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题名:
predicting upgrade project defects based on enhancement requirements: an empirical study
作者: He Lei ; Li Juan ; Wang Qing ; Yang Ye
会议文集: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
会议名称: International Conference on Software Process
会议日期: MAY 16-17,
出版日期: 2009
会议地点: Vancouver, CANADA
关键词: Defect Prediction
出版者: TRUSTWORTHY SOFTWARE DEVELOPMENT PROCESSES, PROCEEDINGS
出版地: HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
收录类别: 其他
ISSN: 0302-9743
ISBN: 978-3-642-01679-0
部门归属: He, Lei; Li, Juan; Wang, Qing; Yang, Ye Chinese Acad Sci, Inst Software, Beijing 100864, Peoples R China.
主办者: Chinese Acad Sci, ISCAS Lab Internet Software Technologies
英文摘要: In upgrade project development, Enhancement Requirements (ER, e.g. requirement additions and modifications) introduce new defects to the project. We need to evaluate this impact to help plan later project schedule and resources. Typically, many of the existing prediction technologies estimate defects based on software size or process performance baselines. However, they are limited in estimating the impact of ER on product quality. This paper proposes a novel ER-based defect prediction method using information retrieval (IR) technique and support vector machines (SVM). We analyze the historical data of defects and requirement specifications of actual upgrade projects to establish multiple prediction models to estimate new defects introduced by ER. Then we design two experiments to validate the method and report some preliminary results. The results indicate that our method can provide useful support for impact analysis of requirement evolution in upgrade projects.
语种: 英语
内容类型: 会议论文
URI标识: http://ir.iscas.ac.cn/handle/311060/8376
Appears in Collections:互联网软件技术实验室 _会议论文

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Recommended Citation:
He Lei,Li Juan,Wang Qing,et al. predicting upgrade project defects based on enhancement requirements: an empirical study[C]. 见:International Conference on Software Process. Vancouver, CANADA. MAY 16-17,.
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