⚡ Performance testing with large repositories

[oscarvalenzuelab]

Description

Develop performance benchmarks and stress tests to ensure the tool scales efficiently with large repositories and directory structures, identifying bottlenecks and optimization opportunities.

Acceptance Criteria

• Create performance test suite in tests/performance/
• Benchmark SWHID generation with large directory trees
• Test API client performance with high request volumes
• Measure directory scanning performance with deep hierarchies
• Test fuzzy matching performance with large datasets
• Benchmark memory usage during processing
• Create performance regression tests
• Test with real large repositories:
  • Linux kernel source tree
  • Chromium source code
  • Large monorepos (Google, Facebook style)
• Measure and document performance baselines
• Identify and document performance bottlenecks
• Create performance optimization recommendations
• Set up automated performance monitoring in CI/CD

Technical Notes

• Use memory profiling tools (memory_profiler, pympler)
• Consider using line_profiler for detailed performance analysis
• Test with various repository sizes and structures
• Document hardware requirements and recommendations

Priority

Medium

Labels

testing, performance, optimization