@inproceedings{svyatkovskiy2022program,
author = {Svyatkovskiy, Alexey and Fakhoury, Sarah and Ghorbani, Negar and Mytkowicz, Todd and Bird, Christian and Jang, Jinu and Sundaresan, Neel and Lahiri, Shuvendu and Dinella, Elizabeth},
title = {Program Merge Conflict Resolution via Neural Transformers},
booktitle = {The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE '22)},
year = {2022},
month = {November},
abstract = {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× performance improvement over existing semi-structured, and 2× 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.},
publisher = {ACM},
url = {http://approjects.co.za/?big=en-us/research/publication/program-merge-conflict-resolution-via-neural-transformers/},
}