Weak alternating automata are not that weak
ACM Transactions on Computational Logic (TOCL)
Communication and Concurrency
CONCUR '97 Proceedings of the 8th International Conference on Concurrency Theory
A Hierarchy of Polynomial-Time Computable Simulations for Automata
CONCUR '02 Proceedings of the 13th International Conference on Concurrency Theory
Efficient Büchi Automata from LTL Formulae
CAV '00 Proceedings of the 12th International Conference on Computer Aided Verification
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
Checking for Language Inclusion Using Simulation Preorders
CAV '91 Proceedings of the 3rd International Workshop on Computer Aided Verification
Applicability of fair simulation
Information and Computation
Fair Simulation Relations, Parity Games, and State Space Reduction for Büchi Automata
SIAM Journal on Computing
Finite automata and their decision problems
IBM Journal of Research and Development
Bridging the gap between fair simulation and trace inclusion
Information and Computation
CIAA'03 Proceedings of the 8th international conference on Implementation and application of automata
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Many verification approaches based on automata theory are related to the language containment problem, which is PSPACE-complete for nondeterministic automata. To avoid such a complexity, one may use simulation as an approximation to language containment, since simulation implies language containment and computing simulation is a polynomial time problem. As it is an approximation, there exists a gap between simulation and language containment, therefore there has been an effort to develop methods to narrow the gap while keeping the computation in polynomial time. In this paper, we present such an approach by building a Büchi automaton based on partial marked subset construction to be used in the computation of simulation relation, such that the automaton preserves the original language and has a structure that helps identify more pairs of automata that are in language containment relation. This approach is an improvement to the fair-k-simulation method [3].