1. A method comprising, by one or more computer systems: receiving information associated with a first plurality of image pairs; assessing each image pair in the first plurality of image pairs to detect visual pairwise differences that qualify as an error, wherein a visual pairwise difference comprises a difference with respect to at least one of position, size, color, or style; training a prediction engine based upon the assessed visual pairwise differences; receiving information associated with a second plurality of image pairs, wherein each image pair in the second plurality of image pairs comprises at least a portion of a visual end-user experience screen of an event-driven application executed in a client-tier environment; assessing, using the prediction engine, each image pair in the second plurality of image pairs to detect visual pairwise differences that qualify as an error; receiving user feedback, for at least one image pair in the second plurality of image pairs that was assessed to have at least one pairwise difference qualifying as an error, that the assessed pairwise difference should not have qualified as an error; and re-training the prediction engine based on the user feedback.