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A Set of Metrics of Non-locality Complexity in UML State Machines

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Behavior Modeling -- Foundations and Applications

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6368))

Abstract

One of the barriers to widespread adoption of behavior modeling languages lies in the complexity of the models. We show in the context of UML state machines how non-locality, i.e., the information for the current behavior of a model being spread over several model elements instead of being locally available, may make seemingly intuitive and simple models rather complex and error-prone. We present a set of metrics to measure the complexity of UML state machines arising from different kinds of non-locality. Our metrics give a better understanding of the complexity of UML state machines, and may alert the modeler to pay more attention to pitfalls in apparently simple UML state machines.

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Notes

  1. 1.

    This example is inspired by [14].

  2. 2.

    Strictly using the terms defined in the UML Specification, this is a special case of the run-to-completion step. For simplicity, we do not use the concept run-to-completion in this paper. Since we ignore most of the pseudo states, see Sect. 3.1, a run-to-completion event is actually very similar to our execution step.

  3. 3.

    In other words, t is a target-unstructured transition, see below, Definition 3.

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Acknowledgment

This work has been partially sponsored by the EU project ASCENS, 257414.

Author information

Authors and Affiliations

  1. Celonis GmbH, München, Germany

    Gefei Zhang

  2. Ludwig-Maximilians-Universität München, München, Germany

    Matthias M. Hölzl

Authors
  1. Gefei Zhang
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  2. Matthias M. Hölzl
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Corresponding author

Correspondence to Gefei Zhang .

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Editors and Affiliations

  1. Open University of the Netherlands, Heerlen, The Netherlands

    Ella Roubtsova

  2. Metamaxim, London, United Kingdom

    Ashley McNeile

  3. Technical University of Denmark, Kgs. Lyngby, Denmark

    Ekkart Kindler

  4. Osnabrück University of Applied Sciences, Osnabrück, Germany

    Christian Gerth

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Zhang, G., Hölzl, M.M. (2015). A Set of Metrics of Non-locality Complexity in UML State Machines. In: Roubtsova, E., McNeile, A., Kindler, E., Gerth, C. (eds) Behavior Modeling -- Foundations and Applications. Lecture Notes in Computer Science(), vol 6368. Springer, Cham. https://doi.org/10.1007/978-3-319-21912-7_3

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  • DOI: https://doi.org/10.1007/978-3-319-21912-7_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21911-0

  • Online ISBN: 978-3-319-21912-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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