Improving evolutionary real-time testing by seeding structural test data

Timing constraints in embedded systems must be satisfied so that real-time embedded systems work properly and safely. Execution time testing involves finding the best and worst case execution times. Evolutionary testing is used to dynamically search for the extreme execution times. During the evolutionary search, some parts of the source code are never accessed. Moreover, it turns out that the search delivers different extreme execution times in a high number of generations. We propose a new approach which makes use of seeding the evolutionary algorithm with test data achieved a high structural coverage. This new method leads to raise the confidence in the results and to gain in efficiency in terms of number of generations needed.