arXiv:2403.14274 공식 코드 · Papers with Code

Multi-role Consensus through LLMs Discussions for Vulnerability Detection

Zhenyu Mao, Jialong Li, Dongming Jin, Munan Li, Kenji Tei

제출 2024-03-21

원문 초록

Recent advancements in large language models (LLMs) have highlighted the potential for vulnerability detection, a crucial component of software quality assurance. Despite this progress, most studies have been limited to the perspective of a single role, usually testers, lacking diverse viewpoints from different roles in a typical software development life-cycle, including both developers and testers. To this end, this paper introduces a multi-role approach to employ LLMs to act as different roles simulating a real-life code review process and engaging in discussions toward a consensus on the existence and classification of vulnerabilities in the code. Preliminary evaluation of this approach indicates a 13.48% increase in the precision rate, an 18.25% increase in the recall rate, and a 16.13% increase in the F1 score.

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