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2007
IEEE

Data Mining Techniques for Building Fault-proneness Models in Telecom Java Software

9 years 1 months ago
Data Mining Techniques for Building Fault-proneness Models in Telecom Java Software
This paper describes a study performed in an industrial setting that attempts to build predictive models to identify parts of a Java system with a high probability of fault. The system under consideration is constantly evolving as several releases a year are shipped to customers. Developers usually have limited resources for their testing and inspections and would like to be able to devote extra resources to faulty system parts. The main research focus of this paper is two-fold: (1) use and compare many data mining and machine learning techniques to build fault-proneness models based mostly on source code measures and change/fault history data, and (2) demonstrate that the usual classification evaluation criteria based on confusion matrices may not be fully appropriate to compare and evaluate models. Categories and Subject Descriptors D.2.8 [Metrics]: Complexity measures, Performance measures, Process metrics, Product metrics, Software science General Terms Management, Measurement, Ec...
Erik Arisholm, Lionel C. Briand, Magnus Fuglerud
Added 26 Oct 2010
Updated 26 Oct 2010
Type Conference
Year 2007
Where ISSRE
Authors Erik Arisholm, Lionel C. Briand, Magnus Fuglerud
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