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

Data augmentation is done only on training set as it helps the model become more generalize and robust. So there's no point of augmenting the test set.