Automatic mining of change set size information from repository for precise productivity estimation

  • Authors:

  • Hui Huang;Qiusong Yang;Junchao Xiao;Jian Zhai

  • Affiliations:

  • Chinese Academy of Sciences, Beijing, China;Chinese Academy of Sciences, Beijing, China;Chinese Academy of Sciences, Beijing, China;Chinese Academy of Sciences, Beijing, China

  • Venue:
  • Proceedings of the 2011 International Conference on Software and Systems Process
  • Year:
  • 2011

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Abstract

Productivity is a crucial concern for most software organizations. It can help project managers to make project plan, supervise project progress, and measure the project members' performance. Thus it has been widely measured and analyzed by both industry and researchers. But in the actual software project management, the project data filled by the developers may be incomplete and imprecise. Especially it is very hard for the developers to give the precise work product scale of each task. Therefore, the productivity calculated basing on those data is also imprecise. To solve the problem, this paper presents a method for precise productivity estimation. The method calculates work product scale of each task using change set size information by rebuilding relationships between the tasks and the SVN commits, and then calculates the productivity. And an experimental study has been done basing on Qone. Qone is an integrated system for project management developed by Institute of Software Chinese Academy of Sciences (ISCAS). It has been used in more than 200 software companies in China.