IP Validation using Genetic Algorithms guided by Mutation Testing
Résumé
In this article, we propose a new approach that jointly qualifies and improves Intellectual Properties (IP) validation. This approach uses the Mutation Testing as an evaluation metric (i.e. Mutation Score) and Genetic Algorithm (GA) to improve validation data. Adaptive GA operators (e.g. crossover and genetic mutation) for the generation of test data are presented. Experimental results obtained on ITC'99 benchmark RTL descriptions show the Mutation Score (MS) enhancement achieved and compare this metric to classical metrics.