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

Only on training. Data augmentation is used to increase the size of training set and to get more different images. Technically, you could use data augmentation on test set to see how model behaves on such images, but usually people don't do it.