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arXiv · 1912.04900

Datamorphic Testing: A Methodology for Testing AI Applications

Hong Zhu·Dongmei Liu·Ian Bayley·Rachel Harrison·Fabio Cuzzolin
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Abstract

With the rapid growth of the applications of machine learning (ML) and other artificial intelligence (AI) techniques, adequate testing has become a necessity to ensure their quality. This paper identifies the characteristics of AI applications that distinguish them from traditional software, and analyses the main difficulties in applying existing testing methods. Based on this analysis, we propose a new method called datamorphic testing and illustrate the method with an example of testing face recognition applications. We also report an experiment with four real industrial application systems of face recognition to validate the proposed approach.

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Hong Zhu, Dongmei Liu, Ian Bayley, Rachel Harrison, Fabio Cuzzolin. 2019-12-10. Datamorphic Testing: A Methodology for Testing AI Applications. https://arxiv.org/abs/1912.04900

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