Strategic Usage of Test Case Generation by Combining Two Test Case Generation Approaches

Model-based testing is used as a cost-effective development approach especially for embedded systems in the automotive sector. In this work, we focus on two kinds of test case generation and compare two methods. Each method has different criteria for generating test cases: One is based on the theory of Markov chains and the other one is a combination of functions to get test cases for unexpected failure. We compared two sets of test cases from the two test case generation methods and show that combining the two methods makes model-based testing more cost-effective in the context of critical embedded systems. The work presented in this paper is work in progress.