Miranda Mundt

Miranda Mundt, Reed Milewicz

Within the rapidly diversifying field of computational science and engineering (CSE), research software engineers (RSEs) represent a shift towards the adoption of mainstream software engineering tools and practices into scientific software development. An unresolved challenge is the need to effectively integrate RSEs and their expertise into multi-disciplinary scientific software teams. There has been a long-standing "chasm" between the domains of CSE and software engineering, and the emergence of RSEs as a professional identity within CSE presents an opportunity to finally bridge that divide. For this reason, we argue there is an urgent need for systematic investigation into multi-disciplinary teaming strategies which could promote a more productive relationship between the two fields.

Reed Milewicz, Miranda Mundt

There has been growing interest within the computational science and engineering (CSE) community in engaging with software engineering research -- the systematic study of software systems and their development, operation, and maintenance -- to solve challenges in scientific software development. Historically, there has been little interaction between scientific computing and the field, which has held back progress. With the ranks of scientific software teams expanding to include software engineering researchers and practitioners, we can work to build bridges to software science and reap the rewards of evidence-based practice in software development.

Reed Milewicz, Miranda Mundt

As a newly designated professional title, research software engineers (RSEs) link the two worlds of software engineering and research science. They lack clear development and training opportunities, particularly in the realm of mentoring. In this paper, we discuss mentorship as it pertains to the unique needs of RSEs and propose ways in which organizations and institutions can support mentor/mentee relationships for RSEs

Miranda Mundt, Evan Harvey

We are research software engineers and team members in the Department of Software Engineering and Research at Sandia National Laboratories, an organization which aims to advance software engineering in the domain of computational science. Our team hopes to promote processes and principles that lead to quality, rigor, correctness, and repeatability in the implementation of algorithms and applications in scientific software for high consequence applications. We use our experience to argue that there is a readily achievable set of software tools and best practices with a large return on investment that can be imparted upon scientific researchers that will remarkably improve the quality of software and, as a result, the quality of research.