Whether for research, administration, learning or teaching, software is an increasingly valuable research tool and output, and needs to be managed as such.
This guide is for researchers who program and anyone who is starting a software-development project. It will help you to understand the sustainability and preservation requirements of your software, the outputs from the development process and how to plan and undertake a software project.
Are about to lose an important developer? This paper provides guidance on how to perform a technical handover. This will ensure that your soon-to-leave developer will impart his or her valuable technical knowledge, and it will help you avoid the common traps and pitfalls that their departure can cause.
It is important to perform a technical handover as early as possible - don’t underestimate the time it will take. The transfer of software technical knowledge is a timeconsuming and complex task, so plan ahead, decide what’s important, schedule regular meetings and slowly get your remaining developers to take over the leaving developer’s tasks.
Assessing the quality of software - either your own or someone else's - is a tricky balance between hard objectivity and the very subjective (but very valid) individual user experience. The Software Sustainability Institute provide a software evaluation service based on two complementary approaches developed over many years in the research software arena. The service can help you to improve your software. It can assess the general usability, and can identify technical or development issues, as well as any barriers to sustainability
By Steve Crouch, SSI Research Software Group lead.
This guide is the first in the Unit Testing for Scale and Profit series.
In a project where changes are frequently made to research software, it is helpful to know that the code still works as expected. In our last two episodes, we looked at the benefits of having a set of unit tests and how we can use test parameterisation to write numerous tests efficiently. However, particularly with projects involving more than one contributor, it would be good to have assurance the software still works without everyone having to pull down all the changes and test them. In this guide, we'll be looking at Continuous Integration, which aims to reduce this burden by automating things in the background, such as running tests. But it also can be used for so much more.
By Steve Crouch, SSI Research Software Group Lead.
This guide is part of the series of resources on learning to code, hosted as part of the Research Software Camp: Beyond the Spreadsheet.
Myths about computing and coding are everywhere. You only have to look at movies for many examples – films like Hackers (1995), The Net (1995) and Swordfish (2001) immediately spring to mind – with the often genius-level protagonists able to weave techno-spells with their fingers to accomplish amazing feats of coding and/or hacking prowess in a bewildering, complex dance of graphical beauty. Fortunately, although somewhat less impressively, the truth of coding is far more straightforward than that, and this guide is aimed at researchers that haven't yet started to code. Here we call out some of the myths surrounding learning it as a skill you can apply in your research, and anywhere else really.
Demonstrating that a process generates the right results is important in any field of research, whether it’s research software generating those results or not. Automation, where possible, enables us to define a potentially complex process in a repeatable way that is quicker and far less prone to error than doing it manually. 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.
Over the last couple of years delivering presentations online has become par for the course, with Covid-19 forcing many people to work from home and events to be delivered remotely. With our work culture changing, online presentations look set to stay, so here are our top tips to help you deliver a strong recording.
This guide is part of the Research Software Camp: research accessibility web content series.
Even before the pandemic-driven age of remote meetings, many open science and open source communities have been using participatory online meeting formats to involve their members from multiple countries. Local communities are also successful at designing inclusive formats that take languages, cultures, and identities into account. Many international initiatives host online training and community meetings using traditional information delivery methods: training workshops, guest presentations, as well as participatory methods: group discussions, collaborative document writing, and online co-working. On one hand, these meetings aim to be inclusive of members from different time zones, languages and identities together in a common place. On the other hand, formats used in these calls presume that participants of such calls actively use spoken language, have shared vocabulary, and learn in similar ways.
New materials are now available to introduce beginners to Github and Application Programming Interfaces (APIs). The materials were developed for Open Data Manchester’s Pick N Mix series – free online sessions which enable people to improve their data skills.
