Enhancing Static Analysis for Practical Bug Detection: An LLM-Integrated Approach

While static analysis is instrumental in uncovering software bugs, its precision in analyzing large and intricate codebases remains challenging. The emerging prowess of Large Language Models (LLMs) offers a promising avenue to address these complexities. In this paper, we present LLift, a pioneering...

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Bibliographic Details
Published in:Proceedings of ACM on programming languages 2024-04, Vol.8 (OOPSLA1), p.474-499, Article 111
Main Authors: Li, Haonan, Hao, Yu, Zhai, Yizhuo, Qian, Zhiyun
Format: Article
Language:English
Subjects:
Automated static analysis
Computing methodologies
Natural language processing
Security and privacy
Software and its engineering
Systems security
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