Unit Testing, Model Validation, and Biological Simulation
This work addresses improving research quality and reliability in computational biology, but it is incremental as it applies existing software practices to a new domain.
The paper examines how software reliability practices like unit testing and test-driven development can improve biological software development, using a case study of the OpenWorm project to model Caenorhabditis elegans, and discusses challenges such as incorporating these methods into data-driven projects and the role of model validation tests.
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.