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Interpreting Intermittent Bugs in Mozilla Applications Using Change Angle

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Data Mining (AusDM 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 996))

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Abstract

Learning in evolving environments involves learning from data where the statistical characteristics can change over time. Current change detection algorithms that are used online for data streams detect whether a change has occurred in the data but there is always a detection delay. None of the existing online techniques can accurately pin-point the exact location of when the change starts to occur, which can be critical. We present a novel method Change Angle and we show, for the first time, how to pin-point online the location at which change starts to occur. We apply our Change Angle method in the application area of software revision control using Mozilla data, where it is important to detect not only the presence of change but also to pin-point accurately the location of when change starts to occur.

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Acknowledgment

We thank all Mozilla engineers that were involved in the development of this research project especially Kyle Lahnakoski, Joel Maher, and Jonathan Griffin for helping us acquire access to the relevant data and validate the work.

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Authors and Affiliations

  1. Department of Computer Science, University of Auckland, Auckland, New Zealand

    David Tse Jung Huang, Yun Sing Koh & Gillian Dobbie

Authors
  1. David Tse Jung Huang
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  2. Yun Sing Koh
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  3. Gillian Dobbie
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Corresponding author

Correspondence to David Tse Jung Huang .

Editor information

Editors and Affiliations

  1. School of Computing and Mathematics, Charles Sturt University, Albury, NSW, Australia

    Rafiqul Islam

  2. University of Auckland, Auckland, New Zealand

    Yun Sing Koh

  3. CSIRO Scientific Computing, Canberra, Australia

    Yanchang Zhao

  4. Data Science and Engineering, Australian Taxation Office, Canberra, Australia

    Graco Warwick

  5. Department of Information Technology, University of Wollongong, Wollongong, NSW, Australia

    David Stirling

  6. School of Computing and Mathematics, Charles Sturt University, Wagga Wagga, Australia

    Chang-Tsun Li

  7. School of Computing and Mathematics, Charles Sturt University, Bathurst, Australia

    Zahidul Islam

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Huang, D.T.J., Koh, Y.S., Dobbie, G. (2019). Interpreting Intermittent Bugs in Mozilla Applications Using Change Angle. In: Islam, R., et al. Data Mining. AusDM 2018. Communications in Computer and Information Science, vol 996. Springer, Singapore. https://doi.org/10.1007/978-981-13-6661-1_25

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  • DOI: https://doi.org/10.1007/978-981-13-6661-1_25

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6660-4

  • Online ISBN: 978-981-13-6661-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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