Software testing in microbial bioinformatics: a call to action

Author:

Mendes Inês1

Affiliation:

1. University of Lisbon

Abstract

Computational algorithms have become an essential component of microbiome research, with great efforts by the scientific community to raise standards on the development and distribution of code. Despite these efforts, sustainability and reproducibility are major issues since continued validation through software testing is still not a widely adopted practice. In the field of microbial bioinformatics, good software engineering practices are not yet widely adopted. Many microbial bioinformaticians start out as (micro)biologists and subsequently learn how to code. Without abundant formal training, a lot of education about good software engineering practices comes down to an exchange of information within the microbial bioinformatics community. Here, we report seven recommendations that help researchers implement software testing in microbial bioinformatics. These recommendations are: Establish software needs and testing goals; Use appropriate input test files; Use an easy-to-follow language format to implement testing; Try to automate testing; Test across multiple computational setups; and Encourage others to test your software. We propose collaborative software testing as an opportunity to continuously engage software users, developers, and students to unify scientific work across domains. As automated software testing remains underused in scientific software, our set of recommendations not only ensures appropriate effort can be invested into producing high quality and robust software but also increases engagement in its sustainability. We have developed these recommendations based on our experience from a collaborative hackathon organised prior to the American Society for Microbiology Next Generation Sequencing (ASM NGS) 2020 conference. We also present a repository hosting examples and guidelines for testing, available from https://github.com/microbinfie-hackathon2020/CSIS.Link to OA paper: https://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000790

Publisher

Cassyni

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