SEL@KIT: O. Mizuno and T. Kikuno, Training on Errors Experiment to Detect Fault-Prone Software Modules by Spam Filter, September 2007.
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O. Mizuno and T. Kikuno, "Training on Errors Experiment to Detect Fault-Prone Software Modules by Spam Filter," In The 6th joint meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE2007), pp. 405-414, September 2007.
ID 511
分類 国際会議(査読付)
タグ detect errors experiment fault-prone filter modules software spam training major-mizuno full-paper
表題 (title) Training on Errors Experiment to Detect Fault-Prone Software Modules by Spam Filter
表題 (英文)
著者名 (author) Osamu Mizuno,Tohru Kikuno
英文著者名 (author) Osamu Mizuno,Tohru Kikuno
編者名 (editor)
編者名 (英文)
キー (key) Osamu Mizuno,Tohru Kikuno
書籍・会議録表題 (booktitle) The 6th joint meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE2007)
書籍・会議録表題(英文)
巻数 (volume)
号数 (number)
ページ範囲 (pages) 405-414
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) 17%, 43/251
URL http://portal.acm.org/citation.cfm?doid=1287624.1287683
付加情報 (note) Dubrovnik, Croatia
注釈 (annote)
内容梗概 (abstract) The fault-prone module detection in source code is of importance for assurance of software quality. Most of previous fault-prone detection approaches are based on software metrics. Such approaches, however, have difficulties in collecting the metrics and constructing mathematical models based on the metrics. In order to mitigate such difficulties, we propose a novel approach for detecting
fault-prone modules using a spam filtering technique, named Fault-Prone Filtering. Because of the
increase of needs for spam e-mail detection, the spam filtering technique has been progressed as a
convenient and effective technique for text mining. 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. This paper describes the training on errors procedure to apply fault-prone
filtering in practice. Since no pre-training is required, this procedure can be applied to actual
development field immediately. In order to show the usefulness of our approach, we conducted an
experiment using a large source code repository of Java based open source project. The result of
experiment shows that our approach can classify about 85% of software modules correctly. The result
also indicates that fault-prone modules can be detected relatively low cost at an early stage.



論文電子ファイル presentation (application/zip) [一般閲覧可]
論文電子ファイル draft (application/pdf) [一般閲覧可]
BiBTeXエントリ
@inproceedings{id511,
         title = {Training on Errors Experiment to Detect Fault-Prone Software Modules by Spam Filter},
        author = {Osamu Mizuno and Tohru Kikuno},
     booktitle = {The 6th joint meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE2007)},
         pages = {405-414},
         month = {9},
          year = {2007},
    acceptance = {17\%, 43/251},
          note = {Dubrovnik, Croatia},
}
  

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