Abstract
Verification and validation (V&V) of computer codes and models used in simulations are two aspects of the scientific practice of high importance that recently have been discussed widely by philosophers of science. While verification is predominantly associated with the correctness of the way a model is represented by a computer code or algorithm, validation more often refers to the model’s relation to the real world and its intended use. Because complex simulations are generally opaque to a practitioner, the Duhem problem can arise with verification and validation due to their entanglement; such an entanglement makes it impossible to distinguish whether a coding error or the model’s general inadequacy to its target should be blamed in the case of a failure. I argue that a clear distinction between computer modeling and simulation has to be made to disentangle verification and validation. Drawing on that distinction, I suggest to associate modeling with verification and simulation, which shares common epistemic strategies with experimentation, with validation. To explain the reasons for their entanglement in practice, I propose a Weberian ideal–typical model of modeling and simulation as roles in practice. I examine an approach to mitigate the Duhem problem for verification and validation that is generally applicable in practice and is based on differences in epistemic strategies and scopes. Based on this analysis, I suggest two strategies to increase the reliability of simulation results, namely, avoiding alterations of verified models at the validation stage as well as performing simulations of the same target system using two or more different models. In response to Winsberg’s claim that verification and validation are entangled I argue that deploying the methodology proposed in this work it is possible to mitigate inseparability of V&V in many if not all domains where modeling and simulation are used.
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Notes
Similar to how the use of a TV set or a phone does not require knowledge of its internal organization.
In accelerator beam dynamics simulations, similar uncertainties often are associated with the so-called “symplecticity”.
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Acknowledgements
The author is indebted to two anonymous reviewers for their careful reading of his manuscript and their many insightful comments and suggestions that helped improve the paper. I would like to thank the audience at Models and Simulations 6 conference for useful comments and discussions. I am grateful to Dr. Eric Winsberg and Dr. Arkadiy Lipkin for valuable feedback on the earlier versions of the manuscript. Fermi National Accelerator Laboratory is operated by the Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics.
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Pronskikh, V. Computer Modeling and Simulation: Increasing Reliability by Disentangling Verification and Validation. Minds & Machines 29, 169–186 (2019). https://doi.org/10.1007/s11023-019-09494-7
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DOI: https://doi.org/10.1007/s11023-019-09494-7