Healthy or Not: A Way to Predict Ecosystem Health in GitHub

Zhifang Liao, Mengjie Yi, Yan Wang, Shengzhou Liu, Hui Liu, Yan Zhang, Yun Zhou

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
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With the development of open source community, through the interaction of developers, the collaborative development of software, and the sharing of software tools, the formation of open source software ecosystem has matured. Natural ecosystems provide ecological services on which human beings depend. Maintaining a healthy natural ecosystem is a necessity for the sustainable development of mankind. Similarly, maintaining a healthy ecosystem of open source software is also a prerequisite for the sustainable development of open source communities, such as GitHub. This paper takes GitHub as an example to analyze the health condition of open source ecosystem and, also, it is a research area in Symmetry. Firstly, the paper presents the healthy definition of GitHub open source ecosystem health and, then, according to the main components of natural ecosystem health, the paper proposes the health indicators and health indicators evaluation method. Based on the above, the GitHub ecosystem health prediction method is proposed. By analyzing the projects and data collected in GitHub, it is found that, using the proposed evaluation indicators and method, we can analyze the healthy development trend of the GitHub ecosystem and contribute to the stability of ecosystem development.
Original languageEnglish
Number of pages16
Issue number2
Publication statusPublished - 28 Jan 2019


  • open source software
  • evaluation method
  • GitHub
  • ecosystem health
  • Symmetry


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