  We describe an extensive study of search in GSAT, an approximation procedure
for propositional satisfiability. GSAT performs greedy hill-climbing on the
number of satisfied clauses in a truth assignment. Our experiments provide a
more complete picture of GSAT's search than previous accounts. We describe in
detail the two phases of search: rapid hill-climbing followed by a long plateau
search. We demonstrate that when applied to randomly generated 3SAT problems,
there is a very simple scaling with problem size for both the mean number of
satisfied clauses and the mean branching rate. Our results allow us to make
detailed numerical conjectures about the length of the hill-climbing phase, the
average gradient of this phase, and to conjecture that both the average score
and average branching rate decay exponentially during plateau search. We end by
showing how these results can be used to direct future theoretical analysis.
This work provides a case study of how computer experiments can be used to
improve understanding of the theoretical properties of algorithms.
