Crossover can be constructive when computing unique input–output sequences

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25 Citations (Scopus)


Unique input-output (UIO) sequences have important applications in conformance testing of finite state machines (FSMs). Previous experimental and theoretical research has shown that evolutionary algorithms (EAs) can compute UIOs efficiently on many FSM instance classes, but fail on others. However, it has been unclear how and to what degree EA parameter settings influence the runtime on the UIO problem. This paper investigates the choice of acceptance criterion in the (1 + 1) EA and the use of crossover in the (mu + 1) Steady State Genetic Algorithm. It is rigorously proved that changing these parameters can reduce the runtime from exponential to polynomial for some instance classes of the UIO problem.
Original languageEnglish
Pages (from-to)1675-1687
Number of pages13
JournalSoft Computing
Issue number9
Early online date9 Jun 2010
Publication statusPublished - 1 Sept 2011


  • Unique input-output sequences
  • Crossover operator
  • Evolutionary algorithms
  • Finite state machines
  • Runtime analysis


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