Paper Info
Title
Healthy or Not: A Way to Predict Ecosystem Health in GitHub.
Abstract
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.
Year
DOI
Venue
2019
10.3390/sym11020144
SYMMETRY-BASEL
Keywords
Field
DocType
open source software,GitHub,Symmetry,ecosystem health,evaluation method
Combinatorics,Environmental resource management,Ecosystem services,Health indicator,Ecosystem health,Software,Sustainable development,Open source software,Mathematics,Ecosystem
Journal
Volume
Issue
Citations 
11
2
1
PageRank 
References 
Authors
0.35
9
7
Name
Order
Citations
PageRank
Zhifang Liao15215.52
Mengjie Yi210.35
Yan Wang310.35
Shengzong Liu410.68
Hui Liu531.43
yan zhang66720.55
Yun Zhou710.35