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Statistical Model Checking of Dynamic Networks of Stochastic Hybrid Automata

机译:随机混合自动机动态网络的统计模型检验

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In this paper we present a modelling formalism for dynamic networksof stochastic hybrid automata. In particular, our formalism is based on primitivesfor the dynamic creation and termination of hybrid automata components duringthe execution of a system. In this way we allow for natural modelling of conceptssuch as multiple threads found in various programming paradigms, as well as thedynamic evolution of biological systems.We provide a natural stochastic semantics of the modelling formalism based on re-peated output races between the dynamic evolving components of a system. Asspecification language we present a quantified extension of the logic Metric Tempo-ral Logic (MTL). As a main contribution of this paper, the statistical model checkingengine of U PPAAL has been extended to the setting of dynamic networks of hybridsystems and quantified MTL. We demonstrate the usefulness of the extended for-malisms in an analysis of a dynamic version of the well-known Train Gate example,as well as in natural monitoring of a MTL formula, where observations may lead todynamic creation of monitors for sub-formulas.
机译:在本文中,我们提出了一种随机混合自动机动态网络的建模形式主义。特别地,我们的形式主义基于用于在系统执行期间动态创建和终止混合自动机组件的原语。这样,我们就可以对概念进行自然建模,例如在各种编程范例中找到多线程,以及生物系统的动态演化。我们基于动态演化组件之间的重复输出竞争,提供了建模形式主义的自然随机语义。一个系统。作为规范语言,我们提出了逻辑度量时间逻辑(MTL)的量化扩展。作为本文的主要贡献,U PPAAL的统计模型检查引擎已扩展到混合系统动态网络和量化MTL的设置。我们在分析著名的Train Gate示例的动态版本以及对MTL公式进行自然监视(其中观察可能导致动态创建子公式的监视程序)的过程中,证明了扩展形式主义的有用性。

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