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Facilitating V-Model Analyses: Useful Computational Tools for Test and Evaluation

机译：促进V模型分析：用于测试和评估的有用计算工具

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摘要

The classic V-Model is critical to Systems Engineering. This paper will examine the special data visualization needs and challenges presented by Test and Evaluation (T&E) and their use of visualization to serve the V-Model. The rapid and insightful analysis of the masses of data collected during the test and evaluation cycle has become one of the grand challenges of this community. The authors assert that newly developed capabilities utilizing emerging capabilities can and should be implemented to assure the T&E analysts are given the information they need most, when they need it, and in a form that will produce the correct outcome. The paper recounts and alludes to historical examples of the difficulties in effectively conveying information within the chain of command, supporting the notion that these problems are neither unique to simulation or T&E nor are they issues that can be ignored. Special emphasis will be put on new ways to convey the range of analytic solutions and alternative conclusions and communicate the relative likelihood of future performance, durability and safety. The T&E community is also faced with the need to convey the insights contained in the data in enlightening and compelling ways to both analysts and end-users. A survey of associated topics like causal modeling and behavioral science insights will be presented along with analysis as to their contribution to better exploitability. The paper concludes with recommended approaches for studying, evaluating and implementing the most promising techniques and technologies.
机译：经典的V模型对于系统工程至关重要。本文将研究测试和评估（T＆E）提出的特殊数据可视化需求和挑战，以及它们在可视化中为V模型提供的服务。对在测试和评估周期中收集到的大量数据进行快速而有见地的分析已成为该社区的一大挑战。作者断言，可以并且应该实施利用新兴功能的新开发功能，以确保T＆E分析师能够在需要时以最正确的方式获得最需要的信息。本文叙述并暗示了在指挥链内有效传达信息的困难的历史例子，支持了以下观点：这些问题既不是仿真或T＆E所独有的，也不是可以忽略的问题。将特别强调新方法，以传达分析解决方案和替代结论的范围，并传达未来性能，耐用性和安全性的相对可能性。 T＆E社区还面临着以启发性和令人信服的方式向分析师和最终用户传达数据中包含的见解的需求。将对因果模型和行为科学见解等相关主题进行调查，并分析它们对更好利用的贡献。本文以研究，评估和实施最有前途的技术的推荐方法作为结尾。

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