An exploratory study of the pull-based software development model

By Georgios Gousios, Martin Pinzger, Arie van Deursen. International Conference on Software Engineering, 2014

653 citations recorded by the source corpus.

Subfields: Computer Science Applications, Information Systems

View Paper: https://www.semanticscholar.org/paper/79d0909c84fbf4e0fba60ecc235192183fecc8c1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Science Applications

In Information Systems

Citations in the corpus

Understanding the Factors That Impact the Popularity of GitHub Repositories (2016, background): “These patterns can help developers to understand how their systems have grown in the a r X i v : 1606 .”
An in-depth study of the promises and perils of mining GitHub (2015, methodology): “Quantitative studies (Gousios et al. 2014; Takhteyev and Hilts 2010; Thung et al. 2013; Tsay et al. 2012) have attempted to systematically archive GitHub’s publicly available data and use it to investigate development practices and network structure in the GitHub environment.”
Gender differences and bias in open source: pull request acceptance of women versus men (2017, background): “Second, the larger a pull request is, the less likely it is to be accepted [13].”
Quality and productivity outcomes relating to continuous integration in GitHub (2015, background): “By “decoupling the development effort from the decision to incorporate the results of the development in the code base” [17], the pull-based model also offers an unprecedentedly low barrier to entry for potential contributors (i.”
Deep Code Search (2018, methodology): “Besides code search, there have been many other information retrieval tasks in software engineering [8, 9, 16, 23, 24, 29, 51, 55, 63, 67] such as bug localization [66, 73, 80], feature localization [19], traceability links recovery [20] and community Question Answering [11].”
A Neural Architecture for Generating Natural Language Descriptions from Source Code Changes (2017, methodology): “lions of lines code are written in a distributed and asynchronous way (Gousios et al., 2014).”
Work Practices and Challenges in Pull-Based Development: The Contributor's Perspective (2014, methodology): “Recent quantitative work identiﬁed that, across projects, simple factors such as the recent activity of the project area affected by the contribution [1] and social distance between the contributor and the integrator [14] can be used to predict whether a contribution will be accepted or not.”