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

• URL: http://arxiv.org/abs/2205.11060v1
• Date: Mon, 23 May 2022 05:58:28 GMT
• Title: Wasserstein Generative Adversarial Networks for Online Test Generation for Cyber Physical Systems
• Authors: Jarkko Peltom\"aki, Frankie Spencer, Ivan Porres
• Abstract summary: 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.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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