Axiomatising Divergence

  • Markus Lohrey
  • Pedro R. D’Argenio
  • Holger Hermanns
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2380)


This paper develops sound and complete axiomatisations for the divergence sensitive spectrum of weak bisimulation equivalence. The axiomatisations can be extended to a considerable fragment of the linear time - branching time spectrum with silent moves, partially solving an open problem posed in [5].


Equation System Free Variable Time Spectrum Open Expression Complete Axiomatisation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    L. Aceto and M. Hennessy. Termination, deadlock, and divergence. J. ACM, 39(1):147–187, 1992.MATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    J.C.M. Baeten and W.P. Weijland. Process Algebra. Cambridge Univ. Press, 1990.Google Scholar
  3. 3.
    J.A. Bergstra, J.W. Klop, and E.-R. Olderog. Failure semantics with fair abstraction. Report CS-R8609, CWI, Amsterdam, 1986.Google Scholar
  4. 4.
    R.J. van Glabbeek. The Linear Time-Branching Time Spectrum I. The semantics of concrete, sequential processes. Chapter 1 in Handbook of Process Algebra, pages 3–99, Elsevier, 2001.Google Scholar
  5. 5.
    R.J. van Glabbeek. The Linear Time-Branching Time Spectrum II. The semantics of sequential systems with silent moves (Extended Abstract). In Proc. CON-CUR’93, LNCS 715, pages 66–81. Springer, 1993.Google Scholar
  6. 6.
    R.J. van Glabbeek. A Complete Axiomatization for Branching Bisimulation Congruence of Finite-State Behaviours. In Proc. MFCS’93, LNCS 711, pages 473–484. Springer, 1993.Google Scholar
  7. 7.
    R.J. van Glabbeek and W.P. Weijland. Branching time and abstraction in bisimulation semantics. J. ACM, 43(3):555–600, 1996.CrossRefMathSciNetGoogle Scholar
  8. 8.
    H. Hermanns and M. Lohrey. Observational Congruence in a Stochastic Timed Calculus with Maximal Progress. Technical Report IMMDVII-7/97, University of Erlangen-Nürnberg, IMMD7, 1997.Google Scholar
  9. 9.
    R. Milner. A Complete Inference System for a Class of Regular Behaviours. J. Com-put. System Sci., 28:439–466, 1984.MATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    R. Milner. A Complete Axiomatisation for Observational Congruence of Finite-State Behaviours. Inf. Comp., 91(227–247), 1989.Google Scholar
  11. 11.
    D.J. Walker. Bisimulation and divergence. Inf. Comp., 85:202–241, 1990.MATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Markus Lohrey
    • 1
  • Pedro R. D’Argenio
    • 2
  • Holger Hermanns
    • 3
  1. 1.Institut für InformatikUniversität StuttgartStuttgartGermany
  2. 2.FaMAFUniversidad Nacional de CórdobaCórdobaArgentina
  3. 3.Formal Methods and Tools Group, Faculty of Computer ScienceUniversity of TwenteEnschedeThe Netherlands

Personalised recommendations