Affiliation:
1. KAIST, Daejeon, Yuseong-gu, Daejeon, Republic of Korea
Abstract
Understanding program behaviors is important to verify program properties or to optimize programs. Static analysis is a widely used technique to approximate program behaviors via abstract interpretation. To evaluate the quality of static analysis, researchers have used three metrics: performance, precision, and soundness. The static analysis quality depends on the analysis techniques used, but the best combination of such techniques may be different for different programs. To find the best combination of analysis techniques for specific programs, recent work has proposed
parametric static analysis
. It considers static analysis as black-box parameterized by
analysis parameters
, which are techniques that may be configured without analysis details. We formally define the parametric static analysis, and we survey analysis parameters and their parameter selection in the literature. We also discuss open challenges and future directions of the parametric static analysis.
Funder
National Research Foundation of Korea
Publisher
Association for Computing Machinery (ACM)
Subject
General Computer Science,Theoretical Computer Science
Reference121 articles.
1. Miltiadis Allamanis Marc Brockschmidt and Mahmoud Khademi. 2018. Learning to represent programs with graphs. (2018). Miltiadis Allamanis Marc Brockschmidt and Mahmoud Khademi. 2018. Learning to represent programs with graphs. (2018).
2. An introduction to MCMC for machine learning;Andrieu Christophe;Mach. Learn.,2003
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. A New Deepfake Detection Method Based on Compound Scaling Dual-Stream Attention Network;EAI Endorsed Transactions on Pervasive Health and Technology;2024-07-18
2. When to Stop Going Down the Rabbit Hole: Taming Context-Sensitivity on the Fly;Proceedings of the 13th ACM SIGPLAN International Workshop on the State Of the Art in Program Analysis;2024-06-20
3. Enhancing Static Analysis for Practical Bug Detection: An LLM-Integrated Approach;Proceedings of the ACM on Programming Languages;2024-04-29
4. Assisting Static Analysis with Large Language Models: A ChatGPT Experiment;Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering;2023-11-30
5. Learning to Boost Disjunctive Static Bug-Finders;2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE);2023-05