Raising the Bar: Assurance Cases for Scientific Software
| Autor: | Mojdeh Sayari Nejad, Spencer Smith, Alan Wassyng, Karla Morris, Jeffrey C. Carver |
|---|---|
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Computing in Science & Engineering. 23:47-57 |
| ISSN: | 1558-366X 1521-9615 |
| Popis: | Assurance cases provide an organized and explicit argument for correctness. They can dramatically improve the quality of scientific software. Assurance cases are already effectively used for real-time safety critical systems. Their advantages for scientific software include engaging domain experts, producing only necessary documentation, and providing evidence that can be verified/replicated. This article illustrates assurance cases through the correctness case for 3dfim+, software for analyzing activity in the brain. The example justifies the value of assurance cases for scientific software, since the existing documentation is shown to have ambiguities and omissions, such as an incompletely defined ranking function and missing details on the coordinate system. We identified a serious concern for 3dfim+: running the software does not produce any warning about the necessity of using data that matches the parametric statistical model employed for the correlation calculations. Raising the bar for scientific software is both feasible and necessary. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|