In the last write-up I covered common issues that can lead to false positives in your automated visual tests along with some workarounds for them.
While this was a good start, it was incomplete.
It provided enough information to add initial resiliency to your visual tests, but it glossed over other common scenarios that will cause false positives and create gaps in your test coverage. Not only that, the tactics I’ve demonstrated thus far won’t hold up when faced with these new scenarios. Read more…