"The result is what's important here, rather than the particular algorithm used to generate this instance of it."

Ah, the "computer modeler's" rallying cry. Something that has always worried me about performing "experiments" on computer models: software has bugs, and the investigators building and using them have preconceptions. The two interact to collectively bias results towards fitting the modelers' preconceptions: you fix bugs until the output "looks plausible" and fits some control data, and then stop.