Result Invalidation for Incremental Modular Analyses

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Introduces three concrete invalidation strategies—component invalidation, dependency invalidation, and provenance-based write invalidation—and interleaves invalidation with recomputation in an effect‑driven modular incremental analyzer. Implements provenance tracking so store entries can be retracted or non‑monotonically updated, evaluates on a curated suite and a generated suite (190 programs × 5 edits), and measures precision and time. Precision improves (many benchmarks raise fully‑precise addresses from ~20% up toward ~50%), incremental updates stay ~5× faster on curated cases, but write invalidation can trigger reanalysis and cause massive slowdowns (up to 100–1000×) on edits that drastically change program behavior.

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" chapters (18)

1. 0:00Introduction
2. 1:24Motivation for incremental modular analysis
3. 2:28Limitations of prior approaches
4. 3:30Effect-driven modular analysis
5. 7:05Analysis result components
6. 7:25Prior incrementalization drawbacks
7. 9:11Invalidation and recomputation
8. 9:53Interleaving recomputation
9. 10:13Component invalidation strategy
10. 10:57Dependency invalidation strategy
11. 12:01Write invalidation and provenance
12. 15:14Write invalidation on deletion
13. 15:56Evaluation setup and benchmarks
14. 17:03Precision improvement results
15. 18:24Impact on update speed
16. 19:28Comparison with full analysis
17. 20:30Summary of techniques
18. 20:53Q&A