Prospects and challenges in R package development |
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| Authors: | Stefan Theu?l Uwe Ligges Kurt Hornik |
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| Institution: | (1) Department of Biostatistical Science, Dana-Farber Cancer Institute, 44 Binney St, 02115 Boston, MA, USA;(2) Channing Laboratory, Brigham and Women's Hospital, 75 Francis Street, 02115 Boston, MA, USA;(3) Department of Statistics, University of Wisconsin-Madison, 1210 W Dayton St, 53706 Madison, WI, USA;(4) Division of Biostatistics, University of California, Berkeley, 140 Warren Hall, 94720-7360 Berkeley, CA, USA;(5) Seminar for Statistics LEO C16, ETH Zentrum, CH-8092 Z?rich, Switzerl;(6) Department of Statistics, Harvard University, 1 Oxford St, 02138 Cambridge, MA, USA;(7) Center for Biological Sequence Analysis, Technical University of Denmark, Building 208, 2800 Lyngby, Denmark;(8) Department of Biomathematical Sciences, Mount Sinai School of Medicine, 1 Gustave Levy Place, Box 1023, 10029 New York, NY, USA;(9) Institut f?r Statistik und Wahrscheinlichkeitstheorie, TU Wien, Wiedner Hauptstrasse 8-10/1071, 1040 Wien, Austria;(10) Biometrie und Epidemiologie, Institut f?r Medizininformatik, Friedrich-Alexander-Universit?t Erlangen-N?rnberg, Waldstra?e6, D-91054 Erlangen, Germany;(11) Division of Molecular Genome Analysis, DKFZ (German Cancer Research Center), 69120 Heidelberg, Germany;(12) Department of Economics, University of Milan, 23 Via Mercalli, I-20123 Milan, Italy;(13) Department of Biostatistics, Johns Hopkins University, 615 N Wolfe St E3035, 21205 Baltimore, MD, USA;(14) Department of Medical Education and Biomedical Informatics, University of Washington, 1959 NE Pacific, Box 357240, 98195 Seattle, WA, USA;(15) Statistisches Labor, Institut f?r Angewandte Mathematik, Im Neuenheimer Feld 294, D 69120 Heidelberg, Germany;(16) Department of Molecular Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, TPC-28, 92037 La Jolla, CA, USA;(17) Division of Genetics and Bioinformatics, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, 3050 Parkville, Victoria, Australia;(18) Department of Statistics and Actuarial Science, University of Iowa, 241 Schaeffer Hall, 52242 Iowa City, IA, USA;(19) Center for Bioinformatics and Molecular Biostatistics, Univerisity of California, San Francisco, 500 Parnassus Ave, 94143-0560 San Francisco, USA |
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| 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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