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arXiv 1111.0370cs.SEcs.DC
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分布式参数和统计模型检验

Distributed Parametric and Statistical Model Checking

Peter Bulychev, Alexandre David, Kim Guldstrand Larsen, Marius Mikučionis, Axel Legay

摘要:

统计模型检验(SMC)是测试和形式化验证之间的折衷。该方法的核心思想是对系统进行一些模拟,并验证它们是否满足某些给定的性质。在本文中,我们表明,SMC是很容易并行化的主/从架构,通过引入一系列的算法,规模几乎线性相对于从计算机的数量。我们的方法已在UPPAAL SMC工具集中实现,并应用于非平凡的案例研究。

英文摘要:

Statistical Model Checking (SMC) is a trade-off between testing and formal verification. The core idea of the approach is to conduct some simulations of the system and verify if they satisfy some given property. In this paper we show that SMC is easily parallelizable on a master/slaves architecture by introducing a series of algorithms that scale almost linearly with respect to the number of slave computers. Our approach has been implemented in the UPPAAL SMC toolset and applied on non-trivial case studies.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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