Automated Model-in-the-Loop Testing of Continuous Controllers using Search

The number and the complexity of software components embedded in
today’s vehicles is rapidly increasing. A large group of these components monitor
and control the operating conditions of physical devices (e.g., components
controlling engines, brakes, and airbags). These controllers are known as continuous
controllers. In this paper, we study testing of continuous controllers at the
Model-in-Loop (MiL) level where both the controller and the environment are
represented by models and connected in a closed feedback loop system.We identify
a set of common requirements characterizing the desired behavior of continuous
controllers, and develop a search-based technique to automatically generate
test cases for these requirements. We evaluated our approach by applying it to a
real automotive air compressor module. Our experience shows that our approach
automatically generates several test cases for which the MiL level simulations
indicate potential violations of the system requirements. Further, not only do our
approach generates better test cases faster than random test case generation, but
we also achieve better results than test scenarios devised by domain experts.