Exploring Applications of Formal Methods in the INSPEX Project

  • Joseph Razavi
  • Richard Banach
  • Olivier Debicki
  • Nicolas Mareau
  • Suzanne Lesecq
  • Julie Foucault
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11176)


As formal methods become increasingly practical, there is a need to explore their use in a variety of domains. Wearable sensing is a rapidly developing area in which formal methods can provide tangible benefits to end users, facilitating the advance of cutting-edge technology where consumer trust is critical. The INSPEX project aims to develop a miniaturized spatial exploration system incorporating multiple sensors and state of the art processing, initially focused on a navigation tool for visually impaired people. It is thus a useful test-case for formal methods in this domain. Applying formal methods in the INSPEX development process entailed adapting to realistic external pressures. The impact of these on the modelling process is described, attending in particular to the relationship between human and tool-supported reasoning.



Open image in new window This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 730953. The work was also supported in part by the Swiss Secretariat for Education, Research and Innovation (SERI) under Grant 16.0136 730953. We thank them for their support.


  1. 1.
    Abrial, J.R.: Formal methods in industry: achievements, problems future. In: Proceedings ACM/IEEE ICSE 2006, pp. 761–768 (2006)Google Scholar
  2. 2.
    Abrial, J.R.: Modeling in Event-B: System and Software Engineering. CUP (2010)Google Scholar
  3. 3.
    Banach, R. (ed.): Special issue on the state of the art in formal methods. J. Univ. Comput. Sci. 13(5) (2007)Google Scholar
  4. 4.
    Barnes, J.E.: Experiences in the industrial use of formal methods. Electron. Commun. EASST 46 (2011)Google Scholar
  5. 5.
  6. 6.
  7. 7.
    Bowen, J., Hinchey, M.: Seven more Myths of formal methods. IEEE Softw. 12, 34–41 (1995)CrossRefGoogle Scholar
  8. 8.
    Braude, E., Bernstein, M.: Software Engineering: Modern Approaches. Wiley, Hoboken (2011)Google Scholar
  9. 9.
    Déharbe, D., Fontaine, P., Guyot, Y., Voisin, L.: SMT solvers for Rodin. In: Derrick, J., et al. (eds.) ABZ 2012. LNCS, vol. 7316, pp. 194–207. Springer, Heidelberg (2012). Scholar
  10. 10.
    Divakaran, S., D’Souza, D., Kushwah, A., Sampath, P., Sridhar, N., Woodcock, J.: Refinement-based verification of the FreeRTOS Scheduler in VCC. In: Butler, M., Conchon, S., Zaïdi, F. (eds.) ICFEM 2015. LNCS, vol. 9407, pp. 170–186. Springer, Cham (2015). Scholar
  11. 11.
  12. 12.
    Salehi Fathabadi, A., Butler, M., Rezazadeh, A.: A Systematic approach to atomicity decomposition in Event-B. In: Eleftherakis, G., Hinchey, M., Holcombe, M. (eds.) SEFM 2012. LNCS, vol. 7504, pp. 78–93. Springer, Heidelberg (2012). Scholar
  13. 13.
    FreeRTOS: (2017).
  14. 14.
    Hall, A.: Seven Myths of formal methods. IEEE Softw. 7, 11–19 (1990)CrossRefGoogle Scholar
  15. 15.
    Hall, D.: Mathematical Techniques in Multisensor Data Fusion. Artech House, Norwood (2004)zbMATHGoogle Scholar
  16. 16.
    Harrison, J.: Formal proof—theory and practice. Not. AMS 55, 1395–1406 (2008)MathSciNetzbMATHGoogle Scholar
  17. 17.
  18. 18.
    INSPEX Homepage: (2017).
  19. 19.
    Kedem, B., De Oliveira, V., Sverchkov, M.: Statistical Data Fusion. World Scientific, Singapore (2017)CrossRefGoogle Scholar
  20. 20.
    Meyer, B.: How you will be programming ten years from now. In: ACM SAC-10 Keynote (2010)Google Scholar
  21. 21.
    Moravec, H., Elfes, A.: High resolution maps from wide angle sonar. In: Proceedings IEEE ICRA (1985)Google Scholar
  22. 22.
    Pratt, V.: Anatomy of the Pentium bug. In: Mosses, P.D., Nielsen, M., Schwartzbach, M.I. (eds.) CAAP 1995. LNCS, vol. 915, pp. 97–107. Springer, Heidelberg (1995). Scholar
  23. 23.
    Pressman, R.: Software Engineering: A Practitioner’s Approach. McGraw Hill, New York City (2005)zbMATHGoogle Scholar
  24. 24.
  25. 25.
  26. 26.
  27. 27.
    Scalise, L., Primiani, V., Russo, P.: Experimental investigation of electromagnetic obstacle detection for visually impaired users: a comparison with ultrasonic sensing. IEEE Trans. Inst. Meas. 61, 3047–3057 (2012)CrossRefGoogle Scholar
  28. 28.
  29. 29.
    Sommerville, I.: Software Engineering. Pearson, London (2015)zbMATHGoogle Scholar
  30. 30.
    Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics. MIT Press, Cambridge (2005)zbMATHGoogle Scholar
  31. 31.
    Ultracane: (2017).
  32. 32.
    Verhoef, M.: From documents to models: towards digital continuity. In: SAFECOMP/IMBSA-17 Keynote.

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Joseph Razavi
    • 1
  • Richard Banach
    • 1
  • Olivier Debicki
    • 2
  • Nicolas Mareau
    • 2
  • Suzanne Lesecq
    • 2
  • Julie Foucault
    • 2
  1. 1.School of Computer ScienceUniversity of ManchesterManchesterUK
  2. 2.Commissariat à l’Énergie Atomique et aux Énergies Alternatives, MINATEC CampusGrenoble CedexFrance

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