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Ten recommendations for software engineering in research
Research in the context of data-driven science requires a backbone of well-written software, but scientific researchers are typically not trained at length in software engineering, the principles for creating better software products. To address this gap, in particular for young researchers new to p...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2014
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4326482/ https://www.ncbi.nlm.nih.gov/pubmed/25685331 http://dx.doi.org/10.1186/2047-217X-3-31 |
| Sumario: | Research in the context of data-driven science requires a backbone of well-written software, but scientific researchers are typically not trained at length in software engineering, the principles for creating better software products. To address this gap, in particular for young researchers new to programming, we give ten recommendations to ensure the usability, sustainability and practicality of research software. |
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