# TDD Mode CLI Commands Documentation

## Overview

This document provides comprehensive guidance for using SAFLA's CLI commands within the Test-Driven Development (TDD) mode. The TDD mode leverages SAFLA's command-line interface to create, execute, and optimize test suites through systematic CLI operations and automated workflows.

## Core Testing CLI Commands

### 1. Test Environment Setup and Configuration

#### Environment Initialization
```bash
# Setup comprehensive testing environment
python -m safla.env --setup \
  --testing \
  --framework jest \
  --coverage-tools \
  --performance-testing \
  --parallel-execution

# Expected Output:
# ✓ Testing framework (Jest) configured
# ✓ Coverage tools installed and configured
# ✓ Performance testing utilities setup
# ✓ Parallel execution environment ready
# ✓ Test environment validation passed

# Setup with specific testing configuration
python -m safla.env --setup \
  --testing \
  --framework mocha \
  --typescript \
  --coverage-threshold 95 \
  --performance-benchmarks

# Validate testing environment
python -m safla.env --validate \
  --testing-focus \
  --framework-check \
  --dependency-verification \
  --export env_validation.json
```

#### Testing Framework Configuration
```bash
# Configure Jest testing framework
python -m safla.test --configure \
  --framework jest \
  --typescript \
  --coverage-reporting \
  --parallel-workers 4 \
  --export jest.config.js

# Configure performance testing
python -m safla.performance --configure \
  --testing-mode \
  --benchmark-tools \
  --memory-profiling \
  --export performance.config.js

# Setup test data management
python -m safla.test --setup-data \
  --mock-generation \
  --fixture-management \
  --synthetic-data \
  --export test_data_config.json
```

### 2. Test Generation and Development

#### Automated Test Generation
```bash
# Generate comprehensive test suite
python -m safla.tdd --generate \
  --module data_processor \
  --requirements validation,transformation,error_handling \
  --framework jest \
  --coverage-target 95 \
  --test-types unit,integration,performance \
  --export test_generation_report.json

# Expected Output:
# ✓ Generated 24 unit tests
# ✓ Generated 8 integration tests  
# ✓ Generated 4 performance tests
# ✓ Estimated coverage: 96.2%
# ✓ Test files created in tests/ directory

# Generate tests from specifications
python -m safla.tdd --generate-from-spec \
  --spec-file phase_1_spec.md \
  --comprehensive \
  --edge-cases \
  --performance-tests \
  --export spec_based_tests.json

# Generate performance-focused tests
python -m safla.tdd --generate-performance \
  --module search_algorithm \
  --benchmarks latency,throughput,memory \
  --load-testing \
  --stress-testing \
  --export performance_tests.json
```

#### Test Case Development
```bash
# Develop unit tests with TDD approach
python -m safla.tdd --develop-unit \
  --red-green-refactor \
  --module validator \
  --coverage-driven \
  --auto-assertions \
  --export unit_development.json

# Create integration test scenarios
python -m safla.tdd --develop-integration \
  --components data_processor,validator,transformer \
  --workflow-testing \
  --api-testing \
  --export integration_scenarios.json

# Develop edge case tests
python -m safla.tdd --develop-edge-cases \
  --boundary-testing \
  --error-scenarios \
  --null-handling \
  --type-validation \
  --export edge_case_tests.json
```

### 3. Test Execution and Validation

#### Comprehensive Test Execution
```bash
# Run complete test suite
python -m safla.test --run \
  --comprehensive \
  --parallel \
  --coverage-report \
  --performance-metrics \
  --export test_execution_results.json

# Expected Output:
# Running test suite...
# ✓ Unit tests: 156/156 passed (2.3s)
# ✓ Integration tests: 24/24 passed (8.7s)  
# ✓ Performance tests: 8/8 passed (15.2s)
# 
# Coverage Summary:
# Lines: 94.7% (1,247/1,317)
# Branches: 91.2% (456/500)
# Functions: 97.8% (89/91)

# Run specific test categories
python -m safla.test --run \
  --category unit \
  --parallel \
  --watch-mode \
  --export unit_test_results.json

# Run tests with performance monitoring
python -m safla.test --run \
  --performance-monitoring \
  --memory-profiling \
  --bottleneck-detection \
  --export performance_test_results.json
```

#### Test Validation and Quality Assurance
```bash
# Validate test quality and effectiveness
python -m safla.test --validate \
  --quality-metrics \
  --coverage-analysis \
  --maintainability-check \
  --export test_quality_report.json

# Expected Output:
# Test Quality Analysis:
# ✓ Test coverage: 94.7% (target: 95%)
# ✓ Test maintainability: 87.4/100
# ✓ Assertion quality: 92.1/100
# ✓ Mock usage efficiency: 89.3/100
# ⚠ Branch coverage: 91.2% (target: 95%)

# Validate test reliability
python -m safla.test --validate-reliability \
  --flaky-test-detection \
  --consistency-check \
  --retry-analysis \
  --export reliability_report.json

# Validate performance tests
python -m safla.test --validate-performance \
  --benchmark-verification \
  --baseline-comparison \
  --regression-detection \
  --export performance_validation.json
```

### 4. Coverage Analysis and Optimization

#### Comprehensive Coverage Analysis
```bash
# Analyze test coverage in detail
python -m safla.coverage --analyze \
  --comprehensive \
  --line-coverage \
  --branch-coverage \
  --function-coverage \
  --condition-coverage \
  --export coverage_analysis.json

# Expected Output:
# Coverage Analysis Report:
# 
# Overall Coverage: 94.7%
# Line Coverage: 94.7% (1,247/1,317 lines)
# Branch Coverage: 91.2% (456/500 branches)
# Function Coverage: 97.8% (89/91 functions)
# 
# Uncovered Areas:
# - data_processor.ts: lines 45, 67, 89
# - validator.ts: lines 156, 178
# - transformer.ts: lines 23, 201, 234

# Generate coverage reports
python -m safla.coverage --report \
  --html-report \
  --json-export \
  --trend-analysis \
  --export coverage_reports/

# Optimize coverage gaps
python -m safla.coverage --optimize \
  --gap-analysis \
  --test-generation \
  --priority-ranking \
  --export coverage_optimization.json
```

#### Coverage-Driven Test Enhancement
```bash
# Enhance tests based on coverage gaps
python -m safla.tdd --enhance-coverage \
  --gap-analysis coverage_analysis.json \
  --auto-generate-tests \
  --priority-focus \
  --export coverage_enhancement.json

# Target specific coverage improvements
python -m safla.coverage --improve \
  --target-files data_processor.ts,validator.ts \
  --branch-focus \
  --edge-case-generation \
  --export targeted_improvements.json

# Validate coverage improvements
python -m safla.coverage --validate-improvements \
  --before-after-comparison \
  --quality-impact-analysis \
  --export improvement_validation.json
```

### 5. Performance Testing and Benchmarking

#### Performance Test Development
```bash
# Develop comprehensive performance tests
python -m safla.performance --develop-tests \
  --module search_algorithm \
  --benchmarks latency,throughput,memory,cpu \
  --load-scenarios light,normal,heavy,stress \
  --export performance_test_suite.json

# Expected Output:
# Performance Test Development:
# ✓ Latency tests: 8 scenarios created
# ✓ Throughput tests: 6 scenarios created
# ✓ Memory tests: 4 scenarios created
# ✓ CPU tests: 4 scenarios created
# ✓ Load scenarios: 4 levels configured

# Create baseline performance tests
python -m safla.performance --create-baseline \
  --comprehensive \
  --multiple-runs 10 \
  --statistical-analysis \
  --export performance_baseline.json

# Develop stress testing scenarios
python -m safla.performance --develop-stress-tests \
  --memory-stress \
  --cpu-stress \
  --concurrent-load \
  --endurance-testing \
  --export stress_test_scenarios.json
```

#### Performance Test Execution
```bash
# Execute performance test suite
python -m safla.performance --test \
  --comprehensive \
  --baseline-comparison \
  --statistical-analysis \
  --export performance_results.json

# Expected Output:
# Performance Test Results:
# 
# Latency Tests:
# ✓ Average response time: 45ms (target: <50ms)
# ✓ 95th percentile: 78ms (target: <100ms)
# ✓ 99th percentile: 123ms (target: <200ms)
# 
# Throughput Tests:
# ✓ Operations per second: 1,247 (target: >1,000)
# ✓ Concurrent users: 500 (target: >400)
# 
# Memory Tests:
# ✓ Peak memory usage: 2.1GB (target: <3GB)
# ✓ Memory efficiency: 94.2%

# Run performance regression tests
python -m safla.performance --regression-test \
  --baseline performance_baseline.json \
  --threshold 10 \
  --detailed-analysis \
  --export regression_results.json

# Execute load testing
python -m safla.performance --load-test \
  --scenarios light,normal,heavy \
  --duration 300 \
  --ramp-up-strategy gradual \
  --export load_test_results.json
```

### 6. Test Automation and CI/CD Integration

#### Automated Testing Workflows
```bash
# Setup automated testing pipeline
python -m safla.automation --testing \
  --ci-cd-integration \
  --github-actions \
  --quality-gates \
  --automated-reporting \
  --export automation_config.yaml

# Expected Output:
# Automation Configuration:
# ✓ CI/CD pipeline configured
# ✓ Quality gates established
# ✓ Automated test execution setup
# ✓ Reporting and notifications configured
# ✓ Integration with GitHub Actions complete

# Configure automated test execution
python -m safla.automation --test-execution \
  --trigger-on-commit \
  --parallel-execution \
  --failure-notifications \
  --export test_automation.json

# Setup automated quality assurance
python -m safla.automation --quality-assurance \
  --coverage-enforcement \
  --performance-validation \
  --security-testing \
  --export qa_automation.json
```

#### Continuous Integration Testing
```bash
# Configure CI testing pipeline
python -m safla.cicd --configure \
  --testing-focus \
  --multi-stage-testing \
  --quality-gates \
  --automated-deployment \
  --export cicd_testing_config.yaml

# Run CI testing pipeline locally
python -m safla.cicd --run \
  --testing-pipeline \
  --local-execution \
  --comprehensive \
  --export ci_test_results.json

# Validate CI/CD testing configuration
python -m safla.cicd --validate \
  --testing-configuration \
  --pipeline-integrity \
  --quality-gate-validation \
  --export cicd_validation.json
```

### 7. Test Data Management and Mocking

#### Test Data Generation and Management
```bash
# Generate comprehensive test data
python -m safla.test-data --generate \
  --synthetic-data \
  --realistic-patterns \
  --edge-case-data \
  --performance-datasets \
  --export test_data_suite/

# Expected Output:
# Test Data Generation:
# ✓ Synthetic user data: 10,000 records
# ✓ Edge case scenarios: 500 cases
# ✓ Performance datasets: 5 sizes (1K, 10K, 100K, 1M, 10M)
# ✓ Realistic data patterns: 15 categories
# ✓ Data validation rules: applied

# Setup mock data management
python -m safla.mock --setup \
  --api-mocking \
  --database-mocking \
  --service-mocking \
  --intelligent-responses \
  --export mock_configuration.json

# Generate fixture data
python -m safla.fixtures --generate \
  --comprehensive \
  --version-controlled \
  --environment-specific \
  --export fixtures/
```

#### Mock and Stub Management
```bash
# Create intelligent mocks
python -m safla.mock --create \
  --api-endpoints \
  --realistic-responses \
  --error-scenarios \
  --performance-simulation \
  --export mock_definitions.json

# Manage test stubs
python -m safla.stub --manage \
  --dependency-stubs \
  --service-stubs \
  --database-stubs \
  --export stub_configuration.json

# Validate mock effectiveness
python -m safla.mock --validate \
  --realism-check \
  --coverage-analysis \
  --performance-impact \
  --export mock_validation.json
```

### 8. Test Maintenance and Optimization

#### Test Suite Maintenance
```bash
# Maintain and optimize test suite
python -m safla.test --maintain \
  --cleanup-obsolete \
  --optimize-performance \
  --update-dependencies \
  --refactor-duplicates \
  --export maintenance_report.json

# Expected Output:
# Test Suite Maintenance:
# ✓ Removed 12 obsolete tests
# ✓ Optimized 8 slow-running tests
# ✓ Updated 15 dependency references
# ✓ Refactored 6 duplicate test patterns
# ✓ Performance improvement: 23%

# Analyze test suite health
python -m safla.test --health-check \
  --performance-analysis \
  --maintainability-assessment \
  --reliability-evaluation \
  --export health_assessment.json

# Optimize test execution performance
python -m safla.test --optimize \
  --execution-speed \
  --resource-usage \
  --parallel-optimization \
  --export optimization_results.json
```

#### Test Quality Improvement
```bash
# Improve test quality systematically
python -m safla.test --improve-quality \
  --assertion-optimization \
  --readability-enhancement \
  --maintainability-focus \
  --export quality_improvements.json

# Refactor test code
python -m safla.test --refactor \
  --extract-common-patterns \
  --improve-naming \
  --reduce-duplication \
  --enhance-documentation \
  --export refactoring_report.json

# Validate quality improvements
python -m safla.test --validate-quality \
  --before-after-comparison \
  --metrics-analysis \
  --maintainability-check \
  --export quality_validation.json
```

### 9. Reporting and Analytics

#### Comprehensive Test Reporting
```bash
# Generate comprehensive test reports
python -m safla.report --testing \
  --comprehensive \
  --coverage-analysis \
  --performance-metrics \
  --quality-assessment \
  --trend-analysis \
  --export test_reports/

# Expected Output:
# Test Report Generation:
# ✓ Executive summary report
# ✓ Detailed coverage analysis
# ✓ Performance metrics report
# ✓ Quality assessment report
# ✓ Trend analysis (30-day)
# ✓ Interactive dashboard created

# Create test analytics dashboard
python -m safla.analytics --testing \
  --real-time-metrics \
  --historical-trends \
  --predictive-analysis \
  --export analytics_dashboard/

# Generate stakeholder reports
python -m safla.report --stakeholder \
  --executive-summary \
  --quality-metrics \
  --risk-assessment \
  --recommendations \
  --export stakeholder_reports/
```

#### Test Metrics and KPI Tracking
```bash
# Track testing KPIs
python -m safla.metrics --testing \
  --kpi-tracking \
  --automated-collection \
  --trend-monitoring \
  --alert-configuration \
  --export metrics_tracking.json

# Analyze testing effectiveness
python -m safla.analytics --effectiveness \
  --test-roi-analysis \
  --defect-prevention-metrics \
  --quality-impact-assessment \
  --export effectiveness_analysis.json

# Monitor testing performance
python -m safla.monitor --testing \
  --real-time-metrics \
  --performance-tracking \
  --resource-utilization \
  --export monitoring_dashboard.json
```

### 10. Integration and Workflow Commands

#### Workflow Integration
```bash
# Integrate with development workflow
python -m safla.workflow --integrate-testing \
  --development-workflow \
  --automated-triggers \
  --quality-gates \
  --export workflow_integration.json

# Coordinate with other modes
python -m safla.coordinate --testing \
  --code-mode-integration \
  --critic-mode-collaboration \
  --orchestrator-reporting \
  --export coordination_config.json

# Setup workflow automation
python -m safla.automation --workflow \
  --testing-triggers \
  --result-propagation \
  --failure-handling \
  --export workflow_automation.json
```

#### Task Management and Handoff
```bash
# Prepare task handoff
python -m safla.workflow --prepare-handoff \
  --next-mode code \
  --test-specifications test_specs.json \
  --coverage-requirements coverage_requirements.json \
  --export handoff_package.json

# Complete testing phase
python -m safla.workflow --complete-testing \
  --comprehensive-validation \
  --quality-certification \
  --performance-validation \
  --export completion_report.json

# Transition to next phase
python -m safla.workflow --transition \
  --target-mode critic \
  --artifacts test_results.json \
  --recommendations recommendations.json \
  --export transition_package.json
```

This comprehensive CLI commands documentation provides detailed guidance for leveraging SAFLA's command-line capabilities within the TDD mode, ensuring effective test-driven development through systematic CLI operations and automated workflows.