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题名:
automatic bug triage using semi-supervised text classification
作者: Xuan Jifeng ; Jiang He ; Ren Zhilei ; Yan Jun ; Luo Zhongxuan
会议文集: SEKE 2010 - Proceedings of the 22nd International Conference on Software Engineering and Knowledge Engineering
会议名称: 22nd International Conference on Software Engineering and Knowledge Engineering, SEKE 2010
会议日期: 44013
出版日期: 2010
会议地点: Redwood City, CA, United states
关键词: Knowledge engineering ; Locomotives ; Maximum principle ; Optimization ; Railroad cars ; Software engineering
出版地: United States
收录类别: ei
ISBN: 1891706268
部门归属: (1) School of Mathematical Sciences, Dalian University of Technology, Dalian, 116024, China; (2) School of Software, Dalian University of Technology, Dalian, 116621, China; (3) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, 100190, China; (4) Technology Center of Software Engineering, Institute of Software, Chinese Academy of Sciences, Beijing, 100190, China
主办者: Knowledge Systems Institute Graduate School
英文摘要: In this paper, we propose a semi-supervised text classification approach for bug triage to avoid the deficiency of labeled bug reports in existing supervised approaches. This new approach combines naive Bayes classifier and expectationmaximization to take advantage of both labeled and unlabeled bug reports. This approach trains a classifier with a fraction of labeled bug reports. Then the approach iteratively labels numerous unlabeled bug reports and trains a new classifier with labels of all the bug reports. We also employ a weighted recommendation list to boost the performance by imposing the weights of multiple developers in training the classifier. Experimental results on bug reports of Eclipse show that our new approach outperforms existing supervised approaches in terms of classification accuracy.
语种: 英语
内容类型: 会议论文
URI标识: http://ir.iscas.ac.cn/handle/311060/8674
Appears in Collections:中科院软件所图书馆_2010软件所会议论文

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Recommended Citation:
Xuan Jifeng,Jiang He,Ren Zhilei,et al. automatic bug triage using semi-supervised text classification[C]. 见:22nd International Conference on Software Engineering and Knowledge Engineering, SEKE 2010. Redwood City, CA, United states. 44013.
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