## Some Pitfalls for Experimenters with Random SAT (1996)

Venue: | Artificial Intelligence |

Citations: | 19 - 3 self |

### BibTeX

@ARTICLE{Mitchell96somepitfalls,

author = {David G. Mitchell and Hector J. Levesque},

title = {Some Pitfalls for Experimenters with Random SAT},

journal = {Artificial Intelligence},

year = {1996},

volume = {81},

pages = {81--1}

}

### Years of Citing Articles

### OpenURL

### Abstract

We consider the use of random CNF formulas in evaluating the performance of SAT testing algorithms, and in particular the role that the phase transition phenomenon plays in this use. Examples from the literature illustrate the importance of understanding the properties of formula distributions prior to designing an experiment. We expect this to be of increasing importance in the field. 1 Introduction Satisfiability testing lies at the core of many computational problems and because of its close relationship to various reasoning tasks, this is especially so in Artificial Intelligence. Randomly generated CNF formulas are a popular class of test problems for evaluating the performance of SAT testing programs. Not surprisingly, the choice of formula distribution is crucial to the validity of any investigation using random formulas. In [23], we argued that some families of distributions were more useful sources of test material than others, and suggested choosing formulas from the "hard reg...