A Complexity Analysis Approach for Model-based System Engineering

With the increasing complexity of the highly engineered products, Model-based Systems Engineering (MBSE) is proposed to support the complexity management of the product development. As the basic of complexity management, complexity analysis is used to measure the system complexity for system solution trade-offs. Using traditional MBSE approaches, system architectures of product are formalized as MBSE models whose complexity measurement provides cues to quantitative trade-offs. In this paper, an MBSE approach is proposed to support complex analysis using qualitative and quantitative approaches. A GOPPRR approach is first proposed to support MBSE formalisms. Then a complexity measurement formula is used to calculate the structure complexity of the MBSE models. Finally, through a tool-chain developed based on Open Services for Lifecycle Collaboration (OSLC), a visualization tool is used to analyze the system complexity by measuring and visualizing the model complexity. A case study is proposed to evaluate the potentials of this approach for supporting product trade-offs. From the results, the approach enables to calculate complexity of MBSE models and virtualizes the model topologies.

[1]  Bernhard Rumpe,et al.  Domain specific modeling , 2005, Software & Systems Modeling.

[2]  Kaushik Sinha,et al.  A network-based structural complexity metric for engineered complex systems , 2013, 2013 IEEE International Systems Conference (SysCon).

[3]  Ugur Dogrusoz,et al.  SBGNViz: A Tool for Visualization and Complexity Management of SBGN Process Description Maps , 2015, PloS one.

[4]  Luo Xueshan,et al.  Entropy-Based Complexity Analysis for Architecture of Information System , 2008, 2008 IEEE International Conference on Networking, Sensing and Control.

[5]  Martin Törngren,et al.  A domain-specific modeling approach supporting tool-chain development with Bayesian network models , 2020, Integr. Comput. Aided Eng..

[6]  S.M. Alhazbi.  Measuring the complexity of component-based system architecture , 2004, Proceedings. 2004 International Conference on Information and Communication Technologies: From Theory to Applications, 2004..

[7]  Stefan Kühne,et al.  Towards a comparative analysis of meta-metamodels , 2011, SPLASH Workshops.

[8]  Li Huang,et al.  Entropy-Based Complexity Analysis for Architecture of Information System , 2008, ICNSC.

[9]  Adrian Pop,et al.  Traceability Support in OpenModelica Using Open Services for Lifecycle Collaboration (OSLC) , 2017, Modelica.

[10]  Udo Lindemann,et al.  Structural Complexity Management: An Approach for the Field of Product Design , 2008 .

[11]  Guoxin Wang,et al.  Ontology Supporting Model-Based Systems Engineering Based on a GOPPRR Approach , 2019, WorldCIST.

[12]  Elaine J. Weyuker,et al.  Evaluating Software Complexity Measures , 2010, IEEE Trans. Software Eng..