Abstract
Implementation can be introduced as one of the important steps of simulation engineering in which all the concepts and ideas, abstracted as models, are transformed to an executable form. MDE had a major effect on the practices of this step. Models became the major artifacts for implementation. MDE proposed that model development and code generation replace the traditional coding practices. This also disrupted and changed the other major implementation practices like static code analysis, integration, and testing. As models are regarded as the major artifacts, the model development is pronounced as the major activity. Guidelines have been developed for increasing the readability and maintainability of the simulation models and the efficiency and performance of the generated code. Along with them, methods and techniques have been developed for model checking and repair. Advancements in model-to-text transformation enabled effective and flexible code generation. Integration requirements could then be attacked by retargeting the code generator for particular platforms. In the same vein, model-based testing (MBT) introduced generation of executable test cases from a model. This chapter explains the activities of implementation that have been changing with introduction of MDE. These activities include model development, model checking, code generation and integration, and testing. These activities are first explained and introduced with examples from an off-the-shelf modeling and simulation environment, and then a recent methodology research on that particular activity is presented.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Amelunxen, C., Legros, E., Schürr, A., & Stürmer, I. (2008). Checking and enforcement of modeling guidelines with graph transformations. In Applications of graph transformations with industrial relevance (pp. 313–328). Berlin: Springer.
Astrom, K., & Wittenmark, B. (1984). Computer controlled systems: Theory and design. Englewood Cliffs: Prentice Hall.
Brambilla, M., Cabot, J., & Wimmer, M. (2012). Model-driven software engineering in practice. San Rafael: Morgan & Claypool Publishers.
Campbell, S., Chancelier, J., & Nikaukhah, R. (2006). Modeling and simulation in scilab/scicos. New York: Springer.
Czarnecki, K., & Helsen, S. (2003). Classification of model transformation approaches. In Proceedings of OOPSLA’03 workshop on generative techniques in context of model driven architecture. Anaheim: ACM.
Czarnecki, K., & Helsen, S. (2006). Feature-based survey of model transformation approaches. IBM Systems Journal, 45(3), 621–645.
Denckla, B., & Mosterman, P. (2005). Formalizing causal block diagrams for modeling a class of hybrid dynamic systems. In Proceedings of 44th IEEE conference on decision and control and the European control conference. Seville: IEEE.
Denil, J., Mosterman, P., & Vangheluwe, H. (2014). Rule-based model transformations for and in Simulink. Proceedings of the Symposium on Theory of Modeling and Simulation-DEVS Integrative (pp. 314–421). San Diago: SCS.
Durak, U. (2015). Pragmatic model transformations for refactoring in Scilab/Xcos. International Journal of Modeling, Simulation, and Scientific Computing. doi:10.1142/S1793962315410044
Durak, U., Schmidt, A., & Pawletta, T. (2014). Ontology for objective flight simulator fidelity evaluation. Simulation Notes Europe, 24(2), 69–78.
Durak, U., Schmidt, A., & Pawletta, T. (2015). Model-based testing for objective fidelity evaluation of engineering and research flight simulators. In AIAA modeling and simulation technologies conference. Dallas: AIAA.
ESA. (2005a). SMP 2.0 C++ mapping. Paris: European Space Agency.
ESA. (2005b). SMP 2.0 component model. Paris: European Space Agency.
ESA. (2005c). SMP 2.0 handbook. Paris: European Space Agency.
ESA. (2005d). SMP 2.0 metamodel. Paris: European Space Agency.
Farkas, T., Hein, C., & Ritter, T. (2006). Automatic evaluation of modelling rules and design guidelines. In Proceedings of the 2. workshop “From code centric to model centric software engineering: practices, implications and ROI”. Bilboa: ESI.
Frankel, D. (2003). Model driven architecture: Applying MDA to enterprise computing. New York: Wiley.
Gerlach, T., Durak, U., & Gotschlich, J. (2014). Model integration workflow for keeping models up to date in a research simulator. In Proceedings of 2014 International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH) (pp. 125–132). Vienna: SCITEPRESS.
Giese, H., Meyer, M., & Wagner, R. (2006). A prototype guideline checking and model transformations in MATLAB/Simulink. In Proceedings of the 4th international Fujaba Days (pp. 56–60). Bayreuth: University of Bayreuth.
Gotschlich, J., Gerlach, T., & Durak, U. (2014). 2Simulate: A distributed real-time simulation framework. Workshop der ASIM/GI-Fachgruppen STS und GMMS. Reutlingen: ARGESIM.
Henry, J. (2011). Orion GN&C MATLAB/Simulink standards. Houston: NASA.
Hollmann, D., Cristia, M., & Frydman, C. (2012). Adapting model-based testing techniques to DEVS models validation. In Proceedings of the 2012 symposium of theory of modeling and simulation – DEVS integrative. San Diego: SCS.
IEEE. (2008). Systems and software engineering – Software life cycle processes. IEEE SA - 12207-2008. New York: IEEE.
IEEE. (2010). IEEE recommended practice for Distributed Simulation Engineering and Execution Process (DSEEP). IEEE Std 1730-2010. New York: IEEE.
Klee, H., & Allen, R. (2011). Simulation of dynamic systems with MATLAB and Simulink. Boca Raton: CRC Press.
Kleppe, A., Warmer, J., & Bast, W. (2003). MDA explained: The model driven architecture: Practice and promise (1st ed.). Boston: Addison-Wesley Professional.
Lee, C., & Friedman, J. (2013). Requirements modeling and automated requirements-based test generation. SAE International Journal of Aerospace, 6(2), 607–615.
Legros, E., Amelunxen, C., Klar, F., & Schürr, A. (2009). Generic and reflective graph transformations for checking and enforcement of modeling guidelines. Journal of Visual Languages & Computing, 20(4), 252–268.
MathWorks Automotive Advisory Board. (2015). MathWorks® automotive advisory board control algorithm modeling guidelines using MATLAB®, Simulink®, and Stateflow®. Natick: The MathWorks, Inc.
Mellor, S., & Balcer, M. (2002). Executable UML: A foundation for model-driven architecture (1st edn.). Boston: Addison-Wesley Professional.
Microsoft. (2015). Code generation and T4 text templates [Online]. Available at: https://msdn.microsoft.com/en-us/library/bb126445.aspx. Accessed 9 July 2015.
Modelica Association. (2014). Functional mock-up interface for model exchange and co-simulation. Linköping: Modelica Association.
Modelon, A. B. (2015). FMI toolbox user’s guide. Lund: Modelon AB.
Nickel, U., Niere, J., & Zündorf, A. (2000). Tool demonstration: The Fujaba environment. In Proceedings of the 22nd International Conference on Software Engineering (ICSE) (pp. 742–745). Limerick: ACM Press.
Pastor, O., & Molina, J. (2007). Model-driven architecture in practice: A software production environment based on conceptual modeling. Secaucus: Springer.
Pawletta, T., Pascheka, D., Schmidt, A., & Pawletta, S. (2014). Ontology-assisted system modeling and simulation within MATLAB/Simulink. Simulation Notes Europe, 24(2), 59–68.
Schmidt, A., Durak, U., Rasch, C., & Pawletta, T. (2015). Model-based testing approach for MATLAB/Simulink using system entity structure and experimental frames. In Proceedings of symposium on theory of modeling and simulation ’15. Alexandria: SCS.
Scilab Enterprises. (2015). Scilab online help [Online]. Available at: https://help.scilab.org/. Accessed 1 July 2015.
SimGe. (2015). SimGe web site [Online]. Available at: https://sites.google.com/site/okantopcu/simge. Accessed 15 Aug 2015.
Steinberg, D., Budinsky, F., Paternostro, M., & Merks, E. (2009). EMF: Eclipse modeling framework (2nd ed.). Boston: Pearson Education, Inc.
Stürmer, I., & Travkin, D. (2007). Automated transformation of MATLAB Simulink and Stateflow Models. In Proceedings of 4th workshop on object-oriented modeling of real-time embedded systems (pp. 57–62). Padeborn: University of Paderborn.
Stürmer, I., Kreuz, I., Schäfer, W., & Schürr, A. (2007). The MATE approach: Enhanced Simulink and stateflow model transformations. In Proceedings of mathworks automative conference. Dearborn: Mathworks, Inc.
The MathWorks, Inc. (2006). Simulink® verification and validation release notes, V1.1.2 (R2006a). Natick: The MathWorks, Inc.
The MathWorks, Inc. (2015a). Simulink® Coder™ getting started guide. Natick: The MathWorks, Inc.
The MathWorks, Inc. (2015b). Simulink® Coder™ target language compiler. Natick: The MathWorks, Inc.
The MathWorks, Inc. (2015c). Simulink® Coder™ user’s guide. Natick: The MathWorks, Inc.
The MathWorks, Inc. (2015d). Simulink® getting started guide. Natick: The MathWorks, Inc.
The MathWorks, Inc. (2015e). Simulink® reference. Natick: The MathWorks, Inc.
The MathWorks, Inc. (2015f). Simulink® user guide. Natick: The MathWorks, Inc.
The MathWorks, Inc. (2015g). Simulink® Verification and Validation™ user’s guide. Natick: The MathWorks, Inc.
Tran, Q., Wilmes, B., & Dziobek, C. (2013). Refactoring of Simulink diagrams via composition of transformation steps. In Proceedings of 8th international conference on software engineering advances (pp. 140–145). Venice: IARIA XPS Press.
Utting, M., & Legeard, M. (2007). Practical model-based testing (1st ed.). San Francisco: Morgen Kaufmann Publishers, Inc.
Watt, A. (2005). Beginning regular expressions. Indianapolis: Wiley.
Yilmaz, F., Durak, U., Taylan, K., & Oguztuzun, H. (2014). Adapting functional mockup units for HLA-compliant distributed simulation. In Proceedings of the 10th International Modelica Conference. Lund: Linköping University Press.
Zander, J., Schieferdecker, I., & Mostermann, P. (2012). Model-based testing for embedded systems. Boca Raton: CRC Press Taylor & Francis Group.
Zander-Nowicka, J. (2008). Model-based testing of real-time embedded systems in the automotive domain. Berlin: Technical University Berlin.
Zander-Nowicka, J., Schieferdecker, I., & Farkas, T. (2006). Derivation of executable test models from embedded system models using model driven architecture artefacts – automotive domain. In Tagungsband Dagstuhl-Workshop MBEES:Modellbasierte Entwicklung eingebetteter Systeme II (pp. 131–140). Braunschweig: Technische Universität Braunschweig.
Zeigler, B. (1984). Multifaceted modelling and discrete event simulation. San Diego: Academic Press Professional, Inc.
Zeigler, B., & Hammonds, P. (2007). Modeling and simulation-based data engineering: introducing pragmatics in ontologies for net-centric information exchange. Amsterdam: Academic Press.
Zeigler, B., Praehofer, H., & Kim, T. (2000). Theory of modeling and simulation: Integrating discrete event and continuous complex systems. Orlando: Academic.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Topçu, O., Durak, U., Oğuztüzün, H., Yilmaz, L. (2016). Implementation, Integration, and Testing. In: Distributed Simulation. Simulation Foundations, Methods and Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-03050-0_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-03050-0_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03049-4
Online ISBN: 978-3-319-03050-0
eBook Packages: Computer ScienceComputer Science (R0)