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Aspect-Oriented Modeling of Mutual Exclusion in UML State Machines

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Modelling Foundations and Applications (ECMFA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7349))

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Abstract

Mutual exclusion is a very common requirement in parallel systems. Yet its modeling is a tedious task in UML state machines, one of the most popular languages for behavior modeling. We present HiLA, an aspect-oriented extension of UML state machines, to address this problem. In HiLA, mutual exclusion can be modeled in a highly modular and declarative way. That is, the logic of mutual exclusion is modeled at a dedicated place rather than by model elements scattered all over the state machine, and the modeler only needs to specify which states to mutually exclude rather than how to exclude them.

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Authors and Affiliations

  1. arvato systems Technologies GmbH, Germany

    Gefei Zhang

Authors
  1. Gefei Zhang
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Editor information

Editors and Affiliations

  1. Universidad de Málaga, ETSI Informâtica, Campus de Teatinos, Bulevar Louis Pasteur 35, 29071, Málaga, Spain

    Antonio Vallecillo

  2. MetaCase, Ylistönmäentie 31, 40500, Jyväskylä, Finland

    Juha-Pekka Tolvanen

  3. Department of Informatics and Mathematical Modelling, Technical University of Denmark, Richard Petersens Plads, 2800, Kgs. Lyngby, Denmark

    Ekkart Kindler  & Harald Störrle  & 

  4. Department of Computer Science, University of York, Deramore Lane, YO10 5GH, York, United Kingdom

    Dimitris Kolovos

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© 2012 Springer-Verlag Berlin Heidelberg

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Zhang, G. (2012). Aspect-Oriented Modeling of Mutual Exclusion in UML State Machines. In: Vallecillo, A., Tolvanen, JP., Kindler, E., Störrle, H., Kolovos, D. (eds) Modelling Foundations and Applications. ECMFA 2012. Lecture Notes in Computer Science, vol 7349. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31491-9_14

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  • DOI: https://doi.org/10.1007/978-3-642-31491-9_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31490-2

  • Online ISBN: 978-3-642-31491-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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