Scalable Hybrid Variability for Distributed Evolving Software Systems
  • Thomas Brox RøstEmail author
  • Christoph Seidl
  • Ingrid Chieh Yu
  • Ferruccio Damiani
  • Einar Broch Johnsen
  • Cristina Chesta
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 824)


The HyVar project ( proposes a development framework for continuous and individualized evolution of distributed software applications running on remote devices in heterogeneous environments, focusing on the automotive domain. The framework combines variability modeling and software reuse from software product lines with formal methods and software upgrades and can be integrated in existing software development processes. HyVar’s objectives are: (O1) To develop a Domain Specific Variability Language (DSVL) and tool chain to support software variability for highly distributed applications; (O2) to develop a cloud infrastructure that exploits software variability as described in the DSVL to track the software configurations deployed on remote devices and to enable (i) the collection of data from the devices to monitor their behavior; and (ii) secure and efficient customized updates; (O3) to develop a technology for over-the-air updates of distributed applications, which enables continuous software evolution after deployment on complex remote devices that incorporate a system of systems; and (O4) to test HyVar’s approach as described in the above objectives in an industry-led demonstrator to assess in quantifiable ways its benefits. The end of the project is approaching and we are close to reaching all the objectives. In this paper, we present the integrated tool chain, which combines formal reuse through software product lines with commonly used industrial practices, and supports the development and deployment of individualized software adaptations. We also describe the main benefits for the stakeholders involved.


Software engineering Software maintenance Software evolution Software product lines Variability models Distributed software Over-the-air updates Data intensive systems Internet of things Cloud computing 


  1. 1.
    Chesta, C., Damiani, F., Dobriakova, L., Guernieri, M., Martini, S., Nieke, M., Rodrigues, V., Schuster, S.: A toolchain for delta-oriented modeling of software product lines. In: Margaria, T., Steffen, B. (eds.) ISoLA 2016. LNCS, vol. 9953, pp. 497–511. Springer, Cham (2016). Scholar
  2. 2.
    Nieke, N., Engel, G., Seidl. C.: DarwinSPL: an integrated tool suite for modeling evolving context-aware software product lines. In: ter Beek, M.H., Siegmund, N., Schaefer, I. (eds.) Proceedings of the Eleventh International Workshop on Variability Modelling of Software-intensive Systems (VAMOS 2017), pp. 92–99. ACM (2017).
  3. 3.
    Damiani, F., Lienhardt, M., Paolini, L.: A formal model for multi SPLs. In: Dastani, M., Sirjani, M. (eds.) FSEN 2017. LNCS, vol. 10522, pp. 67–83. Springer, Cham (2017). Scholar
  4. 4.
    Wille, D., Schulze, S., Seidl, C., Schaefer, I.: Custom-tailored variability mining for block-based languages. In: Proceedings of the International Conference on Software Analysis, Evolution, and Reengineering (SANER 2016). IEEE (2016).
  5. 5.
    Mauro, J., Nieke,, N., Seidl, C., Chieh Yu, I.: Context aware reconfiguration in software product lines. In: Schaefer, I., Alves, V., de Almeida, E.S. (eds.) Proceedings of the Tenth International Workshop on Variability Modelling of Software-intensive Systems (VaMoS 2016), pp. 41–48. ACM (2016).

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Atbrox ASTrondheimNorway
  2. 2.Technische Universität BraunschweigBraunschweigGermany
  3. 3.Universitetet i OsloOsloNorway
  4. 4.Università di TorinoTurinItaly
  5. 5.Santer Reply SpATurinItaly

Personalised recommendations