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 an approach to employ LLMs to act as different roles to simulate real-life code review process, engaging in discussions towards a consensus on the existence and classification of vulnerabilities in the code. Preliminary evaluation of the proposed approach indicates a 4.73% increase in the precision rate, 58.9% increase in the recall rate, and a 28.1% increase in the F1 score.

翻译：近期大语言模型（LLM）的进展凸显了其在漏洞检测领域的潜力，这是软件质量保证的关键环节。尽管取得进展，现有研究大多局限于单一角色（通常为测试人员）的视角，缺乏典型软件开发生命周期中不同角色（包括开发人员和测试人员）的多元化观点。为此，本文提出一种方法，利用LLM扮演不同角色模拟真实代码审查流程，通过讨论达成关于代码中漏洞存在性及分类的共识。初步评估表明，该方法在精确率上提升4.73%，召回率提升58.9%，F1分数提升28.1%。