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International Conference on Artificial Neural Networks

ICANN 2017: Artificial Neural Networks and Machine Learning – ICANN 2017 pp 64–71Cite as

Parallel Implementation of a Bug Report Assignment Recommender Using Deep Learning

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10614))

Abstract

For large software projects which receive many reports daily, assigning the most appropriate developer to fix a bug from a large pool of potential developers is both technically difficult and time-consuming. We introduce a parallel, highly scalable recommender system for bug report assignment. From a machine learning perspective, the core of such a system consists of a multi-class classification process using characteristics of a bug, like textual information and other categorical attributes, as features and the most appropriate developer as the predicted class. We use alternatively two Deep Learning classifiers: Convolutional and Recurrent Neural Networks. The implementation is realized on an Apache Spark engine, running on IBM Power8 servers. The experiments use real-world data from the Netbeans, Eclipse and Mozilla projects.

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Notes

  1. 1.

    https://twitter.com/.

  2. 2.

    https://en.wikipedia.org/wiki/Data_parallelism.

  3. 3.

    http://2011.msrconf.org/msr-challenge.html.

  4. 4.

    http://spark.apache.org/.

  5. 5.

    https://deeplearning4j.org/about.

  6. 6.

    https://github.com/acflorea/deep-columbugus,mariana-triage.

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Acknowledgments

The authors are grateful to the Mozilla Foundation for providing a dump of their Bugzilla database and to IBM Client Center, Poughkeepsie, NY, USA for allowing us to use their infrastructure.

Author information

Authors and Affiliations

  1. Electronics and Computers Department, Transilvania University of Braşov, Braşov, Romania

    Adrian-Cătălin Florea & Răzvan Andonie

  2. Department of Mathematics and Computer Science, University of Lethbridge, Lethbridge, AB, Canada

    John Anvik

  3. Computer Science Department, Central Washington University, Ellensburg, WA, USA

    Răzvan Andonie

Authors
  1. Adrian-Cătălin Florea
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  2. John Anvik
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  3. Răzvan Andonie
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Corresponding author

Correspondence to Adrian-Cătălin Florea .

Editor information

Editors and Affiliations

  1. University of Lausanne, Lausanne, Switzerland

    Alessandra Lintas

  2. University of Genoa, Genoa, Italy

    Stefano Rovetta

  3. Universitat Pompeu Fabra, Barcelona, Spain

    Paul F.M.J. Verschure

  4. University of Lausanne, Lausanne, Switzerland

    Alessandro E.P. Villa

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Florea, AC., Anvik, J., Andonie, R. (2017). Parallel Implementation of a Bug Report Assignment Recommender Using Deep Learning. In: Lintas, A., Rovetta, S., Verschure, P., Villa, A. (eds) Artificial Neural Networks and Machine Learning – ICANN 2017. ICANN 2017. Lecture Notes in Computer Science(), vol 10614. Springer, Cham. https://doi.org/10.1007/978-3-319-68612-7_8

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  • DOI: https://doi.org/10.1007/978-3-319-68612-7_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68611-0

  • Online ISBN: 978-3-319-68612-7

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