Skip to main content

TDDAI Platform Overview

Executive Summary​

TDDAI (Test-Driven Development AI) is a comprehensive development methodology enforcement platform integrated throughout the LLM Platform ecosystem. It combines automated testing, AI-assisted development, and strict TDD workflow enforcement to ensure code quality and maintainability across all projects.

Platform Architecture​

Core Components​

graph TB
    A[TDDAI Core Engine] --> B[Claude Code Integration]
    A --> C[CLI Tools]
    A --> D[IDE Extensions]
    A --> E[CI/CD Pipelines]
    
    B --> F[Context Injection]
    B --> G[Compliance Guardian]
    
    C --> H[tddai CLI]
    C --> I[llmcli Integration]
    
    D --> J[VS Code]
    D --> K[Cursor IDE]
    
    E --> L[GitLab CI]
    E --> M[GitHub Actions]

Implementation Status​

Phase 1: Foundation (✅ Complete)​

  • TDDAI package development
  • Core TDD enforcement engine
  • Basic CLI commands
  • Coverage analysis tools

Phase 2: Integration (✅ Complete)​

  • Claude Code hooks implementation
  • 33 projects configured
  • Multi-language support
  • Automated setup scripts

Phase 3: Enhancement (🚧 In Progress)​

  • AI-powered test generation
  • Real-time coverage monitoring
  • Team collaboration features
  • Advanced analytics

Project Configuration Matrix​

Project TypeCountFrameworkCoverage TargetSpecial Features
TypeScript18Jest95%ES Module support
PHP/Drupal15PHPUnit80-95%Drupal standards
Python1pytest90%FastAPI integration
Docker2docker-test80%Container testing

Key Features​

1. Intelligent Context Awareness​

  • Automatic project type detection
  • Framework-specific guidance
  • Dynamic configuration loading
  • Language-appropriate suggestions

2. Workflow Enforcement​

  • Pre-commit hooks
  • IDE integration
  • CI/CD gates
  • Real-time feedback

3. AI Integration​

  • Ollama as primary provider
  • Fallback to Anthropic/OpenAI
  • Test generation assistance
  • Code quality suggestions

4. Comprehensive Coverage​

  • Unit testing
  • Integration testing
  • E2E testing
  • Performance testing

Command Reference​

Basic Commands​

# Project validation
npx tddai validate --strict

# Test execution
npx tddai test

# Coverage analysis
npx tddai coverage

# Fix common issues
npx tddai fix

# Generate missing tests
npx tddai generate-tests

Advanced Features​

# AI-powered improvements
npx tddai improve analyze --all --detailed
npx tddai improve fix --all
npx tddai improve generate-tests

# Integration with llmcli
npx llmcli test-gen src/utils/helpers.ts
npx llmcli test-gen analyze ./
npx llmcli test-gen batch "src/**/*.ts"

Configuration Standards​

Directory Structure​

project-root/
├── .claude/
│   ├── settings.json
│   └── hooks/
│       ├── tdd-context-injector.[js|cjs]
│       └── tdd-compliance-guardian.[js|cjs]
├── .tddai/
│   └── config.yaml
├── tddai.config.yml
└── .tddai-standards.yaml

Coverage Requirements​

  • Critical Systems: 95%+
  • Core Services: 90%+
  • Support Tools: 85%+
  • Experimental: 80%+

Integration Points​

1. Development Environment​

  • Claude Code: Full hook integration
  • VS Code: Extension support
  • Cursor IDE: Native integration
  • Terminal: CLI tools

2. CI/CD Pipeline​

  • Pre-commit: Local validation
  • PR Checks: Automated testing
  • Merge Gates: Coverage requirements
  • Deployment: Quality assurance

3. Monitoring & Analytics​

  • Coverage Trends: Historical tracking
  • Test Performance: Execution metrics
  • Quality Scores: Composite ratings
  • Team Dashboard: Collaborative view

Best Practices​

1. TDD Workflow​

1. RED Phase
   - Write failing test
   - Verify test fails
   - Commit test

2. GREEN Phase
   - Write minimal code
   - Make test pass
   - Commit implementation

3. REFACTOR Phase
   - Improve code quality
   - Maintain green tests
   - Commit improvements

2. Test Organization​

src/
├── components/
│   ├── Button.ts
│   └── Button.test.ts
├── utils/
│   ├── helpers.ts
│   └── helpers.test.ts
└── __tests__/
    └── integration/

3. Coverage Strategy​

  • Line Coverage: Minimum baseline
  • Branch Coverage: All conditions
  • Function Coverage: Every method
  • Statement Coverage: Complete flow

Platform Benefits​

1. Code Quality​

  • Reduced bug density
  • Improved maintainability
  • Better documentation
  • Consistent patterns

2. Developer Productivity​

  • Faster debugging
  • Confident refactoring
  • Clear requirements
  • Automated validation

3. Team Collaboration​

  • Shared standards
  • Review efficiency
  • Knowledge transfer
  • Onboarding speed

4. Business Value​

  • Reduced defects
  • Faster delivery
  • Lower maintenance
  • Higher reliability

Troubleshooting Guide​

Common Issues​

  1. Hook Not Triggering

    # Check settings
    cat .claude/settings.json

    # Verify permissions
    chmod +x .claude/hooks/*.js

    # Test manually
    node .claude/hooks/tdd-context-injector.js

  2. Coverage Below Threshold

    # Analyze gaps
    npx tddai coverage --detailed

    # Generate tests
    npx tddai generate-tests

    # Focus areas
    npx tddai improve analyze

  3. ES Module Errors

    # Rename to .cjs
    mv hook.js hook.cjs

    # Update settings
    sed -i '' 's/\.js/.cjs/g' .claude/settings.json

Roadmap​

Q1 2025​

  • Real-time coverage display
  • Team synchronization
  • Advanced AI models
  • Performance optimization

Q2 2025​

  • Visual test builder
  • Mutation testing
  • Contract testing
  • Security scanning

Q3 2025​

  • ML-powered suggestions
  • Predictive quality metrics
  • Automated refactoring
  • Cross-project analysis

Getting Started​

Quick Setup​

# Install TDDAI globally
npm install -g @bluefly/tddai

# Initialize in project
tddai init

# Setup Claude integration
tddai setup claude

# Run validation
tddai validate --strict

Learning Resources​

  1. TDD Fundamentals
  2. TDDAI CLI Guide
  3. Claude Integration
  4. Best Practices

Support​

Documentation​

Community​

  • GitLab Issues: Bug reports
  • Discussions: Feature requests
  • Wiki: Community guides
  • Slack: Real-time help

Conclusion​

TDDAI represents a paradigm shift in development methodology enforcement, combining traditional TDD principles with modern AI capabilities. With comprehensive coverage across the LLM Platform ecosystem, it ensures consistent quality standards while accelerating development velocity through intelligent automation and contextual assistance.