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题名:
data transformation and attribute subset selection: do they help make differences in software failure prediction?
作者: Jia Hao ; Shu Fengdi ; Yang Ye ; Li Qi
会议文集: IEEE International Conference on Software Maintenance, ICSM
会议名称: IEEE International Conference on Software Maintenance
会议日期: SEP 20-26,
出版日期: 2009
会议地点: Edmonton, CANADA
关键词: attribute subset selection ; data transformation ; in-house maintenance projects ; open-source projects ; software failure prediction ; attribute grammars ; public domain software ; software maintenance ; software performance evaluation
出版者: 2009 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE, CONFERENCE PROCEEDINGS
出版地: 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA
ISSN: 1063-6773
ISBN: 978-1-4244-4897-5
部门归属: Jia, Hao; Shu, Fengdi; Yang, Ye Chinese Acad Sci, Inst Software, Beijing 100864, Peoples R China.
主办者: IEEE, IEEE Comp Soc, Tech Council Software Engn
英文摘要: Data transformation and attribute subset selection have been adopted in improving software defect/failure prediction methods. However, little consensus was achieved on their effectiveness. This paper reports a comparative study on these two kinds of techniques combined with four classifier and datasets from two projects. The results indicate that data transformation displays unobvious influence on improving the performance, while attribute subset selection methods show distinguishably inconsistent output. Besides, consistency across releases and discrepancy between the open-source and in-house maintenance projects in the evaluation of these methods are discussed.
内容类型: 会议论文
URI标识: http://ir.iscas.ac.cn/handle/311060/8210
Appears in Collections:互联网软件技术实验室 _会议论文

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Recommended Citation:
Jia Hao,Shu Fengdi,Yang Ye,et al. data transformation and attribute subset selection: do they help make differences in software failure prediction?[C]. 见:IEEE International Conference on Software Maintenance. Edmonton, CANADA. SEP 20-26,.
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