Modern Code review is one of the most critical tasks in software maintenance and evolution. A rigorous code review leads to fewer bugs and reduced overall maintenance costs. Most existing studies focus on automatically identifying the most qualified reviewers, based on their expertise, to review pull-up requests. However, the management of code reviews is a complex problem in practice due to a project’s limited resources, including the availability of peer reviewers. Furthermore, the history of collaborations between developers and reviewers could affect the quality of the reviews, in positive or negative ways. In this paper, we formulate the recommendation of code reviewers as a multi-objective search problem to balance the conflicting objectives of expertise, availability, and history of collaborations. Our validation confirms the effectiveness of our multi-objective approach on 9 open source projects by making better recommendations, on average, than the state of the art.

中文翻译：

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多目标代码审查员建议：平衡专业知识、可用性和协作

现代代码审查是软件维护和发展中最关键的任务之一。严格的代码审查可以减少错误并降低总体维护成本。大多数现有研究都侧重于根据他们的专业知识自动识别最合格的审稿人，以审阅 pull-up 请求。然而，由于项目的资源有限，包括同行评审员的可用性，代码审查的管理在实践中是一个复杂的问题。此外，开发人员和评论者之间的合作历史可能会以积极或消极的方式影响评论的质量。在本文中，我们将代码审查者的建议制定为一个多目标搜索问题，以平衡专业知识、可用性和合作历史的冲突目标。