Faster Algorithms for Finding Minimal Consistent DFAs

We describe exbar, a powerful new algorithm for the exact inference of minimal deterministic automata from given training data. This algorithm achieves the highest performance ever on a set of graded benchmark problems that has been posted by Arlindo Oliveira. In addition, we note that the inexact program ed-beam, which resulted from the Abbadingo DFA learning competition, also does well on this benchmark set, despite being designed for larger problems.

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