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a requirement traceability refinement method based on relevance feedback
Kong Lingjun; Li Juan; Li Yin; Yang Ye; Wang Qing
2009
会议名称21st International Conference on Software Engineering and Knowledge Engineering, SEKE 2009
会议录名称Proceedings of the 21st International Conference on Software Engineering and Knowledge Engineering, SEKE 2009
会议日期44013
会议地点Boston, MA, United states
收录类别EI
出版地United Kingdom
ISBN1891706241
部门归属(1) Laboratory for Internet Software Technologies, Institute of Software, China; (2) Graduate University, Chinese Academy of Sciences, China
摘要In this paper, we conduct a study of using relevance feedback-based Information Retrieval (IR) methods to refine Requirement Traceability (RT) from requirement to code. We compare two representative feedback methods: Mixture Model (MM) in language model and Standard Rochio method (SR) in vector-space model. In order to assure the fairness of comparison, we also make modification for both of the methods. Initial experiment results on a real project data set show that 1) few iterations of feedback result in significant increases both in precision and recall; 2) feedback methods in language model are generally more stable than methods in vector-space model in improving precision, but the latter is more effective and can get better precision; 3) negative feedback information plays an important role in refining requirement traceability.
关键词Computational Linguistics Knowledge Engineering Refining Software Engineering Vector Spaces
主办者Knowledge Systems Institute Graduate School
内容类型会议论文
URI标识http://ir.iscas.ac.cn/handle/311060/8422
专题互联网软件技术实验室
推荐引用方式
GB/T 7714
Kong Lingjun,Li Juan,Li Yin,et al. a requirement traceability refinement method based on relevance feedback[C]. United Kingdom,2009.
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