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ESEC/FSE 2022
Mon 14 - Fri 18 November 2022 Singapore
Wed 16 Nov 2022 11:45 - 12:00 at SRC LT 51 - Collaboration Chair(s): Paul Marinescu

Collaborative software development is an integral part of the modern software development life cycle, essential to the success of large-scale software projects. When multiple developers make concurrent changes around the same lines of code, a merge conflict may occur. Such conflicts stall pull requests and continuous integration pipelines for hours to several days, seriously hurting developer productivity. To address this problem, we introduce MergeBERT, a novel neural program merge framework based on token-level three-way differencing and a transformer encoder model. By exploiting the restricted nature of merge conflict resolutions, we reformulate the task of generating the resolution sequence as a classification task over a set of primitive merge patterns extracted from real-world merge commit data. Our model achieves 63–68% accuracy for merge resolution synthesis, yielding nearly a 3$\times$ performance improvement over existing semi-structured, and 2$\times$ improvement over neural program merge tools. Finally, we demonstrate that MergeBERT is sufficiently flexible to work with source code files in Java, JavaScript, TypeScript, and C# programming languages.
To measure the practical use of MergeBERT, we conduct a user study to evaluate MergeBERT suggestions with 25 developers from large OSS projects on 122 real-world conflicts they encountered. Results suggest that in practice, MergeBERT resolutions would be accepted at a higher rate than estimated by automatic metrics for precision and accuracy. Additionally, we use participant feedback to identify future avenues for improvement of MergeBERT.

Wed 16 Nov

Displayed time zone: Beijing, Chongqing, Hong Kong, Urumqi change

11:00 - 12:30
CollaborationIndustry Paper / Research Papers at SRC LT 51
Chair(s): Paul Marinescu Meta
11:00
15m
Talk
Workgraph: Personal Focus vs. Interruption for Engineers at Meta
Industry Paper
Yifen Chen Meta, Peter Rigby Concordia University; Meta, Yulin Chen Meta, Kun Jiang Meta, Nader Dehghani Meta, Qianying Huang Meta, Peter Cottle Meta, Clayton Andrews Meta, Noah Lee Meta, Nachiappan Nagappan Facebook
DOI
11:15
15m
Talk
Understanding Automated Code Review Process and Developer Experience in Industry
Industry Paper
Hyungjin Kim Samsung Research, Yonghwi Kwon Samsung Research, Sangwoo Joh Samsung Research, Hyukin Kwon Samsung Research, Yeonhee Ryou Samsung Research, Taeksu Kim Samsung Research
DOI
11:30
15m
Talk
Software Security during Modern Code Review: The Developer’s Perspective
Research Papers
Larissa Braz University of Zurich, Alberto Bacchelli University of Zurich
DOI Pre-print Media Attached
11:45
15m
Talk
Program Merge Conflict Resolution via Neural Transformers
Research Papers
Alexey Svyatkovskiy Microsoft, Sarah Fakhoury Washington State University, Negar Ghorbani University of California at Irvine, Todd Mytkowicz Microsoft Research, Elizabeth Dinella University of Pennsylvania, Christian Bird Microsoft Research, Jinu Jang Microsoft, Neel Sundaresan Microsoft, Shuvendu K. Lahiri Microsoft Research
DOI