Polynomial-average-time satisfiability problems
Information Sciences: an International Journal
Probabilistic performance of a heuristic for the satisfiability problem
Discrete Applied Mathematics
CNF satisfiability test by counting and polynomial average time
SIAM Journal on Computing
Exponential average time for the pure literal rule
SIAM Journal on Computing
Algorithms for testing the satisfiability of propositional formulae
Journal of Logic Programming
Extended Horn sets in propositional logic
Journal of the ACM (JACM)
A survey of average time analyses of satisfiability algorithms
Journal of Information Processing
Elimination of infrequent variables improves average case performance of satisfiability algorithms
SIAM Journal on Computing
On the occurrence of null clauses in random instances of satisfiability
Discrete Applied Mathematics
On finding solutions for extended Horn formulas
Information Processing Letters
The arborescence-realization problem
Discrete Applied Mathematics
A Computing Procedure for Quantification Theory
Journal of the ACM (JACM)
Renaming a Set of Clauses as a Horn Set
Journal of the ACM (JACM)
A machine program for theorem-proving
Communications of the ACM
Satisfiability threshold of the skewed random k-SAT
SAT'04 Proceedings of the 7th international conference on Theory and Applications of Satisfiability Testing
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In the probabilistic analysis of algorithms for the Satisfiability problem, the random‐clause‐width model is one of the most popular for generating random formulas. This model is parameterized and it is not difficult to show that virtually the entire parameter space is covered by a collection of polynomial time algorithms that find solutions to random formulas with probability tending to 1 as formula size increases. But finding a collection of polynomial average time algorithms that cover the parameter space has proved much harder and such results have spanned approximately ten years. However, it can now be said that virtually the entire parameter space is covered by polynomial average time algorithms. This paper relates dominant, exploitable properties of random formulas over the parameter space to mechanisms of polynomial average time algorithms. The probabilistic discussion of such properties is new; main average‐case results over the last ten years are reviewed.