SEL@KIT: O. Mizuno, T. Hamasaki, Y. Takagi, and T. Kikuno, An Empirical Evaluation of Predicting Runaway Software Projects Using Bayesian Classification, April 2004.
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O. Mizuno, T. Hamasaki, Y. Takagi, and T. Kikuno, "An Empirical Evaluation of Predicting Runaway Software Projects Using Bayesian Classification," In Proc. of 5th International Conference on Product Focused Software Process Improvement (PROFES2004), LNCS 3009, pp. 263-273, April 2004.
ID 417
分類 国際会議(査読付)
タグ full-paper bayesian classification empirical evaluation predicting projects runaway software
表題 (title) An Empirical Evaluation of Predicting Runaway Software Projects Using Bayesian Classification
表題 (英文)
著者名 (author) Osamu Mizuno,Takanari Hamasaki,Yasunari Takagi,Tohru Kikuno
英文著者名 (author) Osamu Mizuno,Takanari Hamasaki,Yasunari Takagi,Tohru Kikuno
編者名 (editor)
編者名 (英文)
キー (key) Osamu Mizuno,Takanari Hamasaki,Yasunari Takagi,Tohru Kikuno
書籍・会議録表題 (booktitle) Proc. of 5th International Conference on Product Focused Software Process Improvement (PROFES2004)
書籍・会議録表題(英文)
巻数 (volume) LNCS 3009
号数 (number)
ページ範囲 (pages) 263-273
組織名 (organization)
出版元 (publisher)
出版元 (英文)
出版社住所 (address)
刊行月 (month) 4
出版年 (year) 2004
採択率 (acceptance)
URL
付加情報 (note) Nara, Japan
注釈 (annote)
内容梗概 (abstract) Since software development projects often fall into runaway
situations, detecting signs of runaway status in early stage of
development has become important. In this paper, we propose a new
scheme for the prediction of runaway projects based on an empirical
questionnaire. We first design a questionnaire from five viewpoints
within the projects: requirements, estimations, planning, team
organization, and project management activities. Each of these
viewpoints consists of questions in which experience and knowledge
of software risks are included. Secondly, we classify projects into
``runaway'' and ``success'' using resultant metrics data. We
then analyze the relationship between responses to the questionnaire
and the runaway status of projects by the Bayesian
classification. The experimental result using actual project data
shows that 33 out of 40 projects were predicted correctly. As a
result, we confirm that the prediction of runaway projects is
successful.


論文電子ファイル draft (application/pdf) [一般閲覧可]
BiBTeXエントリ
@inproceedings{id417,
         title = {An Empirical Evaluation of Predicting Runaway Software Projects Using {Bayesian} Classification},
        author = {Osamu Mizuno and Takanari Hamasaki and Yasunari Takagi and Tohru Kikuno},
     booktitle = {Proc. of  5th International Conference on Product Focused Software Process Improvement (PROFES2004)},
        volume = {LNCS 3009},
         pages = {263-273},
         month = {4},
          year = {2004},
          note = {Nara, Japan},
}
  

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