Mon 16 Jan 2023 11:30 - 12:00 at Arlington - Static Analysis Chair(s): Xavier Rival

To reduce the running time of static analysis tools upon program changes, incremental static analyses reuse and update pre-existing results. Such analyses must efficiently detect and remove outdated results. We introduce three novel, complementary result invalidation strategies for incremental modular analyses. The core idea of our work is to alternate invalidation with computation. We apply our strategies to a recent, state-of-the-art incremental modular analysis that suffers from imprecision, and evaluate them on soundness, precision, and performance. Our strategies lead to precision improvements compared to an incremental analysis without invalidation, though the precision of a full reanalysis is not yet matched. On most benchmarks, our incremental analysis performs well. However, on some benchmarks our analysis performs poorly as the changes drastically change program behaviour, for which the changes are difficult for an incremental analysis to handle.

Mon 16 Jan

Displayed time zone: Eastern Time (US & Canada) change

11:00 - 12:30
Static AnalysisVMCAI at Arlington
Chair(s): Xavier Rival Inria; ENS; CNRS; PSL University
11:00
30m
Talk
Efficient Interprocedural Data-Flow Analysis using Treedepth and Treewidth
VMCAI
Amir Kafshdar Goharshady IST Austria, Austria, Ahmed Khaled Zaher HKUST
11:30
30m
Talk
Result Invalidation for Incremental Modular Analyses
VMCAI
Jens Van der Plas Software Languages Lab, Vrije Universiteit Brussel, Quentin Stiévenart Vrije Universiteit Brussel, Coen De Roover Vrije Universiteit Brussel
12:00
30m
Talk
Symbolic Abstract Heaps for Polymorphic Information-flow Guard Inference
VMCAI
Nicolas Berthier OCamlPro, Narges Khakpour Linnaeus University