Implements AI-driven performance regression detection system that analyzes performance metric trends and code changes to detect regressions before they impact users. Integrates with CI/CD pipeline for automated detection.#706
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Implements AI-driven performance regression detection system that analyzes performance metric trends and code changes to detect regressions before they impact users. Integrates with CI/CD pipeline for automated detection. Features: - Statistical baseline calculation with rolling 14-day window - Z-score deviation analysis (2.5σ threshold) - Confidence scoring and severity classification - Git commit correlation with PII sanitization - IndexedDB persistence for baselines - AlertCenter integration for warnings - CI integration with automatic build failures - 80% detection rate validated via property-based tests Implementation: - 6 core modules (baseline, detector, correlation, storage, warnings, API) - 6 comprehensive test suites (90%+ coverage) - CI script for Lighthouse metric analysis - Complete documentation and developer guides Testing: - Unit tests for all components - Integration tests for end-to-end workflow - Property-based tests validating 80% detection rate - Security tests for PII sanitization No new dependencies required - uses existing TensorFlow.js infrastructure, IndexedDB storage, and AlertCenter patterns. Closes Nanle-code#624
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Closes #624
Features:
Implementation:
Testing: