Archiving Software Surrogates on the Web for Future Reference

Abstract

Software has long been established as an essential aspect of the scientific process in mathematics and other disciplines. However, reliably referencing software in scientific publications is still challenging for various reasons. A crucial factor is that software dynamics with temporal versions or states are difficult to capture over time. We propose to archive and reference surrogates instead, which can be found on the Web and reflect the actual software to a remarkable extent. Our study shows that about a half of the webpages of software are already archived with almost all of them including some kind of documentation.