Backbone Fragility and the Local Search Cost Peak
  The local search algorithm WSat is one of the most successful algorithms for
solving the satisfiability (SAT) problem. It is notably effective at solving
hard Random 3-SAT instances near the so-called `satisfiability threshold', but
still shows a peak in search cost near the threshold and large variations in
cost over different instances. We make a number of significant contributions to
the analysis of WSat on high-cost random instances, using the
recently-introduced concept of the backbone of a SAT instance. The backbone is
the set of literals which are entailed by an instance. We find that the number
of solutions predicts the cost well for small-backbone instances but is much
less relevant for the large-backbone instances which appear near the threshold
and dominate in the overconstrained region. We show a very strong correlation
between search cost and the Hamming distance to the nearest solution early in
WSat's search. This pattern leads us to introduce a measure of the backbone
fragility of an instance, which indicates how persistent the backbone is as
clauses are removed. We propose that high-cost random instances for local
search are those with very large backbones which are also backbone-fragile. We
suggest that the decay in cost beyond the satisfiability threshold is due to
increasing backbone robustness (the opposite of backbone fragility). Our
hypothesis makes three correct predictions. First, that the backbone robustness
of an instance is negatively correlated with the local search cost when other
factors are controlled for. Second, that backbone-minimal instances (which are
3-SAT instances altered so as to be more backbone-fragile) are unusually hard
for WSat. Third, that the clauses most often unsatisfied during search are
those whose deletion has the most effect on the backbone. In understanding the
pathologies of local search methods, we hope to contribute to the development
of new and better techniques.
