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Conference Papers Year : 2018

Abstraction Refinement for Emptiness Checking of Alternating Data Automata

Radu Iosif
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Xiao Xu
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Alternating automata have been widely used to model and verify systems that handle data from finite domains, such as communication protocols or hardware. The main advantage of the alternating model of computation is that complementation is possible in linear time, thus allowing to concisely encode trace inclusion problems that occur often in verification. In this paper we consider alternating automata over infinite alphabets, whose transition rules are formulae in a combined theory of Booleans and some infinite data domain, that relate past and current values of the data variables. The data theory is not fixed, but rather it is a parameter of the class. We show that union, intersection and complementa-tion are possible in linear time in this model and, though the emptiness problem is undecidable, we provide two efficient semi-algorithms, inspired by two state-of-the-art abstraction refinement model checking methods: lazy predicate abstraction [8] and the Impact semi-algorithm [16]. We have implemented both methods and report the results of an experimental comparison.
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hal-02388034 , version 1 (30-11-2019)


  • HAL Id : hal-02388034 , version 1


Radu Iosif, Xiao Xu. Abstraction Refinement for Emptiness Checking of Alternating Data Automata. Tools and Algorithms for the Construction and Analysis of Systems - 24th International Conference, {TACAS} 2018, Apr 2018, Thessaloniki, Greece. ⟨hal-02388034⟩
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