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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.04555 |
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| _version_ | 1866911042138800128 |
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| author | Waters, Gabriella |
| author_facet | Waters, Gabriella |
| contents | Digital twins have emerged as a powerful technology for modeling and simulating complex systems across various domains (Fuller et al., 2020; Tao et al., 2019). As virtual representations of physical assets, processes, or systems, digital twins enable real-time monitoring, predictive analysis, and optimization. However, as digital twins become more sophisticated and integral to decision-making processes, ensuring their accuracy, reliability, and ethical implementation is essential. This paper presents a comprehensive framework for the Testing, Evaluation, Verification and Validation (TEVV) of digital twins to address the unique challenges posed by these dynamic and complex virtual models. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_04555 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Testing, Evaluation, Verification and Validation (TEVV) of Digital Twins: A Comprehensive Framework Waters, Gabriella Software Engineering Digital twins have emerged as a powerful technology for modeling and simulating complex systems across various domains (Fuller et al., 2020; Tao et al., 2019). As virtual representations of physical assets, processes, or systems, digital twins enable real-time monitoring, predictive analysis, and optimization. However, as digital twins become more sophisticated and integral to decision-making processes, ensuring their accuracy, reliability, and ethical implementation is essential. This paper presents a comprehensive framework for the Testing, Evaluation, Verification and Validation (TEVV) of digital twins to address the unique challenges posed by these dynamic and complex virtual models. |
| title | Testing, Evaluation, Verification and Validation (TEVV) of Digital Twins: A Comprehensive Framework |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2507.04555 |