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  • Sequential Schemes for Frequentist Estimation of Properties in Statistical Model Checking

    Author(s)
    Jegourel, Cyrille
    Sun, Jun
    Dong, Jin Song
    Griffith University Author(s)
    Dong, Jin-Song
    Year published
    2019
    Metadata
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    Abstract
    Statistical Model Checking (SMC) is an approximate verification method that overcomes the state space explosion problem for probabilistic systems by Monte Carlo simulations. Simulations might, however, be costly if many samples are required. It is thus necessary to implement efficient algorithms to reduce the sample size while preserving precision and accuracy. In the literature, some sequential schemes have been provided for the estimation of property occurrence based on predefined confidence and absolute or relative error. Nevertheless, these algorithms remain conservative and may result in huge sample sizes if the required ...
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    Statistical Model Checking (SMC) is an approximate verification method that overcomes the state space explosion problem for probabilistic systems by Monte Carlo simulations. Simulations might, however, be costly if many samples are required. It is thus necessary to implement efficient algorithms to reduce the sample size while preserving precision and accuracy. In the literature, some sequential schemes have been provided for the estimation of property occurrence based on predefined confidence and absolute or relative error. Nevertheless, these algorithms remain conservative and may result in huge sample sizes if the required precision standards are demanding. In this article, we compare some useful bounds and some sequential methods. We propose outperforming and rigorous alternative schemes based on Massart bounds and robust confidence intervals. Our theoretical and empirical analyses show that our proposal reduces the sample size while providing the required guarantees on error bounds.
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    Journal Title
    ACM Transactions on Modeling and Computer Simulation
    Volume
    29
    Issue
    4
    DOI
    https://doi.org/10.1145/3310226
    Subject
    Theory of computation
    Information systems
    Science & Technology
    Technology
    Physical Sciences
    Computer Science, Interdisciplinary Applications
    Mathematics, Applied
    Publication URI
    http://hdl.handle.net/10072/393162
    Collection
    • Journal articles

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