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Title:
Learning from evolution history to predict future requirement changes
Author: Shi, Lin (1) ; Wang, Qing (1) ; Li, Mingshu (1)
Conference Name: 2013 21st IEEE International Requirements Engineering Conference, RE 2013
Conference Date: July 15, 2013 - July 19, 2013
Issued Date: 2013
Conference Place: Rio de Janeiro, Brazil
Publish Place: IEEE Computer Society, 2001 L Street N.W., Suite 700, Washington, DC 20036-4928, United States
Indexed Type: EI
ISBN: 9781467357654
Department: (1) Laboratory for Internet Software Technologies, Institute of Software, Chinese Academy of Sciences, Beijing, China; (2) University of Chinese Academy of Sciences, Beijing, China; (3) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China
Abstract: Managing the costs and risks of evolution is a challenging problem in the RE community. The challenge lies in the difficulty of analyzing and assessing the proneness to requirement changes across multiple versions, especially when the scale of requirements is large. In this paper, we define a series of metrics to characterize historic evolution information, and propose a novel method for predicting requirements that are likely to evolve in the future based on the metrics. We apply the prediction method to analyze the product updates history through a case study. The empirical results show that this method can provide a tradeoff solution that narrows down the scope of change analysis to a small set of requirements, but it still can retrieve nearly half of the future changes. The results indicate that the defined metrics are sensitive to the history of requirements evolution, and the prediction method can reach a valuable outcome for requirement engineers to balance their workload and risks. © 2013 IEEE.
English Abstract: Managing the costs and risks of evolution is a challenging problem in the RE community. The challenge lies in the difficulty of analyzing and assessing the proneness to requirement changes across multiple versions, especially when the scale of requirements is large. In this paper, we define a series of metrics to characterize historic evolution information, and propose a novel method for predicting requirements that are likely to evolve in the future based on the metrics. We apply the prediction method to analyze the product updates history through a case study. The empirical results show that this method can provide a tradeoff solution that narrows down the scope of change analysis to a small set of requirements, but it still can retrieve nearly half of the future changes. The results indicate that the defined metrics are sensitive to the history of requirements evolution, and the prediction method can reach a valuable outcome for requirement engineers to balance their workload and risks. © 2013 IEEE.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/16689
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Shi, Lin ,Wang, Qing ,Li, Mingshu . Learning from evolution history to predict future requirement changes[C]. 见:2013 21st IEEE International Requirements Engineering Conference, RE 2013. Rio de Janeiro, Brazil. July 15, 2013 - July 19, 2013.
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