Deep random search for efficient model checking of timed automata

被引:0
|
作者
Grosu, R. [1 ]
Huang, X. [1 ]
Smolka, S. A. [1 ]
Tan, W. [1 ]
Tripakis, S. [2 ]
机构
[1] SUNY Stony Brook, Dept CS, Stony Brook, NY 11794 USA
[2] Verimag, Ctr Equat, F-38610 Gieres, France
关键词
D O I
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中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
We present DRS (Deep Random Search), a new Las Vegas algorithm for model checking safety properties of timed automata. DRS explores the state space of the simulation graph of a timed automaton by performing random walks up to a prescribed depth. Nodes along these walks are then used to construct a random fringe, which is the starting point of additional deep random walks. The DRS algorithm is complete, and optimal to within a specified depth increment. Experimental results show that it is able to find extremely deep counter-examples for a number of benchmarks, outperforming Open-Kronos and UPPAAL in the process.
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收藏
页码:111 / +
页数:2
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