Abstract
We describe a new and more efficient algorithm for checking universality and language inclusion on nondeterministic finite word automata (NFA) and tree automata (TA). To the best of our knowledge, the antichain-based approach proposed by De Wulf et al. was the most efficient one so far. Our idea is to exploit a simulation relation on the states of finite automata to accelerate the antichain-based algorithms. Normally, a simulation relation can be obtained fairly efficiently, and it can help the antichain-based approach to prune out a large portion of unnecessary search paths. We evaluate the performance of our new method on NFA/TA obtained from random regular expressions and from the intermediate steps of regular model checking. The results show that our approach significantly outperforms the previous antichain-based approach in most of the experiments.
This work was supported in part by the Royal Society grant JP080268, the Czech Science Foundation (projects P103/10/0306, 102/09/H042), the Czech COST project OC10009 associated with the ESF COST action IC0901, the Czech Ministry of Education by the project MSM 0021630528, the UPMARC project, the CONNECT project, and the ESF project Games for Design and Verification.
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Keywords
- Tree Automaton
- Simulation Relation
- Maximal Simulation
- Product Automaton
- Nondeterministic Finite Automaton
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Abdulla, P.A., Chen, YF., Holík, L., Mayr, R., Vojnar, T. (2010). When Simulation Meets Antichains. In: Esparza, J., Majumdar, R. (eds) Tools and Algorithms for the Construction and Analysis of Systems. TACAS 2010. Lecture Notes in Computer Science, vol 6015. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12002-2_14
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