Understanding the Impact of Branch Edit Features for the Automatic Prediction of Merge Conflict Resolutions
Pages 149 - 160
Abstract
Developers regularly have to resolve merge conflicts, i.e., two conflicting sets of changes to the same files in different branches, which can be tedious and error-prone. To resolve conflicts, developers typically: keep the local version (KL) or the remote version (KR) of the code. They also sometimes manually edit both versions into a single one (ME). However, most existing techniques only support merging the local and remote versions (the ME strategy).
We recently proposed RPredictor, a machine learning-based approach to support developers in choosing how to resolve a conflict (by KL, KR, or ME), by predicting their resolution strategy. In its original design, RPredictor uses a set of Evolution History Features (EHFs) that capture: the magnitude of the changes in conflict, their evolution, and the experience of the developers involved.
In this paper, we proposed and evaluated a new set of Branch Edit Features (BEFs), that capture the fine-grained edits that were performed on each branch of the conflict. We learned multiple lessons. First, BEFs provided lower effectiveness (F-score) than the original EHFs. Second, combining BEFs with EHFs still did not improve the effectiveness of EHFs, it provided the same f-score. Third, the feature set that provided highest effectiveness in our experiments was the combination of EHFs with a subset of BEFs that captures the number of insertions performed in the local branch, but this combination only improved EHFs by 3 pp. f-score. Finally, our experiments also share the lesson that some feature sets provided higher C-score (i.e., the safety of the technique's mistakes) as a trade-off for lower f-scores. This may be valued by developers and we believe that it should be studied in the future.
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Published In
April 2024
487 pages
ISBN:9798400705861
DOI:10.1145/3643916
- Chair:
- Igor Steinmacher,
- Co-chair:
- Mario Linares-Vasquez,
- Program Chair:
- Kevin Patrick Moran,
- Program Co-chair:
- Olga Baysal
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike International 4.0 License.
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Published: 13 June 2024
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