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Jaskier: A Supporting Software Tool for Continuous Build Outcome Prediction Practice

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Advances and Trends in Artificial Intelligence. From Theory to Practice (IEA/AIE 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12799))

Abstract

Continuous Defect Prediction (CDP) is an assisting software development practice that combines Software Defect Prediction (SDP) with machine learning aided modelling and continuous developer feedback. Jaskier is a set of software tools developed under the supervision and with the participation of the authors of the article that implements a lightweight version of CDP called Continuous Build Outcome Prediction (CBOP). CBOP uses classification to label the possible build results based on historical data and metrics derived from the software repository. This paper contains a detailed description of the tool that was already started to be used in the production environment of a real software project where the CBOP practice is being evaluated.

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Notes

  1. 1.

    Jaskier is a code name we have used to develop the software at a company one of the authors is running. Jaskier in Polish means buttercup – a small yellow flower common in Poland.

  2. 2.

    https://github.com/libgit2/libgit2sharp.

  3. 3.

    https://simpleinjector.org/.

  4. 4.

    https://github.com/ImpressiveCode/ic-jaskier.

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Authors and Affiliations

  1. CODEFUSION Sp. z o.o. and Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Opole, Poland

    Marcin Kawalerowicz

  2. Faculty of Computer Science and Management, Wroclaw University of Science and Technology, Wrocław, Poland

    Lech Madeyski

Authors
  1. Marcin Kawalerowicz
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  2. Lech Madeyski
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Corresponding author

Correspondence to Marcin Kawalerowicz .

Editor information

Editors and Affiliations

  1. i-SOMET Incorporate Association, Morioka, Japan

    Hamido Fujita

  2. Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

    Ali Selamat

  3. Western Norway University of Applied Sciences, Bergen, Norway

    Jerry Chun-Wei Lin

  4. Texas State University San Marcos, San Marcos, TX, USA

    Moonis Ali

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Kawalerowicz, M., Madeyski, L. (2021). Jaskier: A Supporting Software Tool for Continuous Build Outcome Prediction Practice. In: Fujita, H., Selamat, A., Lin, J.CW., Ali, M. (eds) Advances and Trends in Artificial Intelligence. From Theory to Practice. IEA/AIE 2021. Lecture Notes in Computer Science(), vol 12799. Springer, Cham. https://doi.org/10.1007/978-3-030-79463-7_36

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  • DOI: https://doi.org/10.1007/978-3-030-79463-7_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-79462-0

  • Online ISBN: 978-3-030-79463-7

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