Survey of Software Data Mining for Open Source Ecosystem
Author:
Affiliation:

Clc Number:

Fund Project:

National Key Research and Development Program of China (2016YFB1000805); National Natural Science Foundation of China (61472430)

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Crowd-Based software production model in global open source software ecosystem is rapidly becoming a new paradigm in promoting software productivity, and has great impacts on many stages of software development and applications. Crowd-Based software production generates large amounts of software data, continuously expands its collaboration scopes, and highly simplifies its project management. These globalization features present many challenges to crowd-based software production in software reuse, collaboration development and knowledge management, which urgently require new theories and supporting tools. This paper first classifies the distribution, basic process and data form of crowd-based software production activities. Then it analyzes the studies of software communities on data mining technology from the three core aspects-software reuse, collaborative development and knowledge management. Finally, the paper summarizes the problems and future trends of research works in this field.

    Reference
    Related
    Cited by
Get Citation

尹刚,王涛,刘冰珣,周明辉,余跃,李志星,欧阳建权,王怀民.面向开源生态的软件数据挖掘技术研究综述.软件学报,2018,29(8):2258-2271

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:July 18,2017
  • Revised:July 18,2017
  • Adopted:
  • Online: March 13,2018
  • Published:
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-4
Address:4# South Fourth Street, Zhong Guan Cun, Beijing 100190,Postal Code:100190
Phone:010-62562563 Fax:010-62562533 Email:jos@iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063