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Browsing by Subject "data mining"

Browsing by Subject "data mining"

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  • Kula, Raula Gaikovina; Roover, Coen De; German, Daniel M.; Ishio, Takashi; Inoue, Katsuro (IEEE, 2018)
    The popularity of super repositories such as Maven Central and the CRAN is a testament to software reuse activities in both open-source and commercial projects alike. However, several studies have highlighted the risks and ...
  • Monden, Akito; Keung, Jacky; Morisaki, Shuji; Kamei, Yasutaka; Matsumoto, Ken-Ichi (IEEE, 2012)
    Background: Association rules are more comprehensive and understandable than fault-prone module predictors (such as logistic regression model, random forest and support vector machine). One of the challenges is that there ...
  • Uemura, Kyohei; Saito, Yusuke; Fujiwara, Shin; Tanaka, Daiki; Fujiwara, Kenji; Iida, Hajimu; Matsumoto, Kenichi (IEEE, 2016)
    In the research of Mining Software Repositories, source code repositories are one of the core sources since it contains the product and the process of software development. A source code repository stores the versions of ...
  • Terdchanakul, Pannavat; Hata, Hideaki; Phannachitta, Passakorn; Matsumoto, Kenichi (IEEE, 2017)
    Previous studies have found that a significant number of bug reports are misclassified between bugs and nonbugs, and that manually classifying bug reports is a time-consuming task. To address this problem, we propose a bug ...
  • Morisaki, Shuji; Monden, Akito; Matsumura, Tomoko; Tamada, Haruaki; Matsumoto, Ken-ichi (IEEE, 2007)
    This paper describes an empirical study to reveal rules associated with defect correction effort. We defined defect correction effort as a quantitative (ratio scale) variable, and extended conventional (nominal scale based) ...