Improving Testing of Deep-Learning Systems.

The article focuses on the improvement of test effectiveness and quality of test data in deep learning systems. Topics of discussion include the combination of mutation testing using DeepMutation and differential testing using DeepXplore, iterations of models using data from the MNIST database, and the discovery of errors in deep neural network (DNN) models.