Validating the Hybrid ERTMS/ETCS Level 3 Concept with Electrum

  • Alcino Cunha
  • Nuno MacedoEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10817)


This paper reports on the development of a formal model for the Hybrid ERTMS/ETCS Level 3 concept in Electrum, a lightweight formal specification language that extends Alloy with mutable relations and temporal logic operators. We show how Electrum and its Analyzer can be used to perform scenario exploration to validate this model, namely to check that all the example operational scenarios described in the reference document are admissible, and to reason about expected safety properties, which can be easily specified and model checked for arbitrary track configurations. The Analyzer depicts scenarios (and counter-examples) in a graphical notation that is logic-agnostic, making them understandable for stakeholders without expertise in formal specification.



The authors would like to thank David Chemouil for the support provided during the model checking of the model. This work is financed by the ERDF - European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 and by National Funds through the Portuguese funding agency, FCT - Fundaç\(\tilde{a}o\) para a Ciência e a Tecnologia within project POCI-01-0145-FEDER-016826.


  1. 1.
    Biere, A., Cimatti, A., Clarke, E.M., Strichman, O., Zhu, Y.: Bounded model checking. Adv. Comput. 58, 117–148 (2003)CrossRefGoogle Scholar
  2. 2.
    EEIG ERTMS Users Group: Hybrid ERTMS/ETCS Level 3 - Principles (2017)Google Scholar
  3. 3.
    INESC TEC, ONERA: Electrum Analyzer, v1.0. Available Under the MIT License (2018).
  4. 4.
    Jackson, D.: Software Abstractions: Logic, Language, and Analysis. MIT Press, Cambridge (2012). revised ednGoogle Scholar
  5. 5.
    Macedo, N., Brunel, J., Chemouil, D., Cunha, A., Kuperberg, D.: Lightweight specification and analysis of dynamic systems with rich configurations. In: SIGSOFT FSE. pp. 373–383. ACM (2016)Google Scholar
  6. 6.
    Macedo, N., Cunha, A., Pessoa, E.: Exploiting partial knowledge for efficient model analysis. In: D’Souza, D., Narayan Kumar, K. (eds.) ATVA 2017. LNCS, vol. 10482, pp. 344–362. Springer, Cham (2017). Scholar
  7. 7.
    Moreira, J.M., Cunha, A., Macedo, N.: An ORCID based synchronization framework for a national CRIS ecosystem. F1000Research 4(181) (2015)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.INESC TEC & Universidade do MinhoBragaPortugal

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