Unfolding-Based Diagnosis of Systems with an Evolving Topology

  • Paolo Baldan
  • Thomas Chatain
  • Stefan Haar
  • Barbara König
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5201)


We propose a framework for model-based diagnosis of systems with mobility and variable topologies, modelled as graph transformation systems. Generally speaking, model-based diagnosis is aimed at constructing explanations of observed faulty behaviours on the basis of a given model of the system. Since the number of possible explanations may be huge we exploit the unfolding as a compact data structure to store them, along the lines of previous work dealing with Petri net models. Given a model of a system and an observation, the explanations can be constructed by unfolding the model constrained by the observation, and then removing incomplete explanations in a pruning phase. The theory is formalised in a general categorical setting: constraining the system by the observation corresponds to taking a product in the chosen category of graph grammars, so that the correctness of the procedure can be proved by using the fact that the unfolding is a right adjoint and thus it preserves products. The theory thus should be easily applicable to a wide class of system models, including graph grammars and Petri nets.


Discrete Event System Type Graph Graph Grammar Variable Topology Typing Morphism 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Paolo Baldan
    • 1
  • Thomas Chatain
    • 2
  • Stefan Haar
    • 3
  • Barbara König
    • 4
  1. 1.Dipartimento di Matematica Pura e ApplicataUniversità di PadovaItaly
  2. 2.LSV, ENS Cachan, CNRS, INRIAFrance
  3. 3.INRIA, France, and University of OttawaCanada
  4. 4.Abteilung für Informatik und Angewandte KognitionswissenschaftUniversität Duisburg-EssenGermany

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