Research Software Group

Code review is known to be an effective way to improve software quality, foster peer learning and develop common ownership of a research software project. In practice, a code review is nothing else than a conversation between the author of the code and somebody else providing feedback on coding practices, readability or other aspects of code quality. If this sounds straightforward, an effective code review routine can be tricky to establish. Here are five tips for you to get started with code reviews, or get more of them.
It's 10 years since the term Research Software Engineer was coined at the Collaborations Workshop 2012 and the RSE movement began! 
This guide is the second in the Unit Testing for Scale and Profit series. As our code increases in size and particularly complexity, we should expect our number of tests to increase too, which means more time writing tests. Fortunately there is something that can help with this burden which we'll look at in this guide: parameterised tests!
Steve Crouch, SSI Research Software Group Lead, calls out some of the myths surrounding coding.
This guide is the first in the Unit Testing for Scale and Profit series. In this guide we’ll look into techniques of automated testing to improve the predictability of a software change, make development more productive, and help us produce code that works as expected and yields desired results. We'll use Python for illustration purposes, but the concepts and approaches can be readily applied to many other languages.
Miquel Duran-Frigola, Chief Scientific Officer and Co-Founder of the Ersilia Open Source Initiative, underwent the online evaluation offered by the Software Sustainability Institute.
A new initiative has been launched to help Research Software Engineers (RSEs) stay connected while many national RSE conferences have been cancelled due to COVID-19.
EPSRC will be inviting applications for outline proposals for Research Software Engineer Fellowships from 30 June.
On 28 May 2020, the RDA published the pre-final version of their COVID-19 Recommendations and Guidelines covering four research areas – clinical data, omics practices, epidemiology and social sciences. This document is also complemented by overarching areas focusing on legal and ethical considerations, research software, community participation and indigenous data.
By Alastair Downie, Head of IT at The Gurdon Institute, University of Cambridge This blog post was first published on the IT and Research Data Management in the Gurdon Institute blog.
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