Abstract
R, a software package for statistical computing and graphics, has evolved into the lingua franca of (computational) statistics. One of the cornerstones of R’s success is the decentralized and modularized way of creating software using a multi-tiered development model: The R Development Core Team provides the “base system”, which delivers basic statistical functionality, and many other developers contribute code in the form of extensions in a standardized format via so-called packages. In order to be accessible by a broader audience, packages are made available via standardized source code repositories. To support such a loosely coupled development model, repositories should be able to verify that the provided packages meet certain formal quality criteria and “work”: both relative to the development of the base R system as well as with other packages (interoperability). However, established quality assurance systems and collaborative infrastructures typically face several challenges, some of which we will discuss in this paper.
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Theußl, S., Ligges, U. & Hornik, K. Prospects and challenges in R package development. Comput Stat 26, 395–404 (2011). https://doi.org/10.1007/s00180-010-0205-5
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DOI: https://doi.org/10.1007/s00180-010-0205-5