Semantic Data Augmentation for Deep Learning Testing using Generative AI

Missaoui, Sondess and Gerasimou, Simos (2023) Semantic Data Augmentation for Deep Learning Testing using Generative AI. In: 38th IEEE/ACM International Conference on Automated Software Engineering:Proceedings. the 38th IEEE/ACM International Conference on Automated Software Engineering, 11-15 Sep 2023 IEEE , LUX

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
  • Missaoui, Sondess (sm2672@york.ac.uk)
  • Gerasimou, Simos (simos.gerasimou@york.ac.uk)
Copyright, Publisher and Additional Information:

This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.

Keywords: Generative AI, Deep Learning Testing, Coverage Guided Fuzzing, Data Augmentation, Safe AI
Dates:
  • Published: 15 September 2023
  • Accepted: 18 August 2023
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Computer Science (York)
Depositing User: Pure (York)
Date Deposited: 23 Aug 2023 10:40
Last Modified: 10 Jan 2025 00:12
Status: Published
Publisher: IEEE
Open Archives Initiative ID (OAI ID):

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Filename: ase23_nier_134.pdf

Description: ase23-nier-134

Licence: CC-BY 2.5

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