Publication | Closed Access
An exploratory study of the pull-based software development model
599
Citations
34
References
2014
Year
Unknown Venue
Software MaintenanceExploratory StudyEngineeringProject ManagementDistributed DevelopmentSoftware EngineeringPull RequestSoftware AnalysisEmpirical Software Engineering ResearchOpen-source Software DevelopmentOpen-source SystemSystems EngineeringSoftware PracticeSoftware Development ProcessDesignSoftware DesignSoftware DevelopmentProgram AnalysisDevelopment MethodologySoftware TestingBusinessPull Request Rejection
Distributed version control systems have enabled a pull‑based development paradigm, and platforms such as GitHub support it with code‑review and issue‑tracking tools. The study investigates how pull‑based software development operates by analyzing the GHTorrent corpus and a curated sample of 291 projects. The authors analyze pull‑based development using data from the GHTorrent corpus and a selected set of 291 projects. The analysis shows that the pull‑request model delivers fast turnaround, greater community engagement, and shorter integration times, while only a few factors influence merge decisions and processing time, and technical rejections are rare.
The advent of distributed version control systems has led to the development of a new paradigm for distributed software development; instead of pushing changes to a central repository, developers pull them from other repositories and merge them locally. Various code hosting sites, notably Github, have tapped on the opportunity to facilitate pull-based development by offering workflow support tools, such as code reviewing systems and integrated issue trackers. In this work, we explore how pull-based software development works, first on the GHTorrent corpus and then on a carefully selected sample of 291 projects. We find that the pull request model offers fast turnaround, increased opportunities for community engagement and decreased time to incorporate contributions. We show that a relatively small number of factors affect both the decision to merge a pull request and the time to process it. We also examine the reasons for pull request rejection and find that technical ones are only a small minority.
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