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International Conference on Product Focused Software Process Improvement

PROFES 2007: Product-Focused Software Process Improvement pp 300–314Cite as

Software Fault Prediction with Object-Oriented Metrics Based Artificial Immune Recognition System

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 4589))

Abstract

Software testing is a time-consuming and expensive process. Software fault prediction models are used to identify fault-prone classes automatically before system testing. These models can reduce the testing duration, project risks, resource and infrastructure costs. In this study, we propose a novel fault prediction model to improve the testing process. Chidamber-Kemerer Object-Oriented metrics and method-level metrics such as Halstead and McCabe are used as independent metrics in our Artificial Immune Recognition System based model. According to this study, class-level metrics based model which applies AIRS algorithm can be used successfully for fault prediction and its performance is higher than J48 based approach. A fault prediction tool which uses this model can be easily integrated into the testing process.

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Author information

Authors and Affiliations

  1. TUBITAK-Marmara Research Center, Information Tech. Ins., 41470, Turkey

    Cagatay Catal

  2. Yildiz Technical University, Computer Engineering Dept., 34349, Turkey

    Banu Diri

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  1. Cagatay Catal
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  2. Banu Diri
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Jürgen Münch Pekka Abrahamsson

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© 2007 Springer-Verlag Berlin Heidelberg

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Catal, C., Diri, B. (2007). Software Fault Prediction with Object-Oriented Metrics Based Artificial Immune Recognition System. In: Münch, J., Abrahamsson, P. (eds) Product-Focused Software Process Improvement. PROFES 2007. Lecture Notes in Computer Science, vol 4589. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73460-4_27

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  • DOI: https://doi.org/10.1007/978-3-540-73460-4_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73459-8

  • Online ISBN: 978-3-540-73460-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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