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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Veröffentlicht in:	Proceedings of ACM on programming languages Jg. 8; H. OOPSLA1; S. 474 - 499
Hauptverfasser:	Li, Haonan, Hao, Yu, Zhai, Yizhuo, Qian, Zhiyun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY, USA ACM 29.04.2024
Schlagworte:	Automated static analysis Computing methodologies Natural language processing Security and privacy Software and its engineering Systems security large language model Static analysis bug detection
ISSN:	2475-1421, 2475-1421
Online-Zugang:	Volltext
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