Summary
Implement comprehensive automated regression testing infrastructure to ensure that system updates, model changes, and new features don't degrade existing functionality or accuracy.
Description
Build an automated regression testing framework that runs continuously against all benchmark datasets, tracks performance over time, and alerts on any degradation. This system should enable confident deployment of updates while maintaining quality standards across all evaluation dimensions.
Key Features
- Automated Test Execution: Run all benchmark suites on every significant code change
- Performance Tracking: Monitor metrics over time with trend analysis
- Degradation Detection: Automatic alerts when metrics drop below thresholds
- Baseline Management: Version-controlled baseline results for comparison
- Differential Analysis: Compare performance between versions/models
- CI/CD Integration: Block deployments that fail regression criteria
Technical Requirements
- Integration with all existing benchmark datasets
- Automated test scheduling and execution pipeline
- Metrics storage and visualization dashboard
- Configurable alert thresholds per metric
- Git integration for version tracking
- Parallel test execution for efficiency
- Detailed failure reports with example breakdowns
Success Criteria
- All benchmark suites execute automatically on PR creation
- Test execution time <30 minutes for full suite
- Alert accuracy >95% (true positives for real regressions)
- Zero false deployments (degraded versions reaching production)
- Trend visualization available for all key metrics
- Baseline update process automated and documented
Dependencies
Summary
Implement comprehensive automated regression testing infrastructure to ensure that system updates, model changes, and new features don't degrade existing functionality or accuracy.
Description
Build an automated regression testing framework that runs continuously against all benchmark datasets, tracks performance over time, and alerts on any degradation. This system should enable confident deployment of updates while maintaining quality standards across all evaluation dimensions.
Key Features
Technical Requirements
Success Criteria
Dependencies