Abstract

Extended finite state machine (EFSM) is currently one of the most widely used model in the field of software testing. EFSM model is an enhanced model based on finite state machine (FSM). Automated test data generation is still a challenging problem due to the complexity of EFSM which extends the input and output parameters, context variables as well as the predicate condition. These reasons lead to conflict of the context variable with the enable conditions in the transition path. In order to avoid infeasible path generation, this paper proposes a method based on modified breadth first search to generate feasible transition path (MBFS-FTP). To solve the problem of state explosion in path generation, this paper converts state diagram to transition diagram on EFSM model. In order to make the EFSM static model can be driven execution, this paper uses UML model and generate executable model, so that implements EFSM execute dynamically. When using breadth-first search algorithm (MBFS) on every target transition to generate an executable transition path, the conflict detection algorithm is utilized to the transition path for conflict decision, avoiding the occurrence of an infeasible transition path. Considering target transition has multiple feasible transition paths, this paper combines suggested penalized value of definition-predicate-use (def-p-use) pair and length of feasible transition path, and then develops the measurement method of feasible transition path, and obtained a set of feasible transition path containing all of transitions. Through the experiment on two actual EFSM model, verifying the effectiveness of MBFS-FTP for feasible transition automatic generation, the experimental results show that MBFS-FTP can reduce the feasible transition path length, and make transition paths are more easily to be triggered at the times of generating test cases lately, furthermore, it can improve the efficiency of generate feasible transition path and save a lot of time.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call