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A quality requirements model and verification approach for system of systems based on description logic

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Abstract

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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Authors and Affiliations

  1. College of Command Information Systems, PLA University of Science and Technology, Nanjing, 210007, China

    Qing-long Wang, Zhi-xue Wang & Ting-ting Zhang

  2. Information Management Center, PLA University of Science and Technology, Nanjing, 210007, China

    Wei-xing Zhu

Authors
  1. Qing-long Wang
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  2. Zhi-xue Wang
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  3. Ting-ting Zhang
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  4. Wei-xing Zhu
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Corresponding authors

Correspondence to Qing-long Wang or Zhi-xue Wang.

Additional information

Project supported by the National Natural Science Foundation of China (No. 61273210)

ORCID: Zhi-xue WANG, http://orcid.org/0000-0003-2009-6508

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Wang, Ql., Wang, Zx., Zhang, Tt. et al. A quality requirements model and verification approach for system of systems based on description logic. J. Zhejiang Univ. - Sci. C 18, 346–361 (2017). https://doi.org/10.1631/FITEE.1500309

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  • DOI: https://doi.org/10.1631/FITEE.1500309

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