Articles | Volume 4, issue 2
https://doi.org/10.5194/gmd-4-435-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-4-435-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Automated continuous verification for numerical simulation
P. E. Farrell
Applied Modelling and Computation Group, Department of Earth Science and Engineering, Imperial College London, SW7 2AZ, UK
M. D. Piggott
Applied Modelling and Computation Group, Department of Earth Science and Engineering, Imperial College London, SW7 2AZ, UK
Grantham Institute for Climate Change, Imperial College London, London, SW7 2AZ, UK
G. J. Gorman
Applied Modelling and Computation Group, Department of Earth Science and Engineering, Imperial College London, SW7 2AZ, UK
D. A. Ham
Applied Modelling and Computation Group, Department of Earth Science and Engineering, Imperial College London, SW7 2AZ, UK
Grantham Institute for Climate Change, Imperial College London, London, SW7 2AZ, UK
C. R. Wilson
Lamont-Doherty Earth Observatory, Columbia University, New York, USA
T. M. Bond
Applied Modelling and Computation Group, Department of Earth Science and Engineering, Imperial College London, SW7 2AZ, UK
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19 citations as recorded by crossref.
- Shingle 2.0: generalising self-consistent and automated domain discretisation for multi-scale geophysical models A. Candy & J. Pietrzak https://doi.org/10.5194/gmd-11-213-2018
- Editorial: The publication of geoscientific model developments v1.2 https://doi.org/10.5194/gmd-12-2215-2019
- Ensemble-based statistical verification of INM RAS Earth system model M. Tarasevich et al. https://doi.org/10.1515/rnam-2023-0014
- Failure analysis of parameter-induced simulation crashes in climate models D. Lucas et al. https://doi.org/10.5194/gmd-6-1157-2013
- Development and Verification of a Numerical Library for Solving Global Terrestrial Multiphysics Problems G. Bisht & W. Riley https://doi.org/10.1029/2018MS001560
- A survey on software test automation return on investment, in organizations predominantly from Bengaluru, India S. Reine De Reanzi & P. Ranjit Jeba Thangaiah https://doi.org/10.1177/18479790211062044
- Testing research software: a survey N. Eisty & J. Carver https://doi.org/10.1007/s10664-022-10184-9
- From integration to fusion: the challenges ahead J. Sutherland et al. https://doi.org/10.1144/SP408.6
- Application of the adjoint approach to optimise the initial conditions of a turbidity current with the AdjointTurbidity 1.0 model S. Parkinson et al. https://doi.org/10.5194/gmd-10-1051-2017
- gTOOLS, an open-source MATLAB program for processing high precision, relative gravity data for time-lapse gravity monitoring M. Battaglia et al. https://doi.org/10.1016/j.cageo.2021.105028
- Testing scientific software: A systematic literature review U. Kanewala & J. Bieman https://doi.org/10.1016/j.infsof.2014.05.006
- Efficient unstructured mesh generation for marine renewable energy applications A. Avdis et al. https://doi.org/10.1016/j.renene.2017.09.058
- Model input verification of large scale simulations R. Neykova & D. Groen https://doi.org/10.1080/17477778.2025.2490133
- Automated regression test method for scientific computing libraries: Illustration with SPHinXsys B. Zhang et al. https://doi.org/10.1007/s42241-024-0042-6
- An implicit wetting and drying approach for non-hydrostatic baroclinic flows in high aspect ratio domains A. Candy https://doi.org/10.1016/j.advwatres.2017.02.004
- Application of metamorphic testing monitored by test adequacy in a Monte Carlo simulation program J. Ding & X. Hu https://doi.org/10.1007/s11219-016-9337-3
- Unit and regression tests of scientific software: A study on SWMM Z. Peng et al. https://doi.org/10.1016/j.jocs.2021.101347
- Towards a fully unstructured ocean model for ice shelf cavity environments: Model development and verification using the Firedrake finite element framework W. Scott et al. https://doi.org/10.1016/j.ocemod.2023.102178
- Firedrake-Fluids v0.1: numerical modelling of shallow water flows using an automated solution framework C. Jacobs & M. Piggott https://doi.org/10.5194/gmd-8-533-2015
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