Automatic Generation of Pull Request DescriptionsACM SIGSOFT Distinguished Paper Award
Enabled by the pull-based development model, developers can easily contribute to a project through pull requests (PRs). When creating a PR, developers can add a free-form description to describe what changes made in this PR and/or why. Such a description is helpful for reviewers and other developers to gain a quick understanding of the PR without touching the details and may reduce the possibility of the PR being ignored or rejected. However, developers sometimes neglect to write descriptions for PRs. For example, in our collected dataset with over 333K PRs, more than 34% of the PR descriptions are empty. To alleviate this problem, we propose an approach to automatically generate PR descriptions based on the commit messages and the source code comments in the PRs. We regard this problem as a text summarization problem and solve it using a novel sequence-to-sequence model. To cope with out-of-vocabulary words in software artifacts and bridge the gap between the training loss function of the sequence-to-sequence model and the evaluation metric ROUGE, which has been shown to correspond to human evaluation, we integrate the pointer generator and directly optimize for ROUGE using reinforcement learning and a special loss function. We build a dataset with over 41K PRs and evaluate our approach on this dataset through ROUGE and a human evaluation. Our evaluation results show that our approach outperforms two baselines by significant margins.
Tue 12 Nov
13:40 - 15:20: Papers - Natural Language and Human Aspects at Cortez 2&3 Chair(s): Bogdan VasilescuCarnegie Mellon University | ||||||||||||||||||||||||||||||||||||||||||
| 13:40 - 14:00 Talk | Discovering, Explaining and Summarizing Controversial Discussions in Community Q&A Sites Xiaoxue RenZhejiang University, Zhenchang XingAustralia National University, Xin XiaMonash University, Guoqiang LiShanghai Jiao Tong University, Jianling SunZhejiang University Pre-print | |||||||||||||||||||||||||||||||||||||||||
| 14:00 - 14:20 Talk | Automating App Review Response Generation Cuiyun GaoNanyang Technological University, Singapore, Jichuan ZengThe Chinese University of Hong Kong, Xin XiaMonash University, David LoSingapore Management University, Michael LyuThe Chinese University of Hong Kong, Irwin KingThe Chinese University of Hong Kong Pre-print | |||||||||||||||||||||||||||||||||||||||||
| 14:20 - 14:40 Talk | Automatic Generation of Pull Request DescriptionsACM SIGSOFT Distinguished Paper Award Zhongxin LiuZhejiang University, Xin XiaMonash University, Christoph TreudeThe University of Adelaide, David LoSingapore Management University, Shanping LiZhejiang University Pre-print | |||||||||||||||||||||||||||||||||||||||||
| 14:40 - 15:00 Talk | Recommending Who to Follow in the Software Engineering Twitter Space Abhishek Sharma Singapore Management University, Singapore, Yuan TianQueens University, Kingston, Canada, Agus SulistyaSchool of Information Systems, Singapore Management University, Dinusha WijedasaSchool of Information Systems, Singapore Management University, David LoSingapore Management University Pre-print | |||||||||||||||||||||||||||||||||||||||||
| 15:00 - 15:10 Demonstration | Developer Reputation Estimator (DRE) Sadika AmreenUniversity of Tennessee Knoxville, Andrey KarnauchUniversity of Tennessee Knoxville, Audris MockusUniversity of Tennessee - Knoxville | |||||||||||||||||||||||||||||||||||||||||
| 15:10 - 15:20 Demonstration | CocoQa: Question Answering for Coding Conventions over Knowledge Graphs Tianjiao DuShanghai JiaoTong University, Junming CaoShanghai JiaoTong University, Qinyue WuShanghai JiaoTong University, Wei LiShanghai JiaoTong University, Beijun ShenSchool of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Yuting ChenShanghai Jiao Tong University | |||||||||||||||||||||||||||||||||||||||||