@unpublished{svyatkovskiy2021mergebert,
author = {Svyatkovskiy, Alexey and Mytkowicz, Todd and Ghorbani, Negar and Fakhoury, Sarah and Dinella, Elizabeth and Bird, Christian and Sundaresan, Neel and Lahiri, Shuvendu},
title = {MergeBERT: Program Merge Conflict Resolution via Neural Transformers},
year = {2021},
month = {August},
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.
In this paper, we introduce MergeBERT, a novel neural program merge framework based on the token-level three-way differencing and a transformer encoder model. Exploiting 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 64--69% precision of merge resolution synthesis, yielding nearly a 2x performance improvement over existing structured and neural program merge tools. Finally, we demonstrate versatility of our model, which is able to perform program merge in a multilingual setting with Java, JavaScript, TypeScript, and C# programming languages, generalizing zero-shot to unseen languages.},
url = {http://approjects.co.za/?big=en-us/research/publication/mergebert-program-merge-conflict-resolution-via-neural-transformers/},
}