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Managing Variability in Workflow with Feature Model Composition Operators

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Software Composition (SC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 6144))

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Abstract

In grid-based scientific applications, building a workflow essentially involves composing parameterized services describing families of services and then configuring the resulting workflow product line. In domains (e.g., medical imaging) in which many different kinds of highly parameterized services exist, there is a strong need to manage variabilities so that scientists can more easily configure and compose services with consistency guarantees. In this paper, we propose an approach in which variable points in services are described with several separate feature models, so that families of workflow can be defined as compositions of feature models. A compositional technique then allows reasoning about the compatibility between connected services to ensure consistency of an entire workflow, while supporting automatic propagation of variability choices when configuring services.

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Author information

Authors and Affiliations

  1. I3S Laboratory (CNRS UMR 6070), University of Nice Sophia Antipolis, France, 06903, Sophia Antipolis Cedex, France

    Mathieu Acher, Philippe Collet & Philippe Lahire

  2. Computer Science Department, Colorado State University, USA

    Robert France

Authors
  1. Mathieu Acher
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  2. Philippe Collet
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  3. Philippe Lahire
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  4. Robert France
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Editor information

Editors and Affiliations

  1. INRIA Rennes Bretagna Atlantique, Campus de Beaulieu, 35042, Rennes Cedex, France

    Benoît Baudry

  2. Department of Computer Science, University of British Columbia, 351-2366 Main Mall, V6T 1Z4, Vancouver, BC, Canada

    Eric Wohlstadter

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Acher, M., Collet, P., Lahire, P., France, R. (2010). Managing Variability in Workflow with Feature Model Composition Operators. In: Baudry, B., Wohlstadter, E. (eds) Software Composition. SC 2010. Lecture Notes in Computer Science, vol 6144. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14046-4_2

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  • DOI: https://doi.org/10.1007/978-3-642-14046-4_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14045-7

  • Online ISBN: 978-3-642-14046-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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