Empirical study on software and process quality in bioinformatics tools

Abstract

Software quality in computational tools impacts research output in a variety of scientific disciplines. Biology is one of these fields, especially for High Throughput Sequencing (HTS) data, such tools play an important role. This study therefore characterises the overall quality of a selection of tools which are frequently part of HTS pipelines, as well as analyses the maintainability and process quality of a selection of HTS alignment tools. Our findings highlight the most pressing issues, and point to software engineering best practices developed for the improvement of maintenance and process quality. To help future research, we share the tooling for the static code analysis with SonarCloud which we used to collect data on the maintainability of different alignment tools. The results of the analysis show that the maintainability level is generally high but trends towards increasing technical debt over time. We also observed that the development activities on alignment tools are generally driven by very few developers and are not utilising modern tooling to their advantage. Based on these observations, we recommend actions to improve both maintainability and process quality in open source alignment tools. Those actions include improvements in tooling like the use of linters as well as better documentation of architecture and features. We encourage developers to use these tools in order to ease future maintenance efforts, increase user experience, support reproducibility, and ultimately increase the quality of research through increasing the quality of research software tools.