Anyways, in physics they always require several experimental proves for our theory. They also have several "software experiments" for e.g. predicting the same observables. Therefore, researchers need to be able to compile and run the code of their competitors in order to compare and verify the results in detail. In this place, bug-hunting/fixing is sometimes also taking place - of course. So applying the articles suggestions would have the potential to accelerate scientific collaboration.
btw; I know some people who do still work with the data taken at the LEP experiment which was shut down almost 20 (!) years ago and they have a hard time in combining old detector-simulations, monte-carlos etc. with new data-analysis techniques for the exact same reasons mentioned in the article. For large-scale experiments it is a serious problem which nowadays has much more attention than at LEP ages, since LHC has anyways obvious big-data problems to solve before their next upgrade, including also software-solutions.
I suspect that software really is different in this way, and treating it like it's complex, one off hardware is cultural inertia that's going to fade away.
I doubt any physicist believes we need to get the Tevatron running again just to check decade-old measurements of the top quark. I don't understand why decade-old scientific software code must meet that bar.