Build Data-Driven Testing & Quality Assurance Infrastructure #50

Overview

This issue proposes the development of a comprehensive, data-driven testing and quality assurance infrastructure for FEAScript-core, focused on scientific computing reliability, performance, and maintainability.

Goals

• Implement automated performance benchmarking with systematic data collection
• Establish regression testing pipelines with numerical result validation
• Design and integrate memory usage monitoring and reporting systems
• Develop continuous integration analytics for tracking code quality and test coverage

Proposed Tasks

1. Performance Benchmarking

   • Create benchmarks for solvers, mesh generators, and visualization routines
   • Collect and store performance metrics (e.g., runtime, peak memory usage, result accuracy)
   • Automate benchmark runs in CI

2. Regression Testing

   • Setup test suites for key algorithms (e.g., solvers, mesh importers)
   • Validate numerical results against known benchmarks and previous releases
   • Report and visualize regression trends in CI

3. Memory Usage Monitoring

   • Integrate lightweight memory profiling tools for both CPU and WebGPU workflows
   • Store historical memory metrics for large mesh runs
   • Alert on excessive memory growth or leaks

4. Continuous Integration Data Analytics

   • Collect and visualize code coverage, test pass rates, and performance trends
   • Integrate analytics dashboards (e.g., with GitHub Actions, Codecov)
   • Use data insights to guide future development and refactoring

Impact

This initiative will greatly improve the reliability, efficiency, and scalability of FEAScript-core, helping contributors maintain high scientific and technical standards as the project evolves.