Wasserstein generative adversarial networks for online test generation for cyber physical systems

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10 Citeringar (Scopus)

Sammanfattning

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.
OriginalspråkEngelska
Titel på värdpublikationThe 15th Search-Based Software Testing Workshop SBST 2022
FörlagIEEE
Sidor1-5
ISBN (tryckt)978-1-4503-9318-8
DOI
StatusPublicerad - 2022
MoE-publikationstypA4 Artikel i en konferenspublikation
EvenemangInternational Workshop on Search-Based Software Testing -
Varaktighet: 9 maj 2022 → …

Konferens

KonferensInternational Workshop on Search-Based Software Testing
Förkortad titelSBST
Period09/05/22 → …

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