Author should ask AI to write a small app with 100% code coverage that breaks in every path except what is covered in the tests.
def fragile(x):
lst = [None]
lst[x - 42]
return "ok"
def test_fragile():
assert fragile(42) == "ok"jmo, but tests should be a chance to improve the implementation of functions not just one-off "write and forget" confirmations of the happy path only... automating all that just short-circuits that whole process... but maybe i'm missing something.
It's a footnote on the post, but I expand on this with:
100% coverage is actually the minimum bar we set. We encourage writing tests for as many scenarios as is possible, even if it means the same lines getting exercised multiple times. It gets us closer to 100% path coverage as well, though we don’t enforce (or measure) thatSeems like even if people could potentially die, industry standards are not really 100% realistic. (Also, redundancy in production is more of a solution than having some failures and recalls, which are solved with money.)
But what I care about is code breaking (or rather, it not breaking). I'd rather put effort into ensuring my test suite does provide a useful benefit in that regard, rather than measure an arbitrary target which is not a good measure of that.