Volume 14 Number 4 (Apr. 2019)
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JCP 2019 Vol.14(4): 240-246 ISSN: 1796-203X
doi: 10.17706/jcp.14.4.240-246

A Large-Scale Dataset of Popular Open Source Projects

Muna Altherwi, Andy Gravell
School of Electronics and Computer Science, University of Southampton, Southampton, United Kingdom
Abstract—Online open source software repositories offer a wealth of information related to software artifacts and the development process, making them a valuable source for research data. Mining software repositories and retrieving project data from them provide an opportunity to build large-scale datasets of selected, high quality, real project data. Such datasets could be used to empirically validate assumptions, test hypotheses, and verify anecdotal claims about software development processes and the resulting artifacts. Moreover, publishing them would make replicability and verification of studies possible that, in turn, can enhance research quality. Thus, in this work, we publish a large-scale dataset, of 4349 projects in 11 general-purpose programming languages gathered from Github repositories, where a primary language can be identified. The usage of such a dataset can vary from empirically validating claims in the software engineering field, to machine learning training and test sets.

Index Terms—Dataset, mining software repositories, open source software.

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Cite: Muna Altherwi, Andy Gravell, "A Large-Scale Dataset of Popular Open Source Projects," Journal of Computers vol. 14, no. 4, pp. 240-246, 2019.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Monthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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