Selection of Metrics for the Defect Prediction

Ilona Bluemke , Anna Stepień

Abstract

The ability to estimate if a module or a class or a method is faulty, or not, is called the defect prediction. Prediction can be used to target the 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 and several data mining algorithms were used. We conducted an experiment on ten open source projects. The data concerning defects were extracted from the repository of the control version system. In this study the process of choosing appropriate metrics for the defect prediction is described. In the selection process we use unique approach by random forest.
Author Ilona Bluemke II
Ilona Bluemke,,
- The Institute of Computer Science
, Anna Stepień II
Anna Stepień,,
- The Institute of Computer Science
Pages39-50
Publication size in sheets0.55
Book Zamojski Wojciech, Mazurkiewicz Jacek, Sugier Jarosław, Walkowiak Tomasz, Kacprzyk Janusz (eds.): Dependability Engineering and Complex Systems. Proceedings of the Eleventh International Conference on Dependability and Complex Systems DepCoS-RELCOMEX, Advances in Intelligent Systems and Computing, vol. 470, 2016, Springer International Publishing, ISBN 978-3-319-39638-5, [978-3-319-39639-2], 606 p., DOI:10.1007/978-3-319-39639-2 document.gif
Keywords in EnglishDefect prediction, Object metrics
DOIDOI:10.1007/978-3-319-39639-2_4
URL http://link.springer.com/chapter/
projectDevelopment of new algorithms in the areas of software and computer architecture, artificial intelligence and information systems and computer graphics . Project leader: Rybiński Henryk, , Phone: +48 22 234 7731, start date 18-05-2015, end date 30-11-2016, II/2015/DS/1, Completed
WEiTI Działalność statutowa
Languageen angielski
File
Depcos-6-IBlu-2016.pdf (file archived - login or check accessibility on faculty) Depcos-6-IBlu-2016.pdf 177.51 KB
Score (nominal)15
ScoreMinisterial score = 15.0, 27-03-2017, BookChapterSeriesAndMatConf
Ministerial score (2013-2016) = 15.0, 27-03-2017, BookChapterSeriesAndMatConf
Citation count*1 (2018-02-15)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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