Hard and easy distributions of SAT problems

Authors:
David Mitchell;Bart Selman;Hector Levesque
Affiliations:
Dept. of Computing Science, Simon Fraser University, Burnaby, Canada;AT&T Bell Laboratories, Murray Hill, NJ;Dept. of Computer Science, University of Toronto, Toronto, Canada
Venue:
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Year:
1992

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Abstract

We report results from large-scale experiments in satisfiability testing. As has been observed by others, testing the satisfiability of random formulas often appears surprisingly easy. Here we show that by using the right distribution of instances, and appropriate parameter values, it is possible to generate random formulas that are hard, that is, for which satisfiability testing is quite difficult. Our results provide a benchmark for the evaluation of satisfiability-testing procedures.