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Taming Software Variability: Ontological Foundations of Variability Mechanisms

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Conceptual Modeling (ER 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9381))

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Abstract

Variability mechanisms are techniques applied to adapt software product line (SPL) artifacts to the context of particular products, promoting systematic reuse of those artifacts. Despite the large variety of mechanisms reported in the literature, a catalog of variability mechanisms is built ad-hoc and lacks systematization. In this paper we propose an ontologically-grounded theoretical framework for mathematically characterizing well-known variability mechanisms based on analysis of software behavior. We distinguish between variability in the product dimension, which refers to differences in the sets of product’s behaviors, and variability in the element dimension, which focuses on differences in the particular behaviors.

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Author information

Authors and Affiliations

  1. Department of Information Systems, University of Haifa, Haifa, Israel

    Iris Reinhartz-Berger & Anna Zamansky

  2. Sauder School of Business, University of British Columbia, Vancouver, Canada

    Yair Wand

Authors
  1. Iris Reinhartz-Berger
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  2. Anna Zamansky
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  3. Yair Wand
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Corresponding author

Correspondence to Iris Reinhartz-Berger .

Editor information

Editors and Affiliations

  1. Stockholm University, Kista, Sweden

    Paul Johannesson

  2. National University of Singapore, Singapore, Singapore

    Mong Li Lee

  3. Brigham Young University, Provo, Utah, USA

    Stephen W. Liddle

  4. University of Bergen, Bergen, Norway

    Andreas L. Opdahl

  5. Universidad Politécnica de Valencia, Valencia, Spain

    Óscar Pastor López

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© 2015 Springer International Publishing Switzerland

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Reinhartz-Berger, I., Zamansky, A., Wand, Y. (2015). Taming Software Variability: Ontological Foundations of Variability Mechanisms. In: Johannesson, P., Lee, M., Liddle, S., Opdahl, A., Pastor López, Ó. (eds) Conceptual Modeling. ER 2015. Lecture Notes in Computer Science(), vol 9381. Springer, Cham. https://doi.org/10.1007/978-3-319-25264-3_29

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  • DOI: https://doi.org/10.1007/978-3-319-25264-3_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25263-6

  • Online ISBN: 978-3-319-25264-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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