用大模型辅助代码审查，减轻开发者负担。
Automated Code Review Using Large Language Models at Ericsson: An Experience Report
- 结合大模型与静态分析构建轻量级审查工具
- 开发者测试显示结果令人鼓舞
- 适合需要提升审查效率的工程团队
代码审查是保障软件发布质量的关键手段，与测试和静态分析并列。然而，高质量的代码审查依赖有经验的开发者，而他们往往缺乏时间进行深入审查。因此，自动化代码审查可减轻资深开发者的认知负担，使其专注于编写新功能和修复漏洞。本文介绍了埃里克森公司使用大语言模型实现代码审查自动化的实践经验。我们开发了一款基于大模型与静态程序分析的轻量级工具，并通过与经验丰富的开发者合作开展初步实验，评估该工具的效果，结果令人鼓舞。
原文摘要 · Abstract (English)
Code review is one of the primary means of assuring the quality of released software along with testing and static analysis. However, code review requires experienced developers who may not always have the time to perform an in-depth review of code. Thus, automating code review can help alleviate the cognitive burden on experienced software developers allowing them to focus on their primary activities of writing code to add new features and fix bugs. In this paper, we describe our experience in using Large Language Models towards automating the code review process in Ericsson. We describe the development of a lightweight tool using LLMs and static program analysis. We then describe our preliminary experiments with experienced developers in evaluating our code review tool and the encouraging results.
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