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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.
How should courses be designed and pitched to appeal to their target audience whilst effectively teaching the skills they may not be aware of or think that they need (but experience tells us benefit learners in the long-term)? Furthermore after a course, what should be the next steps to support the uptake of those skills?
By Frances Cooper (editor), Aleks Nenadic, Anna-Maria Sichani, Yasemin Turkyilmaz, Pablo Bernabeu and Steve Crouch
Photo by Evan Dennis on Unsplash
By Steve Crouch
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The Software Sustainability Institute has launched a new evaluation service to ensure your research software is as good as it can be.