Evolutionary functional testing of continuous control systems
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Search-based test data generation from stateflow statecharts
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Transition coverage testing for simulink/stateflow models using messy genetic algorithms
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Evolutionary functional black-box testing in an industrial setting
Software Quality Control
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Test case generation constitutes a critical activity in software testing that is cost-intensive, time-consuming and error-prone when done manually. Hence, an automation of this process is required. One automation approach is search-based testing for which the task of generating test data is transformed into an optimization problem which is solved using metaheuristic search techniques. However, only little work has been done so far applying search-based testing techniques to systems that depend on continuous input signals.This paper proposes two novel approaches to generating input signals from within search-based testing techniques for continuous systems. These approaches are then shown to be very effective when experimentally applied to the problem of approximating a set of realistic signals.