Synthesis and exploration of multi-level, multi-perspective architectures of automotive embedded systems


In industry, evaluating candidate architectures for automotive embedded systems is routinely done during the design process. Today’s engineers, however, are limited in the number of candidates that they are able to evaluate in order to find the optimal architectures. This limitation results from the difficulty in defining the candidates as it is a mostly manual process. In this work, we propose a way to synthesize multi-level, multi-perspective candidate architectures and to explore them across the different layers and perspectives. Using a reference model similar to the EAST-ADL domain model but with a focus on early design, we explore the candidate architectures for two case studies: an automotive power window system and the central door locking system. Further, we provide a comprehensive set of question templates, based on the different layers and perspectives, that engineers can ask to synthesize only the candidates relevant to their task at hand. Finally, using the modeling language Clafer, which is supported by automated backend reasoners, we show that it is possible to synthesize and explore optimal candidate architectures for two highly configurable automotive sub-systems.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13


  1. 1.

    Quality attributes are sometimes referred to as non-functional properties.

  2. 2.

    We use italics to introduce a reference model component.

  3. 3.

    We use typeface to denote Emily’s model elements; a concrete component.

  4. 4.

    Throughout this paper if the word Clafer begins with an uppercase letter it describes the language, whereas a lowercase one denotes the language construct.

  5. 5.

    We use bold typeface to refer to a clafer in a listing.

  6. 6.

  7. 7.

    As of this writing, we are using Choco version 3.

  8. 8.

  9. 9.


  1. 1.

    Archeopterix: Last accessed 21 Feb 2017

  2. 2.

    Autofocus 3: Last accessed 21 Feb 2017

  3. 3.

    Clafer: Last accessed 21 Feb 2017

  4. 4.

    EAST-ADL domain model specification, version V2.1.12.: Last accessed 21 Feb 2017

  5. 5.

    OSATE, version 2.: Last accessed 21 Feb 2017

  6. 6.

    Aleti, A., Bjornander, S., Grunske, L., Meedeniya, I.: Archeopterix: An extendable tool for architecture optimization of aadl models. In: ICSE Workshop on Model-Based Methodologies for Pervasive and Embedded Software, 2009, MOMPES ’09. pp. 61–71 (2009)

  7. 7.

    Aleti, A., Buhnova, B., Grunske, L., Koziolek, A., Meedeniya, I.: Software architecture optimization methods: a systematic literature review. IEEE Trans. Softw. Eng. 39(5), 658–683 (2013)

    Article  Google Scholar 

  8. 8.

    Antkiewicz, M., Bąk, K., Murashkin, A., Olaechea, R., Liang, J., Czarnecki, K.: Clafer tools for product line engineering. In: Software Product Line Conference (2013)

  9. 9.

    Bąk, K., Diskin, Z., Antkiewicz, M., Czarnecki, K., Wąsowski, A.: Clafer: unifying class and feature modeling. Softw. Syst. Model. 15(3), 811–845 (2016)

    Article  Google Scholar 

  10. 10.

    Bosch Semiconductors: CAN literature. Last accessed 21 Feb 2017

  11. 11.

    Brandt, L., Krämer, N., Metzger, J., Lindemann, U., et al.: Optimization approach for function-partitioning in an automotive electric electronic system architecture. In: DS 70: Proceedings of DESIGN 2012 (2012)

  12. 12.

    Broy, M.: Challenges in automotive software engineering. In: 28th International Conference on Software Engineering, pp. 33–42 (2006)

  13. 13.

    Coit, D.W., Smith, A.E.: Solving the redundancy allocation problem using a combined neural network/genetic algorithm approach. Comput. Oper. Res. 23(6), 515–526 (1996)

    Article  MATH  Google Scholar 

  14. 14.

    Coit, D.W., Smith, A.E.: Redundancy allocation to maximize a lower percentile of the system time-to-failure distribution. IEEE Trans. Reliabil. 47(1), 79–87 (1998)

    Article  Google Scholar 

  15. 15.

    Cuenot, P., Chen, D., Gerard, S., Lonn, H., Reiser, M.O., Servat, D., Sjostedt, C.J., Kolagari, R., Torngren, M., Weber, M.: Managing complexity of automotive electronics using the EAST-ADL. In: 12th IEEE International Conference on Engineering Complex Computer Systems, 2007, pp. 353–358 (2007)

  16. 16.

    Dave, B.P., Jha, N.K.: Cohra: hardware-software cosynthesis of hierarchical heterogeneous distributed embedded systems. IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. 17(10), 900–919 (1998)

    Article  Google Scholar 

  17. 17.

    Davis, R.I., Burns, A., Bril, R.J., Lukkien, J.J.: Controller area network (can) schedulability analysis: refuted, revisited and revised. Real-Time Syst. 35(3), 239–272 (2007)

    Article  Google Scholar 

  18. 18.

    Feiler, P., Hansson, J.: Flow latency analysis with the architecture analysis and design language (AADL). Tech. Rep. CMU/SEI-2007-TN-010, Software Engineering Institute, Carnegie Mellon University, Pittsburgh, PA (2007).

  19. 19.

    Florentz, B., Huhn, M.: Embedded systems architecture: evaluation and analysis. In: Proceedings of the 2nd International Conference on Quality of Software Architectures, QoSA’06, pp. 145–162 (2006)

  20. 20.

    Glaß, M., Lukasiewycz, M., Wanka, R., Haubelt, C., Teich, J.: Multi-objective routing and topology optimization in networked embedded systems. In: Embedded Computer Systems: Architectures, Modeling, and Simulation 2008, 74–81 (2008)

  21. 21.

    Graf, S., Glaß, M., Teich, J., Lauer, C.: Multi-variant-based design space exploration for automotive embedded systems. In: Proceedings of the Conference on Design, Automation and Test in Europe, DAT ’14, pp. 7:1–7:6. European Design and Automation Association (2014)

  22. 22.

    Han, K., Kwon, Y., Kim, W., Cho, J.: Distributed hierarchical service network for automotive embedded system. In: Information Networking (ICOIN), pp. 188–192 (2012)

  23. 23.

    ISO: Road vehicles–local interconnect network (LIN)—part 6: Protocol conformance test specification (2015). ISO/DIS 17987-6.2

  24. 24.

    Jackson, D., Estler, H., Rayside, D., et al.: The guided improvement algorithm for exact, general-purpose, many-objective combinatorial optimization (2009)

  25. 25.

    Kang, E., Jackson, E., Schulte, W.: An approach for effective design space exploration. In: Foundations of Computer Software. Modeling, Development, and Verification of Adaptive Systems, pp. 33–54. Springer (2010)

  26. 26.

    Kang, K., Cohen, S., Hess, J., Novak, W., Peterson, A.: Feature-oriented domain analysis (foda) feasibility study. Tech. Rep. CMU/SEI-90-TR-021, Software Engineering Institute, Carnegie Mellon University, Pittsburgh, PA (1990).

  27. 27.

    Kugele, S., Pucea, G.: Model-based optimization of automotive E/E-architectures. In: Proceedings of the 6th International Workshop on Constraints in Software Testing, Verification, and Analysis, CSTVA 2014, pp. 18–29 (2014)

  28. 28.

    Li, R., Etemaadi, R., Emmerich, M.T.M., Chaudron, M.R.V.: An evolutionary multiobjective optimization approach to component-based software architecture design. In: Evolutionary Computation (CEC), pp. 432–439 (2011)

  29. 29.

    Lin, C.W., Rao, L., Giusto, P., D’Ambrosio, J., Sangiovanni-Vincentelli, A.L.: Efficient wire routing and wire sizing for weight minimization of automotive systems. IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst. 34(11), 1730–1741 (2015)

    Article  Google Scholar 

  30. 30.

    Meedeniya, I.: Architecture optimisation of embedded systems under uncertainty in probabilistic reliability evaluation model parameters. Ph.D. thesis, Swinburne University of Technology, Melbourne, Australia (2012)

  31. 31.

    Meedeniya, I., Buhnova, B., Aleti, A., Grunske, L.: Architecture-driven reliability and energy optimization for complex embedded systems. In: Proceedings of the 6th International Conference on Quality of Software Architectures: Research into Practice—Reality and Gaps, QoSA’10, pp. 52–67 (2010)

  32. 32.

    Meedeniya, I., Buhnova, B., Aleti, A., Grunske, L.: Reliability-driven deployment optimization for embedded systems. J. Syst. Softw. 84(5), 835–846 (2011)

    Article  Google Scholar 

  33. 33.

    Meedeniya, I., Moser, I., Aleti, A., Grunske, L.: Architecture-based reliability evaluation under uncertainty. In: Proceedings of the Joint ACM SIGSOFT Conference—QoSA and Symposium—ISARCS on Quality of Software Architectures, QoSA-ISARCS ’11, pp. 85–94 (2011)

  34. 34.

    Montgomery, J., Moser, I.: Parallel constraint handling in a multiobjective evolutionary algorithm for the automotive deployment problem. In: 6th IEEE International Conference on e-Science Workshops, 2010, pp. 104–109 (2010)

  35. 35.

    Murashkin, A.: Automotive electronic/electric architecture modeling, design exploration and optimization using Clafer. Master’s thesis, University of Waterloo (2014).

  36. 36.

    Murashkin, A., Antkiewicz, M., Rayside, D., Czarnecki, K.: Visualization and exploration of optimal variants in product line engineering. In: Software Product Line Conference (2013)

  37. 37.

    Nicholson, M., Burns, A., Dd, Y.: Emergence of an architectural topology for safety-critical real-time systems (1997)

  38. 38.

    Prud’homme, C., Fages, J.G., Lorca, X.: Choco3 Documentation. TASC, INRIA Rennes, LINA CNRS UMR 6241, COSLING S.A.S. (2014). Last accessed 21 Feb 2017

  39. 39.

    Ross, J., Antkiewicz, M., Czarnecki, K.: Case studies on E/E architectures for power window and central door locks systems (2016).

  40. 40.

    Schäuffele, J.: E/e architectural design and optimization using preevision. Tech. rep, SAE Technical Paper (2016)

  41. 41.

    Voss, S., Eder, J., Schaetz, B. (eds.).: Scheduling Synthesis for Multi-Period SW Components. SAE Technical Paper 2016-01-0012 (2016). doi:10.4271/2016-01-0012

  42. 42.

    Voss, S., Schatz, B.: Deployment and scheduling synthesis for mixed-critical shared-memory applications. In: 20th IEEE International Conference and Workshops on the Engineering of Computer Based Systems (ECBS), 2013, pp. 100–109 (2013)

  43. 43.

    Zeller, M., Prehofer, C.: Modeling and efficient solving of extra-functional properties for adaptation in networked embedded real-time systems. J. Syst. Archit. 59(10), 1067–1082 (2013)

    Article  Google Scholar 

Download references

Author information



Corresponding author

Correspondence to Jordan A. Ross.

Additional information

Communicated by Prof. Hong Mei.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ross, J.A., Murashkin, A., Liang, J.H. et al. Synthesis and exploration of multi-level, multi-perspective architectures of automotive embedded systems. Softw Syst Model 18, 739–767 (2019).

Download citation


  • Architecture synthesis
  • Multi-level architectures
  • Multi-perspective architectures
  • E/E architecture
  • Architecture optimization
  • Candidate architectures
  • Early design