Similar thing sometimes happens in deep learning field. Just a couple of weeks ago I helped a coworker reproduce a result from a paper. He had been debugging it for several days. Took me about 5 minutes to make a correct guess that his batch size is too small for batchnorm to be effective. He trained the model on 8 GPUs, using a decent batch size, but he didn't realize that the default batchnorm op in Pytorch isn't synchronizing batch statistics across GPUs, so the effective batch size was in fact 8x smaller. How was I able to see it so quickly? Experience.