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Best Practices for Scientific Computing

Research output: Contribution to journalArticle

  • Greg Wilson
  • D. A. Aruliah
  • C. Titus Brown
  • Neil P. Chue Hong
  • Matt Davis
  • Richard T. Guy
  • Steven H D Haddock
  • Kathryn D. Huff
  • Ian M. Mitchell
  • Mark D. Plumbley
  • Ben Waugh
  • Ethan P. White
  • Paul Wilson

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    Rights statement: Copyright: © 2014 Wilson et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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    Licence: Creative Commons: Attribution (CC-BY)

Original languageEnglish
Article numbere1001745
Number of pages7
JournalPLoS Biology
Issue number1
Publication statusPublished - 7 Jan 2014


Scientists spend an increasing amount of time building and using software. However, most scientists are never taught how to do this efficiently. As a result, many are unaware of tools and practices that would allow them to write more reliable and maintainable code with less effort. We describe a set of best practices for scientific software development that have solid foundations in research and experience, and that improve scientists' productivity and the reliability of their software.

    Research areas

  • Computer software, Computers, Language, Open source software, Research validity, Scientists, Software development, Software tools

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