![]() The lack of robustness in published, distributed software leads to duplicated efforts with little practical benefit, which slows the pace of research. The root cause of this problem is that most research software is essentially a prototype, and therefore is not robust. The potential new user is then faced with two unpalatable options: hack the existing code to make it work or start over.īeing unable to replicate results is so common that one publication refers to it as “a rite of passage”. It may produce the intended results in their hands, but what happens when someone else wants to run it? Everyone with a few years of experience feels a bit nervous when told to use another person’s code to analyze their data: it will often be undocumented, work in unexpected ways (if it works at all), rely on nonexistent paths or resources, be tuned for a single dataset, or simply be an older version than was used in published papers. Scientific software is typically developed and used by a single person, usually a graduate student or postdoc. ![]()
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