Challenges of Software Engineering in Computational Biology and Bioinformatics Scientific Software Projects

Abstract

Computational biology scientific software projects are continuously growing and the volume and the task of analyzing, designing, implementing, testing, and maintaining these projects to ensure high-quality software products are only getting harder and more complicated. Conventional software development methodologies are not sufficient in ensuring that scientific software is error-free or up to the standard or comparable to the software designed in the industry. For this reason, it is important to investigate projects that utilized the best software engineering practices during their development and find and understand the problems that arise during the development of those projects. Such understanding will serve as the first step in the process of developing high-quality software products and will enable us to design and propose solutions to the problems that commonly occur during the development of such projects. In this paper, we will discuss different studies that applied software engineering practices and approaches in their computational biology projects. The challenges they encountered and the benefits they gained from employing software engineering quality assurance and testing techniques. In addition, we will demonstrate some of our own experiences when designing, developing, and testing computational biology projects within academic settings. We will also present, based on our experience, some solutions, methodologies, and practices that when adopted will benefit the scientific computational biology software community throughout the process of designing and testing the software.