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Experiment on Defect Prediction

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Theory and Engineering of Complex Systems and Dependability (DepCoS-RELCOMEX 2015)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 365))

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Abstract

It is important to be able to predict if a module or a class or a method is faulty, or not. Such predictions can be used to target improvement efforts to those modules or classes that need it the most. We investigated the classification process (deciding if an element is faulty or not) in which the set of software metrics is used and examined several data mining algorithms. We conducted an experiment in which ten open source projects were evaluated by ten chosen metrics. The data concerning defects were extracted from the repository of the control version system. For each project two versions of code were used in the classification process. In this study the results of two algorithms i.e. k- NN and decision trees used in the classification process are presented.

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Authors and Affiliations

  1. Institute of Computer Science, Nowowiejska 15/19, 00-665, Warsaw, Poland

    Ilona Bluemke & Anna Stepień

Authors
  1. Ilona Bluemke
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  2. Anna Stepień
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Corresponding author

Correspondence to Ilona Bluemke .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Wojciech Zamojski

  2. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Jacek Mazurkiewicz

  3. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Jarosław Sugier

  4. Department of Computer Engineering, Wrocław University of Technology, Wrocław, Poland

    Tomasz Walkowiak

  5. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

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© 2015 Springer International Publishing Switzerland

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Bluemke, I., Stepień, A. (2015). Experiment on Defect Prediction. In: Zamojski, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., Kacprzyk, J. (eds) Theory and Engineering of Complex Systems and Dependability. DepCoS-RELCOMEX 2015. Advances in Intelligent Systems and Computing, vol 365. Springer, Cham. https://doi.org/10.1007/978-3-319-19216-1_3

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  • DOI: https://doi.org/10.1007/978-3-319-19216-1_3

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19215-4

  • Online ISBN: 978-3-319-19216-1

  • eBook Packages: EngineeringEngineering (R0)

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