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H. Hata, O. Mizuno, and T. Kikuno, "Fault-Prone Module Detection Using Large-Scale Text Features Based on Spam Filtering," Empirical Software Engineering, 15(2), pp. 147-165, April 2010.
ID 546
分類 学術論文誌(査読付)
タグ detection fault-prone features filtering large-scale module spam text major-mizuno
表題 (title) Fault-Prone Module Detection Using Large-Scale Text Features Based on Spam Filtering
表題 (英文)
著者名 (author) Hideaki Hata,Osamu Mizuno,Tohru Kikuno
英文著者名 (author) Hideaki Hata,Osamu Mizuno,Tohru Kikuno
キー (key) Hideaki Hata,Osamu Mizuno,Tohru Kikuno
定期刊行物名 (journal) Empirical Software Engineering
定期刊行物名 (英文)
巻数 (volume) 15
号数 (number) 2
ページ範囲 (pages) 147-165
刊行月 (month) 4
出版年 (year) 2010
Impact Factor (JCR) 1.612 (2009)
URL http://www.springerlink.com/content/p7603rq2160756k4/
付加情報 (note)
注釈 (annote) DOI: 10.1007/s10664-009-9117-9
内容梗概 (abstract) This paper proposes an approach using large-scale text features for fault-prone module detection inspired by spam filtering. The number of every text feature in the source code of a module is counted and used as data for training detection models. In this paper, we prepared a naive Bayes classifier and a logistic regression model as detection models. To show the effectiveness of our approaches, we conducted experiments with five open source projects and compared them with a well-known metrics set, thereby achieving higher detection results. The results imply that large-scale text features are useful in constructing practical detection models, and measuring sophisticated metrics is not always necessary for detecting fault-prone modules.

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BiBTeXエントリ 
@article{id546,
         title = {Fault-Prone Module Detection Using Large-Scale Text Features Based on Spam Filtering},
        author = {Hideaki Hata and Osamu Mizuno and Tohru Kikuno},
       journal = {Empirical Software Engineering},
        volume = {15},
        number = {2},
         pages = {147-165},
         month = {4},
          year = {2010},
    impactfactor = {1.612 (2009)},
        annote = {DOI: 10.1007/s10664-009-9117-9},
}