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Development Best Practices for CodePrism 🎯

🤖 AI-Generated Excellence Standards​

This document outlines the rigorous engineering practices our AI developer follows to ensure production-quality software.

🏗️ Architectural Principles​

1. Separation of Concerns​

  • Crate-level: Clear responsibility boundaries between codeprism-core, codeprism-analysis, etc.
  • Module-level: Single responsibility per module
  • Function-level: Each function has one clear purpose

2. Dependency Inversion​

  • High-level modules depend on abstractions, not concretions
  • Use traits for dependency injection
  • Enable easy testing and modularity

🧪 Test-Driven Development​

TDD Cycle​

  1. RED: Write failing test first
  2. GREEN: Write minimal implementation
  3. REFACTOR: Improve while keeping tests green

Test Categories​

  • Unit Tests: 90% coverage target
  • Integration Tests: Critical paths covered
  • Property-Based Tests: Edge case discovery
  • Regression Tests: Every bug gets a test

🔍 Code Quality Standards​

Metrics​

  • Cyclomatic Complexity: Max 10 per function
  • Test Coverage: >90% for critical paths
  • Documentation: All public APIs documented
  • Performance: Sub-second response times

Error Handling​

  • Use Result<T, E> consistently
  • Comprehensive error types with thiserror
  • Early returns for error conditions
  • Never panic in library code

📐 Design Patterns​

Common Patterns Used​

  • Builder Pattern: Complex object construction
  • Strategy Pattern: Algorithm selection
  • Observer Pattern: Event handling
  • Factory Pattern: Object creation

🔒 Security Best Practices​

Input Validation​

  • Validate all external inputs
  • Prevent path traversal attacks
  • Sanitize data before processing

Resource Limits​

  • File size limits (10MB max)
  • Analysis time limits (30s max)
  • Memory usage monitoring

⚡ Performance Optimization​

Strategies​

  • Lazy Evaluation: Compute only when needed
  • Parallel Processing: Use rayon for CPU-intensive tasks
  • Caching: LRU cache for expensive operations
  • Zero-Copy: Avoid unnecessary allocations

📊 Continuous Integration​

Quality Gates​

  • All tests must pass
  • Code formatting enforced
  • Clippy warnings as errors
  • Security audit checks
  • Performance regression tests

📝 Documentation Standards​

Requirements​

  • Comprehensive API documentation
  • Usage examples for all public functions
  • Performance characteristics documented
  • Error conditions explained

🚀 Release Standards​

Semantic Versioning​

  • MAJOR: Breaking changes
  • MINOR: New features
  • PATCH: Bug fixes

Release Checklist​

  • All tests pass
  • Documentation updated
  • Changelog generated
  • Performance benchmarks acceptable

These practices ensure our AI-generated code meets the highest quality standards while maintaining rapid development velocity.