

FOLLOWUS
1College of Command Information Systems, PLA University of Science and Technology, Nanjing 210007, China
2Information Management Center, PLA University of Science and Technology, Nanjing 210007, China
E-mail:jsxq901901@163.com
E-mail:wzxcx801@163.com
Received:25 September 2015,
Accepted:27 February 2016,
Published:2017-03
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Qing-long WANG, Zhi-xue WANG, Ting-ting ZHANG, et al. A quality requirements model and verification approach for system of systems based on description logic[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(3): 346-361.
Qing-long WANG, Zhi-xue WANG, Ting-ting ZHANG, et al. A quality requirements model and verification approach for system of systems based on description logic[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(3): 346-361. DOI: 10.1631/FITEE.1500309.
在体系顶层设计问题中,体系质量需求分析的关键是体系需求的建模以及自动验证,需要合适的建模方法来描述体系质量需求以及验证质量需求是否满足体系的能力需求。针对体系质量需求建模和验证问题,本文提出一种基于描述逻辑的体系质量需求建模与验证方法。首先,为解决体系功能和非功能需求的描述问题,通过添加模糊构造子扩展统一建模语言(Unified Modeling Language
UML)中的类和关系并定义了基于元模型的领域特定建模语言以实现体系质量需求中模糊和不确定概念的建模。随后提出了基于云模型的体系质量需求评估方法实现了对体系质量需求的评估。然后,提出了模型转换算法将模糊UML构建的体系需求模型转换为描述逻辑本体模型,并通过使用描述逻辑本体推理工具实现需求模型的自动化验证。最后,通过一个案例验证和演示了本文方法的正确性和可行性。
System of systems engineering (SoSE) involves the complex procedure of translating capability needs into the high-level requirements for system of systems (SoS) and evaluating how the SoS quality requirements meet their capability needs. One of the key issues is to model the SoS requirements and automate the verification procedure. To solve the problem of modeling and verification
meta-models are proposed to refine both functional and non-functional characteristics of the SoS requirements. A domain-specific modeling language is defined by extending Unified Modeling Language (UML) class and association with fuzzy constructs to model the vague and uncertain concepts of the SoS quality requirements. The efficiency evaluation function of the cloud model is introduced to evaluate the efficiency of the SoS quality requirements. Then a concise algorithm transforms the fuzzy UML models into the description logic (DL) ontology so that the verification can be automated with a DL reasoner. This method implements modeling and verification of high-level SoS quality requirements. A crisp case is used to facilitate and demonstrate the correctness and feasibility of this method.
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