Using Genetic Algorithms To Select Test Cases For Finite State Machines With Timeouts

Testing software is an expensive and time consuming task. This drawback increases in the case that the system presents timeouts which affect the functional behaviour. In this case, it is necessary to invest more time to apply the test cases. Thus, it is desirable to diminish the amount of test cases to be applied and, consequently, the time devoted to test the system, as long as the fault detection capacity of the test cases is not affected. In this work, we introduce a genetic algorithm that selects a subset of test cases from an initial test suite for systems that present timeouts, with the goal of keeping a good level of effectiveness. We report on several experiments performed to compare the generated solutions with random selection and the original test suite.