Please use this identifier to cite or link to this item: doi:10.22028/D291-41530
Title: Predicting merge conflicts considering social and technical assets
Author(s): Vale, Gustavo
Costa, Heitor
Apel, Sven
Language: English
Title: Empirical Software Engineering
Volume: 29 (2024)
Issue: 1
Publisher/Platform: Springer Nature
Year of Publication: 2023
Free key words: Collaborative software development
Version control systems
Developers role
Three-way merge
Merge conflicts
DDC notations: 004 Computer science, internet
Publikation type: Journal Article
Abstract: Concurrent contributions to a code base may introduce merge conflicts. Whereas merge conflicts are easy and common to introduce, resolving them is a difficult, time-consuming, and often error-prone task. Previous research concentrated on the emergence of merge conflicts considering technical assets in their analyses and often ignored the social perspective (e.g., developer roles). Our goal is to understand and predict merge conflicts considering social and technical assets. We devise three models for predicting merge conflicts based on common measures used by developers. The first model focuses on the social assets, the second on technical assets, and the third on technical and social assets. To evaluate our predictors, we report on a large-scale empirical study analyzing the histories of 66 real-world software systems. Specifically, we categorize developers into top or occasional contributors at project and merge-scenario level. We found that top contributors at project level and occasional contributors at merge-scenario level cause more merge conflicts than the other roles. Hence, the coordination of top contributors at project level and occasional contributors at merge-scenario level is a good starting point to minimize the occurrence of merge conflicts (especially because when these two developers work on the source branch, the chances of merge conflicts are 32.31%). Overall, we show that predicting merge conflicts incorporating developer roles is possible in practice with high accuracy (0.92) and recall (1.00) when combining technical and social assets, which is vital information to guide improvements on speculative merging techniques.
DOI of the first publication: 10.1007/s10664-023-10395-8
URL of the first publication: https://link.springer.com/article/10.1007/s10664-023-10395-8
Link to this record: urn:nbn:de:bsz:291--ds-415306
hdl:20.500.11880/37205
http://dx.doi.org/10.22028/D291-41530
ISSN: 1573-7616
1382-3256
Date of registration: 30-Jan-2024
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Informatik
Professorship: MI - Prof. Dr. Sven Apel
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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