ArticlePloS one2020
A content analysis-based approach to explore simulation verification and identify its current challenges.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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Who cites it
2 citing papers in PubMed.
- Short-Range Forecasting of COVID-19 During Early Onset at County, Health District, and State Geographic Levels Using Seven Methods: Comparative Forecasting Study.Journal of medical Internet research · 2021Article
- Credible practice of modeling and simulation in healthcare: ten rules from a multidisciplinary perspective.Journal of translational medicine · 2020Review
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Verification is a crucial process to facilitate the identification and removal of errors within simulations. This study explores semantic changes to the concept of simulation verification over the past six decades using a data-supported, automated content analysis approach. We collect and utilize a corpus of 4,047 peer-reviewed Modeling and Simulation (M&S) publications dealing with a wide range of studies of simulation verification from 1963 to 2015. We group the selected papers by decade of publication to provide insights and explore the corpus from four perspectives: (i) the positioning of prominent concepts across the corpus as a whole; (ii) a comparison of the prominence of verification, validation, and Verification and Validation (V&V) as separate concepts; (iii) the positioning of the concepts specifically associated with verification; and (iv) an evaluation of verification's defining characteristics within each decade. Our analysis reveals unique characterizations of verification in each decade. The insights gathered helped to identify and discuss three categories of verification challenges as avenues of future research, awareness, and understanding for researchers, students, and practitioners. These categories include conveying confidence and maintaining ease of use; techniques' coverage abilities for handling increasing simulation complexities; and new ways to provide error feedback to model users.
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