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Interactive Measures for Mining Understandable State Machines from Embedded Software: Experiments and Case Studies

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Model-Driven Engineering and Software Development (MODELSWARD 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 991))

Abstract

State machines are a commonly used formalism for specifying the behavior of a software component, which could also be helpful for program comprehension. Therefore, it is desirable to extract state machine models from code and also from legacy models. The main drawback of fully-automatic state machine mining approaches is that the mined models are too detailed and not understandable. In our previous work [1], we presented different measures for the interaction with the state machine extraction process, such as selecting a subset of state variables, reducing the state variable range and providing additional user constraints. These measures aimed to reduce the complexity of the mined state machines to an understandable degree. In this article, which is an extended version of [1], we evaluate the approach through a case study with twelve professional developers from the automotive supplier company Bosch. The study shows that adding our interactive measures to the model mining process leads to understandable state machines, which can be very helpful in a rich set of use cases in addition to program comprehension, such as debugging, validation and verification. Furthermore, we conduct an experiment to evaluate the required computation time of the interactive measures against the fully-automatic mining. The experiment shows that the interactive approach can drastically reduce the computation time.

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Notes

  1. 1.

    https://www.etas.com/en/products/ascet_software_products.php.

  2. 2.

    https://www.mathworks.com/products/simulink.html.

  3. 3.

    The combination of all Es from symbolic execution defines the function f.

  4. 4.

    In all our experiments in this paper, we concentrate on the structure and complexity of the resulting state machines regarding the number of states and transitions. Therefore, we do not show transition conditions in the figures.

  5. 5.

    In the figure, we show only five states, because the other five states (with !Sync) are not connected by any transitions.

  6. 6.

    http://www-03.ibm.com/software/products/de/ratirhap.

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Author information

Authors and Affiliations

  1. Robert Bosch GmbH, Corporate Research, Renningen, Germany

    Wasim Said & Jochen Quante

  2. University of Bremen, Bremen, Germany

    Wasim Said & Rainer Koschke

Authors
  1. Wasim Said
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  2. Jochen Quante
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  3. Rainer Koschke
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Corresponding author

Correspondence to Wasim Said .

Editor information

Editors and Affiliations

  1. Université d’Angers/ESEO, Angers, France

    Slimane Hammoudi

  2. University of Twente, Enschede, The Netherlands

    Luís Ferreira Pires

  3. Malina Software Corp., Nepean, ON, Canada

    Bran Selic

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Said, W., Quante, J., Koschke, R. (2019). Interactive Measures for Mining Understandable State Machines from Embedded Software: Experiments and Case Studies. In: Hammoudi, S., Pires, L., Selic, B. (eds) Model-Driven Engineering and Software Development. MODELSWARD 2018. Communications in Computer and Information Science, vol 991. Springer, Cham. https://doi.org/10.1007/978-3-030-11030-7_10

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  • DOI: https://doi.org/10.1007/978-3-030-11030-7_10

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  • Online ISBN: 978-3-030-11030-7

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