Using a genetic algorithm to generate test sequences based on an extended finite state machine

Question

I want to generate extended finite state machine (EFSM) test sequences using a genetic algorithm. EFSM-based trials face the challenge of a possible genetic algorithm path. My coverage criteria are transition coverage. I have an EFSM model of a system that has input parameters and protects against transitions from one state to another. Therefore, using this EFSM model, I want to generate test sequences. But I am confused about how to start. I mean how to generate an initial population. In fact, my research is about generating test cases based on EFSM. I have an ATM model. This model consists of states and transitions. Transitions have protection and actions for input parameters. Now I want to create test cases for this machine.I mean model-based testing. For this task, it is imperative that there is no possible way. I mean that each transition should be considered in a test scenario. Therefore, for this purpose I need to generate test sequences. The genetic algorithm is good for optimizing the path. but I don’t know how to use the specification of my model in a genetic algorithm and generate test sequences.

Answer 1

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