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Title: Computer Modeling and Simulation: Increasing Reliability by Disentangling Verification and Validation

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 ismore » 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.« less

Authors:
ORCiD logo [1]
  1. Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Publication Date:
Research Org.:
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
OSTI Identifier:
1556973
Report Number(s):
FERMILAB-PUB-19-361
Journal ID: ISSN 0924-6495; 1744545
Grant/Contract Number:  
AC02-07CH11359
Resource Type:
Accepted Manuscript
Journal Name:
Minds and Machines
Additional Journal Information:
Journal Volume: 29; Journal Issue: 1; Journal ID: ISSN 0924-6495
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Pronskikh, Vitaly. Computer Modeling and Simulation: Increasing Reliability by Disentangling Verification and Validation. United States: N. p., 2019. Web. doi:10.1007/s11023-019-09494-7.
Pronskikh, Vitaly. Computer Modeling and Simulation: Increasing Reliability by Disentangling Verification and Validation. United States. doi:10.1007/s11023-019-09494-7.
Pronskikh, Vitaly. Wed . "Computer Modeling and Simulation: Increasing Reliability by Disentangling Verification and Validation". United States. doi:10.1007/s11023-019-09494-7.
@article{osti_1556973,
title = {Computer Modeling and Simulation: Increasing Reliability by Disentangling Verification and Validation},
author = {Pronskikh, Vitaly},
abstractNote = {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.},
doi = {10.1007/s11023-019-09494-7},
journal = {Minds and Machines},
number = 1,
volume = 29,
place = {United States},
year = {2019},
month = {3}
}

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This content will become publicly available on March 20, 2020
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