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automatic mining of change set size information from repository for precise productivity estimation
Huang Hui; Yang Qiusong; Xiao Junchao; Zhai Jian
2011
会议名称2011 International Conference on Software and Systems Process, ICSSP 2011, Co-located with ICSE 2011
会议录名称Proceedings - International Conference on Software Engineering
页码72-80
会议日期21-May-20
会议地点Waikiki, Honolulu, HI, United states
收录类别EI
出版地United States
ISSN2705257
ISBN9781450307307
部门归属(1) Laboratory for Internet Software Technologies, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China; (2) Graduate University, Chinese Academy of Sciences, Beijing 100049, China
摘要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. © 2011 ACM.
关键词Project Management Software Engineering
主办者International Software Process Association (ISPA)
内容类型会议论文
URI标识http://ir.iscas.ac.cn/handle/311060/14355
专题互联网软件技术实验室
推荐引用方式
GB/T 7714
Huang Hui,Yang Qiusong,Xiao Junchao,et al. automatic mining of change set size information from repository for precise productivity estimation[C]. United States,2011:72-80.
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