Application of Nature Inspired Algorithms to Test Data Generation/Selection/Minimization using Mutation Testing

This chapter builds the foundation of software testing techniques by classifying the various testing approaches and testing coverage criteria. It gradually advances in the concepts and process of Mutation Testing and its application areas. Mutation testing has been applied at both the source code level and specification level of the software under test. Mutation testing, when applied to the source code, is named as Program Mutation. Similarly, when applied to the specifications, it is named as Specification Mutation. The relevant Mutation Testing tools available for different programming languages for both program and Specification Mutations are hereby listed. Owing to the high cost incurred in applying Mutation Testing to industrial needs, the on-going endeavors of the researchers in the area are elaborated here. Applying nature-inspired algorithms along with Mutation Testing for data generation/selection/minimization is an upcoming area of research. Search based Mutation Testing (SBMT) applies evolutionary techniques like Genetic Algorithms or other metaheuristic approaches for automating the tasks associated with mutation testing, which otherwise requires a lot of human effort, thus, making it a practical approach. This chapter concludes by giving the seminal recent advancements in the area.

Keywords: Generation/Selection/Minimization of test data, Metaheuristics, Mutation Testing, Nature–Inspired Algorithms.