Which Metrics Should Researchers Use to Collect Repositories: An Empirical Study

Kai Yamamoto, Masanari Kondo, Kinari Nishiura, Osamu Mizuno

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

GitHub is a huge publicly available development platform for hosting a version control system based on Git; software developers prefer to host their various software projects in GitHub. Therefore researchers who are interested in mining software repository frequently use GitHub to collect software projects as datasets. GitHub provides us with repository metrics such as popularity, contribution, and interest. We believe that such metrics are related to the quality of software; we use them to opt for studied repositories according to our research purpose. However, to the best of our knowledge, nobody has any evidence to support this assumption.Our main purpose is to provide researchers who study software quality, especially issue management, with repository metrics to select appropriate repositories for their studies. In this paper, we study the relationship between the characteristics of the issue pages of repositories that are selected by repository metrics in order to figure out the best repository metric to select proper repositories. The following findings are the highlights of our study: (1) The number of contributors that indicates the number of developers who contribute to a GitHub repository can be used to select the repositories having issue pages that are well-maintained. More specifically, such issue pages include more issues and in which developers use the labels more frequently rather than those that are selected by other metrics. (2) The number of dependencies opts for the repositories that have fewer issues and in which developers use the labels less often rather than those that are selected by other metrics.

本文言語英語
ホスト出版物のタイトルProceedings - 2020 IEEE 20th International Conference on Software Quality, Reliability, and Security, QRS 2020
出版社Institute of Electrical and Electronics Engineers Inc.
ページ458-466
ページ数9
ISBN(電子版)9781728189130
DOI
出版ステータス出版済み - 12 2020
外部発表はい
イベント20th IEEE International Conference on Software Quality, Reliability, and Security, QRS 2020 - Macau, 中国
継続期間: 12 11 202012 14 2020

出版物シリーズ

名前Proceedings - 2020 IEEE 20th International Conference on Software Quality, Reliability, and Security, QRS 2020

会議

会議20th IEEE International Conference on Software Quality, Reliability, and Security, QRS 2020
Country中国
CityMacau
Period12/11/2012/14/20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality
  • Modelling and Simulation
  • Software

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