# Specification Quality Checklist: Test Quality Audit and Performance Optimization

**Purpose**: Validate specification completeness and quality before proceeding to planning
**Created**: 2025-12-11
**Updated**: 2025-12-11 (Root cause analysis: ggen.toml false positive)
**Feature**: [spec.md](../spec.md)

## Content Quality

- [x] No implementation details (languages, frameworks, APIs)
- [x] Focused on user value and business needs
- [x] Written for non-technical stakeholders
- [x] All mandatory sections completed

## Requirement Completeness

- [x] No [NEEDS CLARIFICATION] markers remain
- [x] Requirements are testable and unambiguous
- [x] Success criteria are measurable
- [x] Success criteria are technology-agnostic (no implementation details)
- [x] All acceptance scenarios are defined
- [x] Edge cases are identified
- [x] Scope is clearly bounded
- [x] Dependencies and assumptions identified

## Feature Readiness

- [x] All functional requirements have clear acceptance criteria
- [x] User scenarios cover primary flows
- [x] Feature meets measurable outcomes defined in Success Criteria
- [x] No implementation details leak into specification

## Validation Notes

**Content Quality Assessment**:
- ✅ Specification avoids implementation details (no mention of specific mutation testing tools, assertion analysis algorithms, or test selection libraries)
- ✅ **CRITICAL**: Addresses root cause FIRST - test quality and false positives (ggen.toml broken but tests pass) BEFORE optimization
- ✅ Focused on test quality (behavior validation) THEN performance (fast feedback, CPU utilization, test suite maintenance)
- ✅ Written in terms of "developers need", "system must", "tests validate" (stakeholder language)
- ✅ All mandatory sections (User Scenarios, Requirements, Success Criteria, Assumptions) are complete with two-phase approach

**Requirement Completeness Assessment**:
- ✅ Zero [NEEDS CLARIFICATION] markers - all requirements are concrete with specific quality and performance targets
- ✅ Requirements are testable in TWO phases: (1) Phase 1/P0: audit test quality and fix false positives, (2) Phase 2/P1-P3: optimize for performance
- ✅ Success criteria include specific metrics for BOTH phases: audit (80% mutation kill rate, zero critical path gaps, ggen.toml false positive fixed) AND optimization (≤1s unit tests, ≤10s integration tests, 80% bug detection)
- ✅ Success criteria avoid technology specifics (e.g., "mutation testing achieves 80% kill rate" vs "use cargo-mutants with PITest")
- ✅ Acceptance scenarios follow Given-When-Then format with clear, measurable conditions including false positive detection (P0 user story)
- ✅ Edge cases identify 14 boundary conditions split across test quality (6 cases: false positives, weak assertions, missing behavior tests) and optimization (8 cases: concurrent conflicts, budget violations, slow tests)
- ✅ Scope is bounded to test quality audit THEN optimization with strict performance budgets (two-phase approach prevents optimizing broken tests)
- ✅ Assumptions section explicitly separates KNOWN issues (ggen.toml false positive) from UNKNOWN issues (full extent of false positives) and infrastructure assumptions (21 total dependencies)

**Feature Readiness Assessment**:
- ✅ All 18 functional requirements have clear, measurable acceptance criteria split across Phase 1 (FR-001 to FR-006: test quality audit) and Phase 2 (FR-007 to FR-018: optimization and budget enforcement)
- ✅ User scenarios cover FOUR prioritized flows: test quality audit (P0), fast feedback (P1), intelligent selection (P2), parallel execution (P3)
- ✅ **ROOT CAUSE ADDRESSED**: P0 user story explicitly tackles user's concern "What are we testing and why? ggen.toml doesn't work at all but is passing tests"
- ✅ Feature meets measurable outcomes across BOTH phases: audit (zero false positives, 80% mutation kill, ggen.toml test fixed) AND optimization (≤1s unit tests, ≤10s integration tests, 80% bug detection)
- ✅ No implementation leakage - spec describes WHAT (identify false positives, fix ggen.toml test, optimize to 200 tests) not HOW (use specific mutation testing tools, assertion analysis algorithms)
- ✅ Two-phase approach ensures quality BEFORE optimization (prevents making broken tests faster)
- ✅ Strict performance budgets clearly defined and enforced (hard limits, not averages) BUT ONLY AFTER test quality is validated

**Quality Assessment**: ✅ **PASS** - Specification is complete, technology-agnostic, addresses root cause (false positives like ggen.toml), and ready for planning phase. Two-phase approach (audit THEN optimize) ensures we understand what we're testing and why before making it fast.
