概率模型检验模理论

Björn Wachter, Lijun Zhang, H. Hermanns
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引用次数: 52

摘要

概率模型被广泛用于分析嵌入式、网络化以及最近的生物系统。现有的数值分析技术仅限于有限状态模型,存在状态爆炸问题。因此,用户通常必须手动抽象预期的模型以获得易于处理的模型。为此,我们提出了谓词抽象模型检查器PASS,它可以自动化这一过程。我们利用自动定理证明的最新进展来计算可处理的有限状态模型。实验证明了该方法的可行性。据我们所知,这是概率无限状态模型的性质第一次在这种自动化水平上得到验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Probabilistic Model Checking Modulo Theories
Probabilistic models are widely used to analyze embedded, networked, and more recently biological systems. Existing numerical analysis techniques are limited to finite- state models and suffer from the state explosion problem. As a consequence, the user often has to manually abstract the intended model to get a tractable one. To this end, we propose the predicate abstraction model checker PASS which automates this process. We leverage recent advances in automatic theorem proving to compute tractable finite-state models. Experiments show the feasibility of our approach. To the best of our knowledge, this is the first time that properties of probabilistic infinite-state models have been verified at this level of automation.
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