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Should I Stay or Should I Go? On Forces that Drive and Prevent MBSE Adoption in the Embedded Systems Industry

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Product-Focused Software Process Improvement (PROFES 2017)

Abstract

[Context] Model-based Systems Engineering (MBSE) comprises a set of models and techniques that is often suggested as solution to cope with the challenges of engineering complex systems. Although many practitioners agree with the arguments on the potential benefits of the techniques, companies struggle with the adoption of MBSE. [Goal] In this paper, we investigate the forces that prevent or impede the adoption of MBSE in companies that develop embedded software systems. We contrast the hindering forces with issues and challenges that drive these companies towards introducing MBSE. [Method] Our results are based on 20 interviews with experts from 10 companies. Through exploratory research, we analyze the results by means of thematic coding. [Results] Forces that prevent MBSE adoption mainly relate to immature tooling, uncertainty about the return-on-investment, and fears on migrating existing data and processes. On the other hand, MBSE adoption also has strong drivers and participants have high expectations mainly with respect to managing complexity, adhering to new regulations, and reducing costs. [Conclusions] We conclude that bad experiences and frustration about MBSE adoption originate from false or too high expectations. Nevertheless, companies should not underestimate the necessary efforts for convincing employees and addressing their anxiety.

The original version of this chapter has been revised. The title of the paper was incorrect and has been modified. The ORCIDs of the authors Andreas Vogelsang and Tiago Amorim have also been added. For detailed information please see the Erratum. The erratum to this chapter is available at https://doi.org/10.1007/978-3-319-69926-4_57

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Notes

  1. 1.

    https://spedit.in.tum.de/.

  2. 2.

    http://atlasti.com.

  3. 3.

    https://doi.org/10.6084/m9.figshare.5368453.

  4. 4.

    https://de.mathworks.com/products/simulink.html.

  5. 5.

    https://leanstack.com/science-of-how-customers-buy/.

  6. 6.

    http://jobstobedone.org.

References

  1. Aranda, J., Damian, D., Borici, A.: Transition to model-driven engineering. In: France, R.B., Kazmeier, J., Breu, R., Atkinson, C. (eds.) MODELS 2012. LNCS, vol. 7590, pp. 692–708. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33666-9_44

    Chapter  Google Scholar 

  2. Bauer, V., Vetrò, A.: Comparing reuse practices in two large software-producing companies. J. Syst. Soft. 117, 545–582 (2016)

    Article  Google Scholar 

  3. Böhm, W., Junker, M., Vogelsang, A., Teufl, S., Pinger, R., Rahn, K.: A formal systems engineering approach in practice: an experience report. In: International Workshop on Software Engineering Research and Industrial Practices (SER&IPs) (2014). 10.1145/2593850.2593856

  4. Bone, M., Cloutier, R.: The current state of model based systems engineering: results from the OMG SysML request for information 2009. In: CSER (2010)

    Google Scholar 

  5. Broy, M., Damm, W., Henkler, S., Pohl, K., Vogelsang, A., Weyer, T.: Introduction to the SPES modeling framework. In: Pohl, K., Hönninger, H., Achatz, R., Broy, M. (eds.) Model-Based Engineering of Embedded Systems, pp. 31–49. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  6. Bryman, A.: Social Research Methods. Oxford University Press, Oxford (2015)

    Google Scholar 

  7. Conner, D.R.: Managing at the Speed of Change. Random House, New York (1993)

    Google Scholar 

  8. Dresch, A., Lacerda, D.P., Antunes, J.A.V.: Design Science Research. Springer, Cham (2015)

    Google Scholar 

  9. Hohl, P., Münch, J., Schneider, K., Stupperich, M.: Forces that prevent agile adoption in the automotive domain. In: Abrahamsson, P., Jedlitschka, A., Nguyen Duc, A., Felderer, M., Amasaki, S., Mikkonen, T. (eds.) PROFES 2016. LNCS, vol. 10027, pp. 468–476. Springer, Cham (2016). 10.1007/978-3-319-49094-6_32

    Chapter  Google Scholar 

  10. Hutchinson, J., Rouncefield, M., Whittle, J.: Model-driven engineering practices in industry. In: ICSE (2011)

    Google Scholar 

  11. INCOSE: Systems engineering vision 2020 (2007)

    Google Scholar 

  12. Kuhn, A., Murphy, G.C., Thompson, C.A.: An exploratory study of forces and frictions affecting large-scale model-driven development. In: France, R.B., Kazmeier, J., Breu, R., Atkinson, C. (eds.) MODELS 2012. LNCS, vol. 7590, pp. 352–367. Springer, Heidelberg (2012). 10.1007/978-3-642-33666-9_23

    Chapter  Google Scholar 

  13. Maxwell, J.A.: Qualitative Research Design: An Interactive Approach, vol. 41. Sage publications, Thousand Oaks (2012)

    Google Scholar 

  14. Mohagheghi, P., Gilani, W., Stefanescu, A., Fernandez, M.A.: An empirical study of the state of the practice and acceptance of model-driven engineering in four industrial cases. Empirical Soft. Eng. 18(1), 89–116 (2013)

    Article  Google Scholar 

  15. Motamedian, B.: MBSE applicability analysis. Int. J. Sci. Eng. Res. 4(2) (2013)

    Google Scholar 

  16. Neuman, W.: Social Research Methods: Qualitative and Quantitative Approaches, 7th edn. Alpha Books, New York (2010)

    Google Scholar 

  17. Riungu-Kalliosaari, L., Mäkinen, S., Lwakatare, L.E., Tiihonen, J., Männistö, T.: DevOps adoption benefits and challenges in practice: a case study. In: Abrahamsson, P., Jedlitschka, A., Nguyen Duc, A., Felderer, M., Amasaki, S., Mikkonen, T. (eds.) PROFES 2016. LNCS, vol. 10027, pp. 590–597. Springer, Cham (2016). 10.1007/978-3-319-49094-6_44

    Chapter  Google Scholar 

  18. Runeson, P., Höst, M.: Guidelines for conducting and reporting case study research in software engineering. Empirical Soft. Eng. 14(2), 131–164 (2008)

    Article  Google Scholar 

  19. Schmitt, A., Diebold, P.: Why do we do software process improvement? In: Abrahamsson, P., Jedlitschka, A., Nguyen Duc, A., Felderer, M., Amasaki, S., Mikkonen, T. (eds.) PROFES 2016. LNCS, vol. 10027, pp. 360–367. Springer, Cham (2016). 10.1007/978-3-319-49094-6_23

    Chapter  Google Scholar 

  20. Shields, P., Rangarjan, N.: A Playbook for Research Methods: Integrating Conceptual Frameworks and Project Management. New Forums, Stillwater (2013)

    Google Scholar 

  21. Vogelsang, A., Eder, S., Hackenberg, G., Junker, M., Teufl, S.: Supporting concurrent development of requirements and architecture: a model-based approach. In: MODELSWARD (2014)

    Google Scholar 

  22. Vogelsang, A., Femmer, H., Winkler, C.: Systematic elicitation of mode models for multifunctional systems. In: International Requirements Engineering Conference (RE) (2015). 10.1109/RE.2015.7320447

  23. Weston, C., Gandell, T., Beauchamp, J., McAlpine, L., Wiseman, C., Beauchamp, C.: Analyzing interview data: the development and evolution of a coding system. Qual. Sociol. 24(3), 381–400 (2001)

    Article  Google Scholar 

  24. Whittle, J., Hutchinson, J., Rouncefield, M., Burden, H., Heldal, R.: A taxonomy of tool-related issues affecting the adoption of model-driven engineering. Soft. Syst. Model. 16(2), 313–331 (2017)

    Article  Google Scholar 

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Acknowledgements

This work was partly funded by the German Federal Ministry of Education and Research (BMBF), grant “SPEDiT, 01IS15058”.

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Correspondence to Andreas Vogelsang .

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Vogelsang, A., Amorim, T., Pudlitz, F., Gersing, P., Philipps, J. (2017). Should I Stay or Should I Go? On Forces that Drive and Prevent MBSE Adoption in the Embedded Systems Industry. In: Felderer, M., Méndez Fernández, D., Turhan, B., Kalinowski, M., Sarro, F., Winkler, D. (eds) Product-Focused Software Process Improvement. PROFES 2017. Lecture Notes in Computer Science(), vol 10611. Springer, Cham. https://doi.org/10.1007/978-3-319-69926-4_14

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  • DOI: https://doi.org/10.1007/978-3-319-69926-4_14

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