Building and Sustaining a Community Resource for Best Practices in Scientific Software: The Story of BSSw.io
The development of scientific software—a cornerstone of long-term collaboration and scientific progress—parallels the development of other types of software but still poses distinct challenges, especially in high-performance computing. Although web searches yield numerous resources on software engineering, there is still a scarcity specifically for scientific software development. This article introduces the Better Scientific Software site (https://bssw.io), a platform that hosts a community of researchers, developers, and practitioners who share their experiences and insights on scientific software development. Since 2017, this collaborative hub has gained traction within the scientific computing community, attracting a growing number of readers and contributors eager to share ideas and elevate their software development practices. In sharing the BSSw.io site’s story, we hope to encourage further growth of the BSSw.io community through both readership and contributors, with a long-term goal of fostering culture change by increasing emphasis on best practices in scientific software.
Authors
- David E. Bernholdt (ORCID: https://orcid.org/0000-0001-7874-3064)
- Mark Miller (ORCID: https://orcid.org/0000-0003-2422-2866)
- Gregory R. Watson (ORCID: https://orcid.org/0000-0002-8591-2441)
- Paul Wolfenbarger
- Lois Curfman McInnes (ORCID: https://orcid.org/0000-0002-6381-4736)
- Jean Shuler
- Deborah Stevens (ORCID: https://orcid.org/0009-0003-6227-471X)
- Rinku Gupta (ORCID: https://orcid.org/0009-0002-0669-1271)
- Roscoe Bartlett (ORCID: https://orcid.org/0000-0002-3831-8060)
- Michael A. Heroux (ORCID: https://orcid.org/0000-0002-5893-0273)
- Patricia Grubel (ORCID: https://orcid.org/0000-0002-5156-3132)
- Kasia Salim
Institutions
- Argonne National Laboratory (US)
- Lawrence Livermore National Laboratory (US)
- Oak Ridge National Laboratory (US)
- Los Alamos National Laboratory (US)
- Sandia National Laboratories (US)
Publication Details
- Journal
- Computing in Science & Engineering
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1109/mcse.2024.3480808
- Citations
- 1
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 1.05
Funders
- U.S. Department of Energy