total acceptance criteria + restrictions
3. Calculate coverage percentage: covered_items / total_items * 100

Metric	Value
Total AC + Restrictions	?
Covered by remaining tests	?
Coverage %	?%

Decision:

• Coverage ≥ 75% → Phase 3 PASSED. Present final summary to user.

• Coverage < 75% → Phase 3 FAILED. Report:

  ❌ Test coverage dropped to X% (minimum 75% required). The removed test scenarios left gaps in the following acceptance criteria / restrictions:

  Uncovered Item	Type (AC/Restriction)	Missing Test Data Needed

  Action required: Provide the missing test data for the items above, or add alternative test scenarios that cover these items with data you can supply.

  BLOCKING: Loop back to Step 2 with the uncovered items. Do NOT finalize until coverage ≥ 75%.

Phase 3 Completion

When coverage ≥ 75% and all remaining tests have validated data AND quantifiable expected results:

1. Present the final coverage report
2. List all removed tests (if any) with reasons
3. Confirm every remaining test has: input data + quantifiable expected result + comparison method
4. Confirm all artifacts are saved and consistent

After Phase 3 completion, run phases/hardware-assessment.md before Phase 4.