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Nudge: Accelerating Overdue Pull Requests Towards Completion
arXiv - CS - Software Engineering Pub Date : 2020-11-25 , DOI: arxiv-2011.12468
Chandra Maddila, Sai Surya Upadrasta, Chetan Bansal, Nachiappan Nagappan, Georgios Gousios, Arie van Deursen

Pull requests are a key part of the collaborative software development and code review process today. However, pull requests can also slow down the software development process when the reviewer(s) or the author do not actively engage with the pull request. In this work, we design an end-to-end service, Nudge, for accelerating overdue pull requests towards completion by reminding the author or the reviewer(s) to engage with their overdue pull requests. First, we use models based on effort estimation and machine learning to predict the completion time for a given pull request. Second, we use activity detection to reduce false positives. Lastly, we use dependency determination to understand the blocker of the pull request and nudge the appropriate actor(author or reviewer(s)). We also do a correlation analysis to understand the statistical relationship between the pull request completion times and various pull request and developer related attributes. Nudge has been deployed on 147 repositories at Microsoft since 2019. We do a large scale evaluation based on the implicit and explicit feedback we received from sending the Nudge notifications on 8,500 pull requests. We observe significant reduction in completion time, by over 60%, for pull requests which were nudged thus increasing the efficiency of the code review process and accelerating the pull request progression.

中文翻译:

轻推:加速完成请求的过期请求

拉取请求是当今协作软件开发和代码审查过程的关键部分。但是,当审阅者或作者未积极参与拉取请求时,拉取请求也可能减慢软件开发过程。在这项工作中,我们设计了一个端到端服务Nudge,通过提醒作者或审阅者处理其过期请求,来加速过期请求的完成。首先,我们使用基于工作量估计和机器学习的模型来预测给定拉动请求的完成时间。其次,我们使用活动检测来减少误报。最后,我们使用依赖性确定来了解拉取请求的阻止者,并微调适当的参与者(作者或审阅者)。我们还进行了相关分析,以了解拉取请求完成时间与各种拉取请求和开发人员相关属性之间的统计关系。自2019年以来,Nudge已在Microsoft的147个存储库中部署。我们根据从发送有关8,500个拉取请求的Nudge通知中获得的隐式和显式反馈,进行了大规模评估。我们发现被拉动的拉取请求的完成时间显着减少了60%以上,从而提高了代码审查过程的效率并加快了拉取请求的进度。我们根据在8,500个拉取请求上发送Nudge通知所收到的隐式和显式反馈,进行了大规模评估。我们发现被拉动的拉取请求的完成时间显着减少了60%以上,从而提高了代码审查过程的效率并加快了拉取请求的进度。我们根据在8,500个拉取请求上发送Nudge通知所收到的隐式和显式反馈,进行了大规模评估。我们发现被拉动的拉取请求的完成时间显着减少了60%以上,从而提高了代码审查过程的效率并加快了拉取请求的进度。
更新日期:2020-11-27
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