Nmag micromagnetic simulation tool - software engineering lessons learned
January 27, 2016 Β· Declared Dead Β· π 2016 IEEE/ACM International Workshop on Software Engineering for Science (SE4Science)
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Authors
Hans Fangohr, Maximilian Albert, Matteo Franchin
arXiv ID
1601.07392
Category
cs.SE: Software Engineering
Cross-listed
physics.comp-ph
Citations
7
Venue
2016 IEEE/ACM International Workshop on Software Engineering for Science (SE4Science)
Last Checked
4 months ago
Abstract
We review design and development decisions and their impact for the open source code Nmag from a software engineering in computational science point of view. We summarise lessons learned and recommendations for future computational science projects. Key lessons include that encapsulating the simulation functionality in a library of a general purpose language, here Python, provides great flexibility in using the software. The choice of Python for the top-level user interface was very well received by users from the science and engineering community. The from-source installation in which required external libraries and dependencies are compiled from a tarball was remarkably robust. In places, the code is a lot more ambitious than necessary, which introduces unnecessary complexity and reduces main- tainability. Tests distributed with the package are useful, although more unit tests and continuous integration would have been desirable. The detailed documentation, together with a tutorial for the usage of the system, was perceived as one of its main strengths by the community.
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