Variability in Factors Influencing Pull Request Merge Decisions: A Microscopic Exploration
Abstract
Context: The pull-based development model is a widely adopted practice in dis- tributed version control systems, particularly in open-source projects. In this model, con- tributors submit pull requests proposing changes to the codebase, which are then reviewed and potentially merged by project maintainers. Previous studies have extensively investi- gated the influence of different factors in merge outcome, aiming to generalize their impact across multiple projects.
Objective: This thesis takes a unique approach by examining these factors at the project level, aiming to understand how the influence of each factor varies across projects.
Methodology: To achieve this, we conducted a large-scale quantitative analysis on 841,399 pull requests from 1,100 GitHub projects. We constructed fixed-effect logistic regression models for each project and explored the correlations be- tween different factors and merge outcomes.
Results: Our analysis indicates that the influence of factors varies across projects, both in terms of their order and direction. For example, while contributor experience is highly valued in many projects, it was found to be statistically insignificant in others. Likewise, the likelihood of a successful merge increases with the number of commits in some projects, whereas in others, it has the opposite effect. These findings have implications for both researchers and practitioners.
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Cite this version of the work
Nasif Ahmed
(2024).
Variability in Factors Influencing Pull Request Merge Decisions: A Microscopic Exploration. UWSpace.
http://hdl.handle.net/10012/20565
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