Pull Request Decisions Explained: An Empirical Overview

Context : The pull-based development model is widely used in open source projects, leading to the emergence of trends in distributed software development. One aspect that has garnered significant attention concerning pull request decisions is the identification of explanatory factors. Objective : Th...

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Published in:	IEEE transactions on software engineering Vol. 49; no. 2; pp. 849 - 871
Main Authors:	Zhang, Xunhui, Yu, Yue, Gousios, Georgios, Rastogi, Ayushi
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.02.2023 IEEE Computer Society
Subjects:	Bibliographies Context Data mining Data models Decisions distributed software development GitHub Internet Literature reviews Project development pull request decision Pull-based development Regression models Software Software development Software development management Systematics
ISSN:	0098-5589, 1939-3520
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Abstract	Context : The pull-based development model is widely used in open source projects, leading to the emergence of trends in distributed software development. One aspect that has garnered significant attention concerning pull request decisions is the identification of explanatory factors. Objective : This study builds on a decade of research on pull request decisions and provides further insights. We empirically investigate how factors influence pull request decisions and the scenarios that change the influence of such factors. Method : We identify factors influencing pull request decisions on GitHub through a systematic literature review and infer them by mining archival data. We collect a total of 3,347,937 pull requests with 95 features from 11,230 diverse projects on GitHub. Using these data, we explore the relations among the factors and build mixed effects logistic regression models to empirically explain pull request decisions. Results : Our study shows that a small number of factors explain pull request decisions, with that concerning whether the integrator is the same as or different from the submitter being the most important factor. We also note that the influence of factors on pull request decisions change with a change in context; e.g., the area hotness of pull request is important only in the early stage of project development, however it becomes unimportant for pull request decisions as projects become mature.
AbstractList	Context : The pull-based development model is widely used in open source projects, leading to the emergence of trends in distributed software development. One aspect that has garnered significant attention concerning pull request decisions is the identification of explanatory factors. Objective : This study builds on a decade of research on pull request decisions and provides further insights. We empirically investigate how factors influence pull request decisions and the scenarios that change the influence of such factors. Method : We identify factors influencing pull request decisions on GitHub through a systematic literature review and infer them by mining archival data. We collect a total of 3,347,937 pull requests with 95 features from 11,230 diverse projects on GitHub. Using these data, we explore the relations among the factors and build mixed effects logistic regression models to empirically explain pull request decisions. Results : Our study shows that a small number of factors explain pull request decisions, with that concerning whether the integrator is the same as or different from the submitter being the most important factor. We also note that the influence of factors on pull request decisions change with a change in context; e.g., the area hotness of pull request is important only in the early stage of project development, however it becomes unimportant for pull request decisions as projects become mature.
Author	Yu, Yue Rastogi, Ayushi Gousios, Georgios Zhang, Xunhui
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SubjectTerms	Bibliographies Context Data mining Data models Decisions distributed software development GitHub Internet Literature reviews Project development pull request decision Pull-based development Regression models Software Software development Software development management Systematics
Title	Pull Request Decisions Explained: An Empirical Overview
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