I've always wondered about building a test-sensitivity metric to complement coverage (and thus make coverage more useful): - Pick a random line of code (skip c

I've always wondered about building a test-sensitivity metric to complement coverage (and thus make coverage more useful): - Pick a random line of code (skip comments and whitespace if you can) - Delete/modify it in some way - Run the test suite and see if it passes Do this thousands of times on a codebase, then report on the test suite failure rate accross all of the random changes, broken down by file etc. You could track it all in a long running database and focus each test on lines which have recently changed to make it less expensive. I've never actually done this, but I'd guess that you could get a good sense of which files have good tests, and (combined with traditional coverage data) which files have bad tests vs just no tests.