Foundations of logic programming
Foundations of logic programming
Petri nets: an introduction
The C programming language
Journal of the ACM (JACM)
Computability, complexity, and languages (2nd ed.): fundamentals of theoretical computer science
Computability, complexity, and languages (2nd ed.): fundamentals of theoretical computer science
A partial order approach to branching time logic model checking
Information and Computation
The Semantics of Predicate Logic as a Programming Language
Journal of the ACM (JACM)
Model checking
Partial-Order Methods for the Verification of Concurrent Systems: An Approach to the State-Explosion Problem
Logic programs with stable model semantics as a constraint programming paradigm
Annals of Mathematics and Artificial Intelligence
Relaxed Visibility Enhances Partial Order Reduction
CAV '97 Proceedings of the 9th International Conference on Computer Aided Verification
Stubborn Sets for Standard Properties
Proceedings of the 20th International Conference on Application and Theory of Petri Nets
All from One, One for All: on Model Checking Using Representatives
CAV '93 Proceedings of the 5th International Conference on Computer Aided Verification
Towards Ambitious Approximation Algorithms in Stubborn Set Optimization
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P'2002), Part 1
Minimizing the Number of Successor States in the Stubborn Set Method
Fundamenta Informaticae - Concurrency Specification and Programming Workshop (CS&P'2001)
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The stubborn set method is one of the methods that try to relieve the state space explosion problem that occurs in state space generation. Spending some time in looking for “good” stubborn sets can pay off in the total time spent in generating a reduced state space. This article shows how the method can exploit tools that solve certain problems of logic programs. The restriction of a definition of stubbornness to a given state can be translated into a variable-free logic program. When a stubborn set satisfying additional constraints is wanted, the additional constraints should be translated, too. It is easy to make the translation in such a way that each acceptable stubborn set of the state is represented by at least one stable model of the program, each stable model of the program represents at least one acceptable stubborn set of the state, and for each pair in the representation relation, the number of certain atoms in the stable model is equal to the number of enabled transitions of the represented stubborn set. So, in order to find a stubborn set which is good w.r.t. the number of enabled transitions, it suffices to find a stable model which is good w.r.t. the number of certain atoms. The article also presents a new NP-completeness result concerning stubborn sets.