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Model Learning and Model-Based Testing

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Machine Learning for Dynamic Software Analysis: Potentials and Limits

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11026))

Abstract

We present a survey of the recent research efforts in integrating model learning with model-based testing. We distinguished two strands of work in this domain, namely test-based learning (also called test-based modeling) and learning-based testing. We classify the results in terms of their underlying models, their test purpose and techniques, and their target domains.

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Notes

  1. 1.

    The authors also briefly discuss stochastic properties of Mealy machines, though.

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Acknowledgments

The insightful comments of Karl Meinke and Neil Walkinshaw on an earlier draft led to improvements and are gratefully acknowledged.

The work of B. K. Aichernig and M. Tappler was supported by the TU Graz LEAD project “Dependable Internet of Things in Adverse Environments”. The work of M. R. Mousavi and M. Taromirad has been partially supported by the Swedish Research Council (Vetenskapsradet) award number: 621-2014-5057 (Effective Model-Based Testing of Concurrent Systems) and the Strategic Research Environment ELLIIT. The work of M. R. Mousavi has also been partially supported by the Swedish Knowledge Foundation (Stiftelsen for Kunskaps- och Kompetensutveckling) in the context of the AUTO-CAAS HöG project (number: 20140312).

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Authors and Affiliations

  1. Institute of Software Technology, Graz University of Technology, Graz, Austria

    Bernhard K. Aichernig & Martin Tappler

  2. Centre for Research on Embedded Systems, Halmstad University, Halmstad, Sweden

    Wojciech Mostowski, Mohammad Reza Mousavi & Masoumeh Taromirad

  3. Department of Informatics, University of Leicester, Leicester, UK

    Mohammad Reza Mousavi

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  1. Bernhard K. Aichernig
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  2. Wojciech Mostowski
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  3. Mohammad Reza Mousavi
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  4. Martin Tappler
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  5. Masoumeh Taromirad
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Correspondence to Mohammad Reza Mousavi .

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  1. The Open University, Milton Keynes, United Kingdom

    Amel Bennaceur

  2. Technische Universität Darmstadt, Darmstadt, Germany

    Reiner Hähnle

  3. KTH Royal Institute of Technology, Stockholm, Sweden

    Karl Meinke

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Aichernig, B.K., Mostowski, W., Mousavi, M.R., Tappler, M., Taromirad, M. (2018). Model Learning and Model-Based Testing. In: Bennaceur, A., Hähnle, R., Meinke, K. (eds) Machine Learning for Dynamic Software Analysis: Potentials and Limits. Lecture Notes in Computer Science(), vol 11026. Springer, Cham. https://doi.org/10.1007/978-3-319-96562-8_3

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