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Ten simple rules for documenting scientific software · Study

WorkTen simple rules for documenting scientific software

Benjamin D. Lee2018

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Workgold2018

Ten simple rules for documenting scientific software

Benjamin D. Lee

60 citations·0/0 files stored·PLoS Computational Biology

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Scientific Computing and Data Management Research Data Management Practices Software Engineering Techniques and Practices

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References

2014Best Practices for Scientific Computing 2016Ten Simple Rules for Taking Advantage of Git and GitHub 2016A Quick Introduction to Version Control with Git and GitHub 2012Ten Simple Rules for the Open Development of Scientific Software 2009A Quick Guide to Organizing Computational Biology Projects 2017Ten Simple Rules for Developing Usable Software in Computational Biology

Cited by

2021An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action 2021Ten simple rules on writing clean and reliable open-source scientific software 2020An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action 2020Can reproducibility be improved in clinical natural language processing? A study of 7 clinical NLP suites 2021Dealing with software complexity in individual‐based models 2022A call for clean code to effectively communicate science 2019Bionitio: demonstrating and facilitating best practices for bioinformatics command-line software

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Details

Year2018

Typeeditorial

Published2018-12-20

VenuePLoS Computational Biology

ISSN-L1553-734X

Languageen

Citations60

Files0 public / 0

ShelfScientific Computing and Data Management

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doi10.1371/journal.pcbi.1006561

openalex_workW2903593834

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2022Ten simple rules for making a software tool workflow-ready