# FraiseQL Test Suite Quality Scorecard

**Generated:** 2024-11-30
**Evaluation Period:** Full test suite analysis

## Overall Score: 3.8/5

| Dimension | Score | Trend | Notes |
|-----------|-------|-------|-------|
| Test Volume | 5/5 | ↑ | 4,655 tests - excellent coverage breadth |
| Test Quality | 4.2/5 | → | Good quality from sampled reviews |
| Organization | 4/5 | → | Well-structured directories |
| Marker Consistency | 3/5 | ⚠ | Many tests missing markers |
| Performance | 4/5 | ↑ | 6.3s collection, 72% fast tests |
| Code Coverage | 3/5 | ⚠ | Many modules <50% coverage |
| Fixture Quality | 4/5 | → | Good scope usage, needs docs |

## Strengths

1. **High test volume** - 4,655 tests with 1.53x test-to-code ratio (111,064 test lines vs 72,283 source lines)
2. **Excellent regression test quality** - Regression tests scored 5.0/5 with proper isolation and edge case coverage
3. **Smart fixture optimization** - Conditional clearing based on markers reduces overhead
4. **Fast test collection** - ~6 seconds with FRAISEQL_SKIP_RUST=1
5. **Clear test naming** - Test names consistently describe what they verify

## Areas for Improvement

1. **Coverage gaps in core modules** - `nested_field_resolver.py` at 11%, `cqrs/repository.py` at 15%
2. **Marker inconsistency** - Only 180 explicit `@pytest.mark.unit` vs ~3,372 potential unit tests
3. **Zero coverage on caching module** - Entire `caching/` package untested
4. **Integration test isolation** - Many integration tests reduce isolation scores
5. **Star imports in conftest** - Makes fixture discovery difficult

## Key Metrics

| Metric | Value |
|--------|-------|
| Total Tests | 4,655 |
| Source Lines | 72,283 |
| Test Lines | 111,064 |
| Test-to-Code Ratio | 1.53x |
| Test Files | 439 |
| Unit Test Files | 189 |
| Integration Test Files | 175 |
| Regression Test Files | 25 |
| Collection Time | 6.3s |
| Database Tests | 506 (10.9%) |
| Fast Tests (no db) | ~3,372 (72.4%) |

## Marker Distribution

| Marker | Count | % of Tests |
|--------|-------|------------|
| @pytest.mark.asyncio | 703 | 15.1% |
| @pytest.mark.unit | 180 | 3.9% |
| @pytest.mark.integration | 28 | 0.6% |
| @pytest.mark.database | 18+ | ~0.4% |
| @pytest.mark.core | 15 | 0.3% |
| @pytest.mark.regression | 12 | 0.3% |
| @pytest.mark.security | 11 | 0.2% |
| @pytest.mark.slow | 3 | <0.1% |

## Coverage by Module Category

| Category | Coverage Range | Priority |
|----------|----------------|----------|
| Core | 11-100% | **P0 - Critical** |
| CQRS | 13-36% | **P0 - Critical** |
| Auth | 0-96% | **P1 - High** |
| Caching | 0% | **P1 - High** |
| FastAPI | 0-82% | P2 - Medium |
| CLI | 0% | P3 - Low |
| Enterprise | 0% | P3 - Low |

## Recommendations Summary

### Immediate (P0)
1. **Add markers to unmarked tests** - Run `fix_test_markers.py` on remaining files
2. **Add core module tests** - Target `nested_field_resolver.py`, `cqrs/repository.py`

### Short-term (P1)
3. **Add caching tests** - Entire module at 0% coverage
4. **Add auth flow tests** - `auth0.py` at 20%, `token_revocation.py` at 28%

### Medium-term (P2)
5. **Replace star imports in conftest** - Improves fixture discoverability
6. **Add fixture documentation** - Missing type hints and docstrings

### Long-term (P3)
7. **Consider CLI integration tests** - Currently 0% coverage
8. **Enterprise feature tests** - Add when features are actively used

## CI/CD Optimization Potential

- **Current state**: All tests run together
- **Optimization**: Split into fast (72%) and slow (28%) jobs
- **Estimated speedup**: 2-3x faster feedback on unit test failures
- **Implementation**: Use marker-based test selection in CI workflow

## Quality Trend Assessment

| Area | 6mo Trend | Notes |
|------|-----------|-------|
| Test Count | ↑ | Growing with features |
| Coverage | → | Stable but needs improvement |
| Quality | → | Consistent standards |
| Performance | ↑ | Recent optimizations |
| Markers | ↑ | Recent fix_test_markers.py additions |

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*This scorecard should be regenerated monthly to track progress.*
