用公平假设有效地验证LTL

Yong Li, Lei Song, Yuan Feng, Lijun Zhang
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引用次数: 1

摘要

本文研究了公平性假设下LTL属性的模型检验问题。我们首先提出了一种有效的算法来处理公平假设的片段,然后将该算法扩展到处理任意的公平假设。值得注意的是,通过使用一些语法转换,我们的算法避免了为整个公平性假设构建相应的b chi自动机,这在实践中可能会非常大。我们在NuSMV中实现我们的算法,并考虑了大量的公式选择。我们的实验表明,在许多情况下,我们的方法在时间和内存方面都超过了自动机理论方法的几个数量级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Verify LTL with Fairness Assumptions Efficiently
This paper deals with model checking problems with respect to LTL properties under fairness assumptions. We first present an efficient algorithm to deal with a fragment of fairness assumptions and then extend the algorithm to handle arbitrary ones. Notably, by making use of some syntactic transformations, our algorithm avoids constructing corresponding Büchi automata for the whole fairness assumptions, which can be very large in practice. We implement our algorithm in NuSMV and consider a large selection of formulas. Our experiments show that in many cases our approach exceeds the automata-theoretic approach up to several orders of magnitude, in both time and memory.
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