Unfolding-based diagnosis of systems with an evolving topology

  • Authors:

  • Paolo Baldan;Thomas Chatain;Stefan Haar;Barbara König

  • Affiliations:

  • Dipartimento di Matematica Pura e Applicata, Università di Padova, Italy;LSV, CNRS & ENS de Cachan, INRIA, France;LSV, CNRS & ENS de Cachan, INRIA, France;Abteilung für Informatik und Angewandte Kognitionswissenschaft, Universität Duisburg-Essen, Germany

  • Venue:
  • Information and Computation
  • Year:
  • 2010

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Abstract

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 should hence be easily applicable to a wide class of system models, including graph grammars and Petri nets.