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Best Practices for Scientific Computing

Authors: Wilson, G; Aruliah, DA; Brown, CT; Hong, NPC; Davis, M; Guy, RT; Haddock, SHD; +6 Authors

Best Practices for Scientific Computing

Abstract

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.

18 pages

Countries
United Kingdom, United States
Keywords

Life Sciences & Biomedicine - Other Topics, FOS: Computer and information sciences, Biochemistry & Molecular Biology, Biomedical and clinical sciences, Biomedical Research, QH301-705.5, CODE, Veterinary and Food Sciences, BIOLOGY, WRITE, Medical and Health Sciences, Computing Methodologies, Computer Science - Software Engineering, veterinary and food sciences, Community Page, Humans, Software tools, Computer software, Research validity, Biology (General), Biology, Language, Agricultural, Science & Technology, Biomedical and Clinical Sciences, Agricultural and Veterinary Sciences, Computers, Software development, SOFTWARE-DEVELOPMENT, Biological Sciences, Open source software, 004, Software Engineering (cs.SE), Biological sciences, Scientists, Computer Science - Mathematical Software, Life Sciences & Biomedicine, BIOCHEMISTRY & MOLECULAR BIOLOGY, Mathematical Software (cs.MS), Software, Developmental Biology

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    486
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 0.1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 0.1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 0.1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
486
Top 0.1%
Top 0.1%
Top 0.1%
Green
gold