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National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Counter-Example Generation in the Analysis of Markov Models
 Molek, Martin ; Matyáš, Jiří (referee) ; Češka, Milan (advisor)
This thesis deals with generating counterexamples in context of probabilistic models. Counterexamples are generated for Markov models (specifically DTMC). Definitions of model properties are given by logic PCTL. Two algorithms (Best-first search and Recursive Enumration Algorithm) are used to generate these counterexamples. Thesis describes implementation of algorithms into verification tool STORM. The results of experiments show that REA is capable of handling models containg millions of states.
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Counter-Example Generation in the Analysis of Markov Models
 Molek, Martin ; Matyáš, Jiří (referee) ; Češka, Milan (advisor)
This thesis deals with generating counterexamples in context of probabilistic models. Counterexamples are generated for Markov models (specifically DTMC). Definitions of model properties are given by logic PCTL. Two algorithms (Best-first search and Recursive Enumration Algorithm) are used to generate these counterexamples. Thesis describes implementation of algorithms into verification tool STORM. The results of experiments show that REA is capable of handling models containg millions of states.
Detailed record

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