SEL@KIT: O. Mizuno, S. Ikami, S. Nakaichi, and T. Kikuno, Fault-Prone Filtering: Detection of Fault-Prone Modules Using Spam Filtering Technique, September 2007.
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O. Mizuno, S. Ikami, S. Nakaichi, and T. Kikuno, "Fault-Prone Filtering: Detection of Fault-Prone Modules Using Spam Filtering Technique," In Proc. 1st International Symposium on Empirical Software Engineering and Measurement (ESEM2007), pp. 374-383, September 2007.
ID 500
分類 国際会議(査読付)
タグ detection fault-prone filtering modules spam technique major-mizuno full-paper
表題 (title) Fault-Prone Filtering: Detection of Fault-Prone Modules Using Spam Filtering Technique
表題 (英文)
著者名 (author) Osamu Mizuno,Shiro Ikami,Shuya Nakaichi,Tohru Kikuno
英文著者名 (author) Osamu Mizuno,Shiro Ikami,Shuya Nakaichi,Tohru Kikuno
編者名 (editor)
編者名 (英文)
キー (key) Osamu Mizuno,Shiro Ikami,Shuya Nakaichi,Tohru Kikuno
書籍・会議録表題 (booktitle) Proc. 1st International Symposium on Empirical Software Engineering and Measurement (ESEM2007)
書籍・会議録表題(英文)
巻数 (volume)
号数 (number)
ページ範囲 (pages) 374-383
組織名 (organization)
出版元 (publisher)
出版元 (英文)
出版社住所 (address)
刊行月 (month) 9
出版年 (year) 2007
採択率 (acceptance) 41%, 44/107
URL http://www2.computer.org/portal/web/csdl/doi/10.1109/ESEM.2007.29
付加情報 (note) Madrid, Spain
注釈 (annote)
内容梗概 (abstract) The fault-prone module detection in source code is of im- portance for assurance of software quality. Most of pre- vious conventional fault-prone detection approaches have been based on using software metrics. Such approaches, however, have difficulties in collecting the metrics and con- structing mathematical models based on the metrics. In order to mitigate such difficulties, we propose a novel ap- proach for detecting fault-prone modules using a spam fil- tering technique. Because of the increase of needs for spam e-mail detection, the spam filtering technique has been pro- gressed as a convenient and effective technique for text min- ing. In our approach, fault-prone modules are detected in a way that the source code modules are considered as text files and are applied to the spam filter directly. In order to show the usefulness of our approach, we conducted an experiment using source code repository of a Java based open source development. The result of experiment shows that our approach can classify more than 70% of software modules correctly.
論文電子ファイル presentation (application/zip) [一般閲覧可]
BiBTeXエントリ
@inproceedings{id500,
         title = {Fault-Prone Filtering: Detection of Fault-Prone Modules Using Spam Filtering Technique},
        author = {Osamu Mizuno and Shiro Ikami and Shuya Nakaichi and Tohru Kikuno},
     booktitle = {Proc. 1st International Symposium on Empirical Software Engineering and Measurement (ESEM2007)},
         pages = {374-383},
         month = {9},
          year = {2007},
    acceptance = {41\%, 44/107},
          note = {Madrid, Spain},
}
  

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