Lightweight Software Process Improvement using Productivity and Sustainability Improvement Planning (PSIP)
Originally published at BSSw.io
Are you new to PSIPs? Are you interested in learning more about this software improvement process targetted for the scientific computing community? The paper titled A Lightweight Software Process Improvement using Productivity and Sustainability Improvement Planning (PSIP) is a good overview of this topic.
| Resource information | Details |
|---|---|
| Paper title | Lightweight Software Process Improvement using Productivity and Sustainability Improvement Planning (PSIP) |
| Authors | Michael A. Heroux, Elsa Gonsiorowski, Rinku Gupta, Reed Milewicz, David Moulton, Gregory Watson, Jim Willenbring, Richard Zamora and Elaine Raybourn |
| Publication | Year 2019, U.S. DoE Office of Scientific and Technical Information, Publication Link |
Within the context of scientific software research and development, software process improvement (SPI) is undeveloped territory. While software has garnered increasing importance in the scientific computing field in recent decades, and while researchers perceive tremendous value in improving software practices, lack of time and resources along with the complexities of traditional SPI methods have hindered the adoption of better software practices.
The Productivity and Sustainability Improvement Planning (PSIP) process recognizes that productivity and sustainability improvements for scientific software benefit from an incremental, iterative approach. This paper presents an overview of PSIP and how it compares to other software process improvement methods. Also mentioned are case studies that describe how the use of PSIP led to successful improvements in team effectiveness and efficiency.
This paper is good read for anyone embarking on the PSIP journey with an aim of reducing the technical debt of their project and improving long-term software quality and sustainability.
Contributed by Rinku Gupta
For more resources on PSIP, please refer to the following articles on the BSSw.io site: