Patterns to Improve Fidelity for Model-Based Testing

Abstract

Model-based Testing (MBT), is an important testing technology to generate test cases automatically by MBT tools. While a single MBT tool supports a single MBT model, it is necessary to integrate implicitly multiple models to detect failures manually such as exploratory testing in industry. A single-model-MBT lacks fidelity which means the ability to generate the required test cases. In this research, we analyse such failures to identify implicit multiple models. Several patterns on integration of multiple models are discovered. This paper introduces the patterns and examples of test case generation to improve fidelity.