The parallel induction algorithm discussed in the paper finds a minimal nondeterministic finite automaton (NFA) consistent with the given sample. The sample consists of examples and counterexamples, i.e., words that are accepted and rejected by the automaton. The algorithm transforms the problem to a family of constraint satisfaction problems solved in parallel. Only the first solution is sought, which means that upon finding a consistent automaton, the remaining processes terminate their execution. We analyze the parallel algorithm in terms of achieved speedups. In particular, we discuss the reasons of the observed superlinear speedups. The analysis includes experiments conducted for the samples defined over the alphabets of different sizes.
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