Industrial Evaluation of Search-Based Test Generation Techniques for Control Systems
Florian Hauer, Alexander Pretschner, Maximilian Schmitt, Markus Grötsch · 2017
The systems and the software in the domain of industrial trucks are becoming increasingly complex due to the rapidly increasing demand for more functionality. This leads to an even faster rising effort for manual verification activities. Therefore, automated testing techniques need to be introduced into the verification process. In this work, a search-based test generation technique has been adapted for the requirements-based black box test of control systems for counterweight forklift trucks. Fitness functions are derived from industrial requirement documents and are utilized to automatically generate test cases consisting of multiple input signals. The designed approach has been evaluated on an industrial control system and the results show that failures can be detected in the system as well as in the environment model.