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An Empirical Analysis of Inferences From Commit, Fork, and Branch Rates of Top GitHub Projects

An Empirical Analysis of Inferences From Commit, Fork, and Branch Rates of Top GitHub Projects

Ekbal Rashid, Mohan Prakash
Copyright: © 2022 |Volume: 13 |Issue: 1 |Pages: 16
ISSN: 1942-3926|EISSN: 1942-3934|EISBN13: 9781683180975|DOI: 10.4018/IJOSSP.300751
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MLA

Rashid, Ekbal, and Mohan Prakash. "An Empirical Analysis of Inferences From Commit, Fork, and Branch Rates of Top GitHub Projects." IJOSSP vol.13, no.1 2022: pp.1-16. http://doi.org/10.4018/IJOSSP.300751

APA

Rashid, E. & Prakash, M. (2022). An Empirical Analysis of Inferences From Commit, Fork, and Branch Rates of Top GitHub Projects. International Journal of Open Source Software and Processes (IJOSSP), 13(1), 1-16. http://doi.org/10.4018/IJOSSP.300751

Chicago

Rashid, Ekbal, and Mohan Prakash. "An Empirical Analysis of Inferences From Commit, Fork, and Branch Rates of Top GitHub Projects," International Journal of Open Source Software and Processes (IJOSSP) 13, no.1: 1-16. http://doi.org/10.4018/IJOSSP.300751

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Abstract

GitHub repositories have been used to understand some important parameters related to quantitative growth of software projects. The rate at which fork, commits and branches have been done in different repositories which are supposed to be the topmost ones when it comes to the number of contributors is the main point of study in this paper. The desirable goal is to find out some sort of similarity in the trends of all these software projects. Similar trends tend to lead to interesting inferences regarding the quantitative growth and even the quality of these software projects. Is the rate of forking, branching, committing anything to do with the success of software projects? The authors have taken up this question in the current study.

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