%0 Journal Article %A LIU Jialuo %A YAO Yi %A HUANG Song %A HUI Zhanwei %A CHEN Qiang %A KOU Dalei %A ZHANG Zhongwei %T Metamorphic Testing Framework for Machine Learning Image Classification Program %D 2020 %R 10.3778/j.issn.1002-8331.1906-0242 %J Computer Engineering and Applications %P 69-77 %V 56 %N 17 %X

Machine learning has achieved remarkable success in practical applications such as computer vision, speech recognition, and natural language processing. Image classification is a major branch of computer vision. In the near future, many image classification programs will be presented in machine learning. However, since the testing of machine learning image classification programs faces test oracle problems, it will require a lot of manpower and material resources in the testing process. In this paper, in order to alleviate the testing oracle problem, it uses the Metamorphic Testing(MT) technology. At the same time, in order to standardize the testing process and improve the testing efficiency, a metamorphic testing framework suitable for machine learning image classification program is proposed. Through testing SVM and VGGNet image classification programs, the rationality and effectiveness of the testing framework are verified.

%U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1906-0242