Optimizing Test Input Generation for Reactive Systems with an Adaptive Differential Evolution

The development of search-based algorithms forautomatic test case generation is a key issue in the researcharea of software testing. Evolutionary algorithms have beenfrequently used for this purpose due to their ability to solvecomplex optimization problems. In this paper we introduce anovel approach to the automatic test-case generation problemfor reactive software systems. We build upon our previouswork where we defined a test generation framework based onparameterized executable environment models written in theLutin language. The main contribution of this paper is theapplication of a self-adaptive evolutionary algorithm, JADE inthe context of our test generation framework and the evaluationof its performance on a realistic reactive system written in Scade. Our preliminary results show that adaptive differential evolutioncan be used efficiently to increase the structural coverage of thesystem under test and is easier to use due to the fewer parametersthat require fine-tuning.