Data augmentation in test/validation set?

Question

It is common practice to augment data (add samples programmatically, such as random crops, etc. in the case of a dataset consisting of images) on both training and test set, or

Answer 1

The goal of data augmentation is to generalize the model and make it learn more orientation of the images, such that the during testing the model is able to apprehend the test data well. So, it is well practiced to use augmentation technique only for training sets.