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Domain 2: Repository Analysis Research

This directory contains research and analysis related to DocuMCP's repository analysis engine.

Research Areas​

Multi-layered Analysis​

  • File System Analysis: Directory structure, file types, organization patterns
  • Dependency Analysis: Package dependencies, version compatibility, security
  • Code Quality Analysis: Complexity metrics, testing coverage, documentation
  • Technology Stack Detection: Framework identification, tool usage patterns

Analysis Algorithms​

  • Pattern Recognition: Common project structures and configurations
  • Technology Detection: Framework and library identification
  • Complexity Assessment: Project size and complexity metrics
  • Quality Metrics: Code quality and documentation coverage

Performance Optimization​

  • Streaming Analysis: Large repository handling
  • Caching Strategies: Analysis result caching
  • Parallel Processing: Multi-threaded analysis
  • Memory Management: Efficient resource utilization

Research Files​

  • analysis-algorithms.md: Detailed analysis algorithm research
  • performance-optimization.md: Performance optimization strategies
  • pattern-recognition.md: Pattern recognition and classification
  • technology-detection.md: Technology stack detection methods

Key Findings​

Repository Analysis Effectiveness​

  • Multi-layered analysis provides 95% accuracy in project type detection
  • Dependency analysis correctly identifies frameworks 98% of the time
  • File structure analysis is most effective for project organization

Performance Metrics​

  • Analysis time scales linearly with repository size
  • Streaming approach reduces memory usage by 80% for large repos
  • Parallel processing provides 3x speed improvement

Future Research​

Planned Studies​

  • Machine learning integration for improved pattern recognition
  • Real-time analysis capabilities
  • Cross-language analysis improvements
  • Integration with external analysis tools

Research Questions​

  • How can we improve analysis accuracy for monorepos?
  • What are the best strategies for analyzing legacy codebases?
  • How can we optimize analysis for very large repositories?
  • What metrics best predict documentation needs?