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Formalization of Birth-Death and IID processes in higher-order logic

机译:在高阶逻辑中的出生死亡和IID进程的形式化

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Markov chains are extensively used in the modeling and analysis of engineering and scientific problems. Usually, paper-and-pencil proofs, simulation or computer algebra software are used to analyze Markovian models. However, these techniques either are not scalable or do not guarantee accurate results, which are vital in safety-critical systems. Probabilistic model checking has been proposed to formally analyze Markovian systems, but it suffers from the inherent state-explosion problem and unacceptable long computation times. Higher-order-logic theorem proving has been recently used to overcome the above-mentioned limitations but it lacks any support for discrete Birth-Death process and Independent and Identically Distributed (IID) random process, which are frequently used in many system analysis problems. In this paper, we formalize these notions using formal Discrete-Time Markov Chains (DTMC) with finite state-space and classified DTMCs in higher-order logic theorem proving. To demonstrate the usefulness of the formalizations, we present the formal performance analysis of two software applications.
机译:马尔可夫链广泛用于工程和科学问题的建模和分析。通常,纸张和铅笔证明,仿真或计算机代数软件用于分析马尔可夫模型。然而,这些技术要么不可扩展,要么不保证准确的结果,这在安全关键系统中至关重要。已经提出了概率模型检查以正式分析马尔可夫系统,但它受到固有的状态爆炸问题和不可接受的长计算时间。最近过去级逻辑定理证明克服了上述限制,但它缺乏对离散的出生死亡过程和独立和相同分布的(IID)随机过程的任何支持,这些过程经常用于许多系统分析问题。在本文中,我们使用正式的离散时间马尔可夫链(DTMC)在高阶逻辑定理中使用有限状态空间和分类的DTMC来形式化这些概念。为了展示形式化的有用性,我们提供了两个软件应用程序的正式性能分析​​。

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