Unit testing, model validation, and biological simulation

, , , , ,
1 School of Medicine, Emory University, Atlanta, Georgia, United States
2 OpenWorm.org, San Diego, California, United States
3 Department of Bioengineering, Imperial College London, London, United Kingdom
4 Department of Computer Science, University of Texas at Austin, Austin, Texas, United States
5 Laboratory of Systems Biology and Bioinformatics, University of Tehran, Tehran, Iran
6 School of Life Sciences, Arizona State University, Tempe, Arizona, United States
DOI
10.7287/peerj.preprints.1315v1
Published
Accepted
Subject Areas
Computational Biology, Neuroscience, Computational Science
Keywords
unit testing, biological simulation, scientific software, validation testing, test-driven development, model validation
Copyright
© 2015 Sarma et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
Cite this article
Sarma G, Jacobs TW, Watts MD, Ghayoomi V, Gerkin RC, Larson SD. 2015. Unit testing, model validation, and biological simulation. PeerJ PrePrints 3:e1315v1

Abstract

The growth of the software industry has gone hand in hand with the development of tools and cultural practices for ensuring the reliability of complex pieces of software. These tools and practices are now acknowledged to be essential to the management of modern software. As computational models and methods have become increasingly common in the biological sciences, it is important to examine how these practices can accelerate biological software development and improve research quality. In this article, we give a focused case study of our experience with the practices of unit testing and test-driven development in OpenWorm, an open-science project aimed at modeling Caenorhabditis elegans. We identify and discuss the challenges of incorporating test-driven development into a heterogeneous, data-driven project, as well as the role of model validation tests, a category of tests unique to software which expresses scientific models.

Author Comment

This manuscript will be submitted for publication in a peer-reviewed journal.