Model-Based Testing of Stochastic Systems with IOCO Theory

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    Abstract

    We present essential concepts of a model-based testing framework for probabilistic systems with continuous time. Markov automata are used as an underlying model. Key result of the work is the solid core of a probabilistic test theory, that incorporates real-time stochastic behaviour. We connect ioco theory and hypothesis testing to infer about trace probabilities. We show that our conformance relation conservatively extends ioco and discuss the meaning of quiescence in the presence of exponentially distributed time delays.
    Original languageUndefined
    Title of host publicationProceedings of the 7th International Workshop on Automating Test Case Design, Selection, and Evaluation, A-TEST 2016
    Place of PublicationNew York
    PublisherAssociation for Computing Machinery (ACM)
    Pages45-51
    Number of pages7
    ISBN (Print)978-1-4503-4401-2
    DOIs
    Publication statusPublished - 18 Nov 2016

    Publication series

    Name
    PublisherACM

    Keywords

    • FMT-FMPA: FORMAL METHODS FOR PERFORMANCE ANALYSIS
    • EWI-27399
    • Markov Automata
    • IR-102861
    • IOCO
    • METIS-320887
    • Model-Based Testing

    Cite this

    Gerhold, M., & Stoelinga, M. I. A. (2016). Model-Based Testing of Stochastic Systems with IOCO Theory. In Proceedings of the 7th International Workshop on Automating Test Case Design, Selection, and Evaluation, A-TEST 2016 (pp. 45-51). New York: Association for Computing Machinery (ACM). https://doi.org/10.1145/2994291.2994298