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Less is More: Temporal Fault Predictive Performance over Multiple Hadoop Releases

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Search-Based Software Engineering (SSBSE 2014)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 8636))

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Abstract

We investigate search based fault prediction over time based on 8 consecutive Hadoop versions, aiming to analyse the impact of chronology on fault prediction performance. Our results confound the assumption, implicit in previous work, that additional information from historical versions improves prediction; though G-mean tends to improve, Recall can be reduced.

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Author information

Authors and Affiliations

  1. CREST, University College London, UK

    Mark Harman, Syed Islam, Yue Jia & Federica Sarro

  2. CERCIA, University of Birmingham, UK

    Leandro L. Minku

  3. Department of Computer Science, University of York, UK

    Komsan Srivisut

Authors
  1. Mark Harman
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  2. Syed Islam
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  3. Yue Jia
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  4. Leandro L. Minku
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  5. Federica Sarro
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  6. Komsan Srivisut
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Editor information

Editors and Affiliations

  1. School of Computer Science, Institute for Software Research, Carnegie Mellon University, 5000 Forbes Avenue, 15213, Pittsburgh, PA, USA

    Claire Le Goues

  2. Department of Computer Scioence, University College London, Gower Street, WC1E 6BT, London, UK

    Shin Yoo

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© 2014 Springer International Publishing Switzerland

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Harman, M., Islam, S., Jia, Y., Minku, L.L., Sarro, F., Srivisut, K. (2014). Less is More: Temporal Fault Predictive Performance over Multiple Hadoop Releases. In: Le Goues, C., Yoo, S. (eds) Search-Based Software Engineering. SSBSE 2014. Lecture Notes in Computer Science, vol 8636. Springer, Cham. https://doi.org/10.1007/978-3-319-09940-8_19

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  • DOI: https://doi.org/10.1007/978-3-319-09940-8_19

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09939-2

  • Online ISBN: 978-3-319-09940-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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