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Wasserstein Generative Adversarial Networks for Online Test Generation for Cyber Physical Systems (2205.11060v1)

Published 23 May 2022 in cs.LG and cs.SE

Abstract: 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.

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