This does not present a good understanding of how to test machine learning models. If you let the "labels" be visible at test time, your test is worthless. Your analogy of "real world software development" doesn't hold up. In real world software development, I don't have magical commits from the future, that I merely need to check out and look at to see the solution.

This was never in question and an actual developer has already answered in another comment why this is not as big of an issue as the title might suggest. The question in this chain was about the value of additional data, which is perfectly clear if you're familiar with this particular benchmark.