Evaluating Hierarchical Domain-Specific Languages for Computational Science: Applying the Sprat Approach to a Marine Ecosystem Model

Johanson, Arne, Hasselbring, Wilhelm, Oschlies, Andreas and Worm, Boris (2016) Evaluating Hierarchical Domain-Specific Languages for Computational Science: Applying the Sprat Approach to a Marine Ecosystem Model Software Engineering for Science. Taylor & Francis Group, CRC Press, Boca Raton, FL, pp. 175-200. ISBN 978-1-4987-4385-3

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Abstract

In this chapter, we present a Model-Driven Software Engineering (MDSE) approach called Sprat, which adapts traditional software engineering practices in order to employ them in computational science. The approach is based on the hierarchical integration of so-called Domain-Specific Languages (DSLs) to facilitate the collaboration of scientists from different disciplines in the development of complex simulation software. We describe how multiple DSLs can be integrated to achieve a clear separation of concerns among the disciplines and how to apply Sprat during the different phases of the software life cycle.

To evaluate our approach, we discuss results from a case study in which Sprat has been utilized for the implementation of a coupled marine ecosystem model for spatially-explicit fish stock prediction. We report on the DSLs developed for this case study, how scientists benefit from them, and on lessons learned. In particular, we analyze the results from expert interviews conducted with both scientists and professional DSL developers.

Document Type: Book chapter
Additional Information: FO Sust. - Digital Ocean
Keywords: Domain-Specific Language, Computational Science, Marine Ecosystem Model
Research affiliation: OceanRep > GEOMAR > FB2 Marine Biogeochemistry > FB2-BM Biogeochemical Modeling
Kiel University > Software Engineering
Kiel University > Kiel Marine Science
OceanRep > The Future Ocean - Cluster of Excellence > FO-R11
OceanRep > The Future Ocean - Cluster of Excellence
Refereed: Yes
Projects: Sprat, Future Ocean
Date Deposited: 25 Nov 2016 09:34
Last Modified: 10 Apr 2018 10:30
URI: http://eprints.uni-kiel.de/id/eprint/34913

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