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Challenge to scientists: does your ten-year-old code still run?

From Nature Careers

Thanks to Clément H for sharing their work on Unsplash.

What Nicolas Rougier needed was a disk. Not a pocket-sized terabyte hard drive, not a compact disc — an actual floppy disk.

For those who missed the 1980s, the original floppy disk was a flexible, flimsy disk inside a square sleeve with a hole in the centre and a notch in the corner, and a couple of hundred kilobytes of storage. In the 1983 cold-war film War Games, high-school hacker David Lightman uses one to break into the school’s computer and give his girlfriend top marks in biology; he later hacks into a military network, narrowly averting a global thermonuclear war. Rougier’s need was more prosaic. He just wanted to transfer a text file from his desktop Mac to a relic of the computational palaeolithic: a vintage Apple II, the company’s first consumer product, introduced in 1977.

Rougier is a computational neuroscientist and programmer at INRIA, the French National Institute for Research in Digital Science and Technology in Bordeaux. That file transfer marked the final stage of his picking up a computational gauntlet he himself threw down: the Ten Years Reproducibility Challenge. Conceived in 2019 together with Konrad Hinsen, a theoretical biophysicist at the French National Centre for Scientific Research (CNRS) in Orléans, the challenge dares scientists to find and re-execute old code, to reproduce computationally driven papers they had published ten or more years earlier. Participants were supposed to discuss what they learnt at a workshop in Bordeaux in June, but COVID-19 scuppered those plans. (The event has been tentatively rescheduled for June 2021.)

Although computation plays a key and ever-larger part in science, scientific articles rarely include their underlying code, Rougier says. Even when they do, it can be difficult for others to execute it, and even the original authors might encounter problems some time later. Programming languages evolve, as do the computing environments in which they run, and code that works flawlessly one day can fail the next.


Read the article in full on the Nature Careers Blog – https://www.nature.com/articles/d41586-020-02462-7

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