  We report (to our knowledge) the first evaluation of Constraint Satisfaction
as a computational framework for solving closest string problems. We show that
careful consideration of symbol occurrences can provide search heuristics that
provide several orders of magnitude speedup at and above the optimal distance.
We also report (to our knowledge) the first analysis and evaluation -- using
any technique -- of the computational difficulties involved in the
identification of all closest strings for a given input set. We describe
algorithms for web-scale distributed solution of closest string problems, both
purely based on AI backtrack search and also hybrid numeric-AI methods.
