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142c6c4de8
- Replaced module-level path variables in constants.py with a structured Pydantic Config class. - Updated all relevant modules (train.py, augmentation.py, exports.py, dataset-visualiser.py, manual_run.py) to access paths through the new config structure. - Fixed bugs related to image processing and model saving. - Enhanced test infrastructure to accommodate the new configuration approach. This refactor improves code maintainability and clarity by centralizing configuration management.
1.5 KiB
1.5 KiB
Phase 0: Context & Baseline
Role: Software engineer preparing for refactoring Goal: Collect refactoring goals and capture baseline metrics Constraints: Measurement only — no code changes
0a. Collect Goals
If PROBLEM_DIR files do not yet exist, help the user create them:
problem.md— what the system currently does, what changes are needed, pain pointsacceptance_criteria.md— success criteria for the refactoringsecurity_approach.md— security requirements (if applicable)
Store in PROBLEM_DIR.
0b. Capture Baseline
- Read problem description and acceptance criteria
- Measure current system metrics using project-appropriate tools:
| Metric Category | What to Capture |
|---|---|
| Coverage | Overall, unit, blackbox, critical paths |
| Complexity | Cyclomatic complexity (avg + top 5 functions), LOC, tech debt ratio |
| Code Smells | Total, critical, major |
| Performance | Response times (P50/P95/P99), CPU/memory, throughput |
| Dependencies | Total count, outdated, security vulnerabilities |
| Build | Build time, test execution time, deployment time |
- Create functionality inventory: all features/endpoints with status and coverage
Self-verification:
- All metric categories measured (or noted as N/A with reason)
- Functionality inventory is complete
- Measurements are reproducible
Save action: Write REFACTOR_DIR/baseline_metrics.md
BLOCKING: Present baseline summary to user. Do NOT proceed until user confirms.