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Striking a balance

Akshay Utture, Shuyang Liu, Christian Gram Kalhauge, Jens Palsberg

2022Proceedings of the 44th International Conference on Software Engineering18 citationsDOIOpen Access PDF

Abstract

Researchers have reported that static analysis tools rarely achieve a false-positive rate that would make them attractive to developers. We overcome this problem by a technique that leads to reporting fewer bugs but also much fewer false positives. Our technique prunes the static call graph that sits at the core of many static analyses. Specifically, static call-graph construction proceeds as usual, after which a call-graph pruner removes many false-positive edges but few true edges. The challenge is to strike a balance between being aggressive in removing false-positive edges but not so aggressive that no true edges remain. We achieve this goal by automatically producing a call-graph pruner through an automatic, ahead-of-time learning process. We added such a call-graph pruner to a software tool for null-pointer analysis and found that the falsepositive rate decreased from 73% to 23%. This improvement makes the tool more useful to developers.

Topics & Concepts

False positive paradoxComputer scienceCall graphGraphStatic analysisPointer (user interface)SoftwareFalse positives and false negativesTheoretical computer scienceData miningProgramming languageMachine learningArtificial intelligenceSoftware Testing and Debugging TechniquesSoftware Engineering ResearchAdvanced Malware Detection Techniques
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