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SimScience 2017: Simulation Science pp 193-207 | Cite as

Extending the CMMI Engineering Process Areas for Simulation Systems Engineering

  • Somaye Mahmoodi
  • Umut Durak
  • Torsten Gerlach
  • Sven Hartmann
  • Andrea D’Ambrogio
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 889)

Abstract

Today’s companies in high-tech industries develop products of high complexity which consist of complicated subsystems with many heterogeneous components integrated together. As the system complexity increases, it becomes increasingly more challenging to manage the tedious development process. The Capability Maturity Model Integration (CMMI) was proposed as a general framework for process management and improvement which judges the maturity of a process. Simulations have long been regarded as complex and integrated systems. Simulation system engineering manages the total simulation system’s life-cycle process. The adaptation of the CMMI for simulation life-cycle processes is envisioned as a domain specific solution for simulation process management and improvement. This article investigates the opportunities of extending the CMMI engineering process area with emphasis in simulation system engineering, having its roots from IEEE Recommended Practice for Distributed Simulation Engineering and Execution Process (DSEEP).

Keywords

Distributed Simulation Engineering and Execution Process (DSEEP) Capability Maturity Model Integration (CMMI) Simulation process improvement 

References

  1. 1.
    CMMI Product Team: CMMI for development, version 1.3 (2010)Google Scholar
  2. 2.
    Goldenson, D., Gibson, D.L.: Demonstrating the impact and benefits of CMMI: an update and preliminary results (2003)Google Scholar
  3. 3.
    Balci, O.: Guidelines for successful simulation studies. In: Proceedings of the 22nd Conference on Winter Simulation. IEEE Press (1990)Google Scholar
  4. 4.
    IEEE Recommended Practice for High Level Architecture (HLA) Federation Development and Execution Process (FEDEP): IEEE Std 1516.3-2003 (2003)Google Scholar
  5. 5.
    IEEE Recommended Practice for Distributed Simulation Engineering and Execution Process (DSEEP): IEEE Std 1730-2010 (2011)Google Scholar
  6. 6.
    Durak, U., Ören, T.: Towards an ontology for simulation systems engineering. In: Proceedings of the 49th Annual Simulation Symposium. Society for Computer Simulation International, p. 13 (2016)Google Scholar
  7. 7.
    D’Ambrogio, A., Durak, U.: Setting systems and simulation life cycle processes side by side. In: 2016 IEEE International Symposium on Systems Engineering (ISSE), pp. 1–7. IEEE (2016)Google Scholar
  8. 8.
    Richey, F.: Modeling and simulation CMMI: a conceptual view. CrossTalk J. Def. Softw. Eng. 15(3), 29–30 (2002)Google Scholar
  9. 9.
    Withalm, J., Wölfel, W., Duin, H., Peters, M.: Combining CMMI with serious gaming and e-learning to support skill assessment and development in tourism. In: International Conference on Interactive Computer Aided Learning (ICL2008). University Press, Kassel (2008)Google Scholar
  10. 10.
    Chen, C., Kuo, C., Chen, P.: The teaching capability maturity model for teachers in higher education: a preliminary study. In: 2011 International Conference on Frontiers in Education: Computer Science and Computer Engineering (2011)Google Scholar
  11. 11.
    Williams, P.: A practical application of CMM to medical security capability. Inf. Manag. Comput. Secur. 16(1), 58–73 (2008)CrossRefGoogle Scholar
  12. 12.
    Neuhauser, C.: A maturity model: does it provide a path for online course design. J. Interact. Online Learn. 3(1), 1–17 (2004)MathSciNetGoogle Scholar
  13. 13.
    Bofinger, M., Robinson, N., Lindsay, P., Spiers, M., Ashford, M., Pitman, A.: Experience with extending CMMISM for safety related applications. In: 12th Annual Symposium International Council on Systems Engineering, Las Vegas, NV (2002)Google Scholar
  14. 14.
    Fujimoto, R., Bock, C., Chen, W., Page, E., Panchal, J.H.: Research challenges in modeling and simulation for engineering complex systems (2017)Google Scholar
  15. 15.
    Duda, H., Gerlach, T., Advani, S., Potter, M.: Design of the DLR AVES research flight simulator. In: AIAA Modeling and Simulation Technologies Conference (2013)Google Scholar
  16. 16.
    Gerlach, T., Durak, U.: AVES SDK: bridging the gap between simulator and flight systems designer. In: AIAA Modeling and Simulation Technologies Conference (2015)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Somaye Mahmoodi
    • 1
  • Umut Durak
    • 1
    • 2
  • Torsten Gerlach
    • 2
  • Sven Hartmann
    • 1
  • Andrea D’Ambrogio
    • 3
  1. 1.Department of InformaticsClausthal University of TechnologyClausthal-ZellerfeldGermany
  2. 2.Institute of Flight SystemsGerman Aerospace Center (DLR)BraunschweigGermany
  3. 3.Department of Enterprise EngineeringUniversity of Rome Tor VergataRomeItaly

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