Best Practices for Scientific Software Development
Author Information
Author(s): Susan M. Baxter, Steven W. Day, Jacquelyn S. Fetrow, Stephanie J. Reisinger
Primary Institution: National Center for Genome Resources
Hypothesis
Scientific software development can benefit from established best practices to improve efficiency and reproducibility.
Conclusion
Following best practices in scientific software development can enhance project efficiency and the usability of computational biology work.
Supporting Evidence
- Many scientists spend too much time on software instead of research.
- Good software practices can lead to reproducible results.
- Documenting software is as important as documenting scientific experiments.
- Quality control processes are essential for reliable software.
- Using data standards helps in sharing and integrating scientific data.
Takeaway
Scientists often struggle with software because they aren't taught how to write it well, but using some simple guidelines can help them make better software.
Methodology
The authors propose a set of best practices for scientific software development based on their experiences and literature review.
Limitations
The guidelines may not cover all aspects of software development and may not apply universally to all projects.
Digital Object Identifier (DOI)
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