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.

中文翻译：

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计算机建模和仿真：通过分解验证和验证来提高可靠性

模拟中使用的计算机代码和模型的验证和验证 (V&V) 是最近被科学哲学家广泛讨论的非常重要的科学实践的两个方面。虽然验证主要与计算机代码或算法表示模型方式的正确性有关，但验证更多地是指模型与现实世界及其预期用途的关系。因为复杂的模拟对于从业者来说通常是不透明的，由于它们的纠缠，Duhem 问题可能会随着验证和验证而出现；这种纠缠使得无法区分是否应该在失败的情况下归咎于编码错误或模型对目标的普遍不足。我认为，必须明确区分计算机建模和模拟，以区分验证和确认。基于这种区别，我建议将建模与验证和模拟联系起来，这与实验和验证共享共同的认知策略。为了解释它们在实践中纠缠不清的原因，我提出了一个韦伯理想-典型的建模和仿真模型作为实践中的角色。我研究了一种减轻 Duhem 问题的验证和确认方法，该方法通常适用于实践，并且基于认知策略和范围的差异。基于此分析，我提出了两种提高仿真结果可靠性的策略，即：避免在验证阶段更改已验证模型，以及使用两个或多个不同模型对同一目标系统进行模拟。针对 Winsberg 声称验证和验证相互纠缠的说法，我认为部署这项工作中提出的方法可以在使用建模和仿真的许多领域（如果不是所有领域）中减轻 V&V 的不可分割性。