Bloodsuckers, banshees and brains: a bestiary of scary software projects and how to banish them

Neil Chue Hong & Benjamin Cowan • October 31, 2019

With All Hallows Eve upon us once more, as the souls of the dead come to haunt us, it’s time to recount terrifying tales and scary stories… about software. You might think that research software is safe from such gruesome goings-on but you would be wrong, for there are many undead projects out to devour us. Here’s how to recognise some of these spooky software, along with other pestilent projects, and dispatch them back whence they came.

Open Sourcing Your Software is Not a Sustainability Strategy – Until it Is!

David E. Bernholdt • October 2, 2019

When asked how they plan to sustain their software, many (naïve) software developers will say that they plan to make it open source. And that’s often their whole plan. There is an assumption that the mere act of exposing the software to the public will create a community who are able and willing to contribute to the support, maintenance, and perhaps the enhancement of the software product. Those who have more experience observing how open source software works will realize that it is very rare for a project to reap significant benefits from the broader community.

Research Software Science: A Scientific Approach to Understanding and Improving How We Develop and Use Software for Research

Michael A. Heroux • September 25, 2019

Development and use of software are fundamental to numerous areas of scientific research. Many scientists write, modify, and use software to gain insight and prove scientific results. At the same time, formal software engineering techniques and knowledge that are widely adopted in other software development domains are not as commonly used in research software projects. In my experience, research software development approaches are more informal, particularly in the upstream activities of requirements, analysis, and design.

Data-driven Software Sustainability

Daniel S. Katz • September 18, 2019

This blog post suggests an expression that can be used to loosely quantify software sustainability, and then proposes that projects that seek sustainability use this formula when making decisions. It’s heavily based on a a white paper for the 2019 Collegeville Workshop on Sustainable Scientific Software (CW3S19), which in turn is based on a previous blog post, and it is crossposted on the BSSw and URSSI blogs, as well as my own blog.

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