Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (22): 53-67.DOI: 10.3778/j.issn.1002-8331.2106-0342

• Research Hotspots and Reviews • Previous Articles     Next Articles

Survey of Research on Neural Network Verification and Testing Technology

LI Duo, DONG Chaoqun, SI Pinchao, HE Man, LIU Qianchao   

  1. 1.PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China
    2.Software Testing and Evaluation Center, Jiangnan Institute of Computing Technology, Wuxi, Jiangsu 214083, China
  • Online:2021-11-15 Published:2021-11-16



  1. 1.战略支援部队信息工程大学,郑州 450001
    2.江南计算技术研究所 软件测评中心,江苏 无锡 214083


Neural network technology has made remarkable achievements in the fields of image processing, text analysis and speech recognition. With the application of neural network technology to some security related fields, how to ensure the quality of these software applications is particularly important. Software based on neural network technology is essentially different from traditional software in development and programming. Traditional testing technology is difficult to be directly applied to this kind of software. It is necessary to study the verification and testing evaluation technology for neural network. To effectively evaluate and test neural networks, this paper reviews the research status of neural network verification and testing technology, summarizes and classifies the verification technology, testing technology based on coverage, testing technology based on adversarial sample, and fusing traditional testing technology. The basic idea and implementation of some key technologies are briefly introduced, and some testing frameworks and tools are listed. The challenges of neural network verification and testing are summarized, which can provide reference for researchers in this field.

Key words: neural networks, test evaluation, verification technology, testing technology



关键词: 神经网络, 测试评估, 验证技术, 测试技术