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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9952))

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Abstract

Statistical Model Checking (SMC) is a compromise between verification and testing where executions of the systems are monitored until an algorithm from statistics can produce an estimate for the system to satisfy a given property.

The objective of this introduction is to summarizes SMC as well as a series of challenges for which contributors at Isola propose a solution.

Contributions include new SMC toolsets, new flexible SMC algorithms for larger classes of systems, and new applications.

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Notes

  1. 1.

    As we shall see later, stochastic systems may deal with additional quantities such as real-time.

  2. 2.

    This thesis is not concerned with the definition of efficient monitoring procedures.

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Correspondence to Axel Legay .

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Larsen, K.G., Legay, A. (2016). Statistical Model Checking: Past, Present, and Future. In: Margaria, T., Steffen, B. (eds) Leveraging Applications of Formal Methods, Verification and Validation: Foundational Techniques. ISoLA 2016. Lecture Notes in Computer Science(), vol 9952. Springer, Cham. https://doi.org/10.1007/978-3-319-47166-2_1

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