The Better Scientific Software (BSSw) Tutorial

The BSSw tutorial focuses on issues of developer productivity, software sustainability, and reproducibility in scientific research software, particularly targeting high-performance computers. In selecting topics for our tutorials, we try to emphasize topics for which few other training resources are available which speak to the particular experiences of developers of scientific software.

We first presented a version of this tutorial in 2016, and since then we have been working continually to refine and expand it. We present it most often as part of conferences, but we are open to a wide range of venues, both in person (circumstances permitting) and online. Contact us for more information.

In the listings below, each tutorial event has its own page, providing details specific to that tutorial, including the agenda, presentations, hands-on activities, and other resources. Quick links are also provided to key tutorial artifacts, where available.

Stability and persistence

We consider the individual tutorial web pages to be archival. Once a tutorial is over, we minimize further changes, though we will update pages if we find significant issues in the tutorial materials, or when we get additional artifacts (e.g., recordings are rarely available immediately). We also periodically check the URLs in the ‚ÄúResources from Presentations‚ÄĚ sections of the pages and will attempt to provide alternative resources for links that are no longer available (we do not update the presentation slides). This site is hosted on GitHub Pages. Presentations are generally archived on FigShare, and recordings on YouTube. We rely on these high-profile sites to provide a reasonable degree of persistence for the tutorial resources.

Scheduled Tutorials

We do not currently have any tutorials scheduled. Check back periodically for updates. Also, some of our past tutorials have recordings available.

Past Tutorials

Acknowledgements

The BSSw tutorial is produced by the IDEAS Productivity project.

This work was supported by the U.S. Department of Energy Office of Science, Office of Advanced Scientific Computing Research (ASCR), and by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration.

Built 2023-11-13 from commit 213d88f