Paper ID: 2205.11060

Wasserstein Generative Adversarial Networks for Online Test Generation for Cyber Physical Systems

Jarkko Peltomäki, Frankie Spencer, Ivan Porres

We propose a novel online test generation algorithm WOGAN based on Wasserstein Generative Adversarial Networks. WOGAN is a general-purpose black-box test generator applicable to any system under test having a fitness function for determining failing tests. As a proof of concept, we evaluate WOGAN by generating roads such that a lane assistance system of a car fails to stay on the designated lane. We find that our algorithm has a competitive performance respect to previously published algorithms.

Submitted: May 23, 2022