Markov modelling and parameterisation of genetic evolutionary test generations

Genetic evolutionary algorithm is an effective and optimal test generation method. However, the method to select the algorithm parameters is often ad hoc relying on empirical data. We use Markov-based method to model the genetic evolutionary test generation process, parameterise the process characteristics, and derive analytical solutions for selecting the optimisation parameters. The method eliminates preliminary test generation calibration and experimentation effort needed to select these parameters used in current practice.