Abstract：Taking GitHub community as an example，this paper analyzes the risk transfer and cascading collapse response of open source projects in the development process by collecting massive community project data.Based on the analysis of the most common risk transfer mode between the two open-source projects，technical association and cooperative association，combined with the collection of data，it is concluded that a single project failure will produce a certain scale of cascading collapse response.Secondly，aiming at a large number of successful and failed project data of GitHub open source community，through the design of reasonable characteristics and support vector machine，the successful and failed project data are trained.Through data cleaning and optimization methods，the trained model can better predict the project failure risk，which provides an effective way for the long-term development and risk assessment of open source community basis.
张翔,周健. 开源社区级联崩塌效应分析及基于SVM的项目失败预测[J]. 小型微型计算机系统, 2021, 42(5): 1103-1108.
ZHANG Xiang,ZHOU Jian. Analysis of Cascade Collapse Effect of Open Source Community and Project Failure Prediction Based on Support Vector Machine. Journal of Chinese Computer Systems, 2021, 42(5): 1103-1108.
2021, Vol. 42 
