Improving Software Engineering in Biostatistics: Challenges and Opportunities

TL;DR

This paper discusses the challenges faced in applying software engineering principles to biostatistics, emphasizing education, collaboration, and tools to improve reproducibility, code quality, and long-term maintenance.

Contribution

It highlights the importance of integrating software engineering practices into biostatistics and proposes strategies like education, dedicated teams, and community tools to address current challenges.

Findings

Software engineering practices can improve reproducibility and code quality in biostatistics.

Dedicated teams and education are key to adopting better software practices.

Community tools enhance transparency and collaboration.

Abstract

Programming is ubiquitous in applied biostatistics; adopting software engineering skills will help biostatisticians do a better job. To explain this, we start by highlighting key challenges for software development and application in biostatistics. Silos between different statistician roles, projects, departments, and organizations lead to the development of duplicate and suboptimal code. Building on top of open-source software requires critical appraisal and risk-based assessment of the used modules. Code that is written needs to be readable to ensure reliable software. The software needs to be easily understandable for the user, as well as developed within testing frameworks to ensure that long term maintenance of the software is feasible. Finally, the reproducibility of research results is hindered by manual analysis workflows and uncontrolled code development. We next describe how the awareness of the importance and application of good software engineering practices and strategies can help address these challenges. The foundation is a better education in basic software engineering skills in schools, universities, and during the work life. Dedicated software engineering teams within academic institutions and companies can be a key factor for the establishment of good software engineering practices and catalyze improvements across research projects. Providing attractive career paths is important for the retainment of talents. Readily available tools can improve the reproducibility of statistical analyses and their use can be exercised in community events. [...]