一句话：提出并部署 Pull Request 生命周期预测系统，为开发者提供个体工作量估算并加速 PR 完成。
软件工程中的工作量估算多聚焦项目级，较少关注单个 Pull Request（代码提交）级别。本文提出一种面向开发者单次提交的估算方法，构建 Pull Request 生命周期预测系统，并将预测结果展示给开发者以帮助跟踪工作项。由于公司普遍采用云开发基础设施，作者将该系统部署到多个软件家族、数千名开发者中。部署结果显示，PR 生命周期预测系统可通过加速 PR 完成来保守地节省 44.61% 的开发者时间，表明个体级工作量估算在实际开发流程中具有应用价值。
Effort estimation models have been long studied in software engineering research. Effort estimation models help organizations and individuals plan and track progress of their software projects and individual tasks to help plan delivery milestones better. Towards this end, there is a large body of work that has been done on effort estimation for projects but little work on an individual checkin (Pull Request) level. In this paper we present a methodology that provides effort estimates on individual developer check-ins which is displayed to developers to help them track their work items. Given the cloud development infrastructure pervasive in companies, it has enabled us to deploy our Pull Request Lifetime prediction system to several thousand developers across multiple software families. We observe from our deployment that the pull request lifetime prediction system conservatively helps save 44.61% of the developer time by accelerating Pull Requests to completion.
DOI 原文 ·
@inproceedings{paperbot5086,
title = {Predicting pull request completion time: a case study on large scale cloud services},
author = {Chandra Maddila and Chetan Bansal and Nachiappan Nagappan},
booktitle = {FSE},
year = {2019},
doi = {10.1145/3338906.3340457}
}