By James A. Whittaker

Let me be clear that these plague posts are specifically aimed at pointing out problems in testing. I'll get around to the lore and the solutions afterward. But keep up the debate in the comments, that's what this blog is all about.

The plague of repetitiveness

If aimlessness is the result of ‘just doing it’ then repetitiveness is the result of ‘just doing it some more.’ Pass after pass, build after build, sprint after sprint, version after version we test our product. Developers perform reviews, write unit tests and run static analyzers. But we have little insight into this effort and can't take credit for it. Developers test but then we retest. We can’t assume anything about what they did so we retest everything. As our product grows in features and bug fixes get applied, we continue our testing. It isn’t long until new tests become old tests and all of them eventually become stale.


This is Boris Beizer’s pesticide paradox. Pesticide will kill bugs, but spray the same field enough times with the same poison and the remaining bugs will grow immune. Rinse and repeat is a process for cleaning one’s hair, not testing software. The last thing we need is a build full of super-bugs that resist our ‘testicide.’ Even worse, all that so-called successful testing will give us a false sense of thoroughness and make our completeness metrics a pack of very dangerous lies. When you aren't finding bugs it's not because there are no bugs, it's the repetition that's creating the pesticide paradox.


Farmers know to adjust their pesticide formula from time to time and also to adjust the formula for the specific type of pest they expect in their fields. They do this because they understand the history of pesticide they used and know they can't get by with brute force repetition of they same old poison. Testers must pay attention to their test results too and watch for automation that isn’t adding value. A healthy injection of variation into automation is called for. Change the order of tests, change their data source, find new environments, modify input values do something the bugs aren’t prepared for.