Computer Science ›› 2020, Vol. 47 ›› Issue (3): 25-33.doi: 10.11896/jsjkx.191000087

• Intelligent Software Engineering • Previous Articles     Next Articles

Approach of Automatic Fork Summary Generation in Open Source Community Based on Feature Extraction

ZHANG Chao1,MAO Xin-jun1,2,LU Yao1   

  1. (College of Computer Science and Technology, National University of Defense Technology, Changsha 410000, China)1;
    (Key Laboratory of Complex System Software Engineering, Changsha 410000, China)2
  • Received:2019-10-15 Online:2020-03-15 Published:2020-03-30
  • About author:ZHANG Chao,born in 1991,postgradua-te,is member of China Computer Fe-deration.His main research interests include software engineering and open source community. MAO Xin-jun,born in 1970,Ph.D,professor,is member of China Computer Federation.His main research interests include software engineering and open source community.
  • Supported by:
    This work was supported by the National Key R&D Program of China (2018YFB1004202) and Research on Mechanism and Method of Massive Online Collaborative Learning (61532004).

Abstract: At present,distributed collaborative development based on P/R has become the dominant software development me-thod in open source community.Because of the openness,transparency and parallelism of the software development in P/R mo-del,it is difficult for developers to obtain the complete Fork profile of the whole project,and know whether other developers have accomplished the same or similar development tasks,which are prone to duplicate contributions and redundant development.To solve this problem,this paper proposed an automatic generation method of Fork summary to help project managers strengthen project management,avoid redundant contributions,and enhance cooperation and communication among developers.The proposed method firstly crawls Issue data with feature and Bug label information in open source community,and trains a classifier model with random forest method to classify Fork features.Then,it collects the data of Fork branch’s software development activities and uses TextRank algorithm to generate detailed Fork information to explain the main purpose of Fork activity.Finally,a set of combination rules and corresponding algorithm are designed to integrate Fork’s categories,features and other information to form a complete Fork summary.In order to validate the effectiveness of the proposed method,30 groups of manual tests and 60 groups of actual live study were conducted on Github.The results show that the accuracy of Fork summary generated by this method is 67.2%.In the experiment,76% of project managers believe that Fork summary can help to better manage projects,and strengthen communication and cooperation.

Key words: Opens source, Open source community, Fork summary, Distributed cooperative development

CLC Number: 

  • TP311
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