My understanding is that it has been manually tested. I.e. it has produced correct results to previously intractable problems. I'm not sure how much automated testing would add at that point.
And, given the external results of the application, it's unclear to me how much additional value would come from a rigorous testing system.
Care to expand on what you're trying to do?
In a sense, I see software testing/big web data and modern large scale data processing in science as a continuum and I want to bring the practices from the big web data and testing fields to bear on science pipelines.