Basic Operations for Generating Behavioral Mutants

This paper attempts to subsume the existing great variety of mutation operations to two basic operations, insertion and omission and their combinations. These basic operations are applied to different elements of graph-based models of increasing representation power. A case study applies the approach to these models for generating mutants of different features and compares the fault detection capacity of the mutants generated.