Reveal Your Faults: It's Only Fair!

We present a methodology for fault diagnosis in concurrent, partially observable systems with additional fairness constraints. In this weak diagnosis, one asks whether a concurrent chronicle of observed events allows to determine that a non-observable fault will inevitably occur, sooner or later, on any maximal system run compatible with the observation. The approach builds on strengths and techniques of unfoldings of safe Petri nets, striving to compute a compact prefix of the unfolding that carries sufficient information for the diagnosis algorithm. Our work extends and generalizes the unfolding-based diagnosis approaches by Benveniste et al. [1] as well as Esparza and Kern [2]. Both of these focused mostly on the use of sequential observations, in particular did not exploit the capacity of unfoldings to reveal inevitable occurrences of concurrent or future events studied by Balaguer et al. [3]. Our diagnosis method captures such indirect, revealed dependencies. We develop theoretical foundations and an algorithmic solution to the diagnosis problem, and present a SAT solving method for practical diagnosis with our approach.