Conflict-preserving abstraction of discrete event systems using annotated automata

This paper proposes to enhance compositional verification of the nonblocking property of discrete event systems by introducing annotated automata. Annotations store nondeterministic branching information, which would otherwise be stored in extra states and transitions. This succinct representation makes it easier to simplify automata and enables new efficientmeans of abstraction, reducing the size of automata to be composed and thus the size of the synchronous product state space encountered in verification. The abstractions proposed are of polynomial complexity, and they have been successfully applied to model check the nonblocking property of the same set of large-scale industrial examples as used in related work

Transforming opacity verification to nonblocking verification in modular systems

We consider the verification of current-state and K-step opacity for systems modeled as interacting non-deterministic finite-state automata. We describe a new methodology for compositional opacity verification that employs abstraction, in the form of a notion called opaque observation equivalence, and that leverages existing compositional nonblocking verification algorithms. The compositional approach is based on a transformation of the system, where the transformed system is nonblocking if and only if the original one is current-state opaque. Furthermore, we prove that $K$-step opacity can also be inferred if the transformed system is nonblocking. We provide experimental results where current-state opacity is verified efficiently for a large scaled-up system

On Compositional Approaches for Discrete Event Systems Verification and Synthesis

Over the past decades, human dependability on technical devices has rapidly increased.Many activities of such devices can be described by sequences of events,where the occurrence of an event causes the system to go from one state to another.This is elegantly modelled by state machines. Systems that are modelledin this way are referred to as discrete event systems. Usually, these systems arehighly complex, and appear in settings that are safety critical, where small failuresmay result in huge financial and/or human losses. Having a control functionis one way to guarantee system correctness.The work presented in this thesis concerns verification and synthesis of suchsystems using the supervisory control theory proposed by Ramadge and Wonham. Supervisory control theory provides a general framework to automaticallycalculate control functions for discrete event systems. Given a model of thesystem, the plant to be controlled, and a specification of the desired behaviour,it is possible to automatically compute, i.e. synthesise, a supervisor that ensuresthat the specification is satisfied.Usually, systems are modular and consist of several components interactingwith each other. Calculating a supervisor for such a system in the straightforwardway involves constructing the complete model of the considered system, whichmay lead to the inherent complexity problem known as the state-space explosionproblem. This problem occurs as the number of states grows exponentially withthe number of components, which makes it intractable to examine the globalstates of a system due to lack of memory and time.One way to alleviate the state-space explosion problem is to use a compositionalapproach. A compositional approach exploits the modular structure of asystem to reduce the size of the model. This thesis mainly focuses on developingabstraction methods for the compositional approach in a way that the finalverification and synthesis results are the same as it would have been for the nonabstractedsystem. The algorithms have been implemented in the discrete eventsystem software tool Supremica and have been applied to verify and computememory efficient supervisors for several large industrial models

On Compositional Approaches for Discrete Event Systems Verification and Synthesis

Over the past decades, human dependability on technical devices has rapidly increased.Many activities of such devices can be described by sequences of events,where the occurrence of an event causes the system to go from one state to another.This is elegantly modelled by state machines. Systems that are modelledin this way are referred to as discrete event systems. Usually, these systems arehighly complex, and appear in settings that are safety critical, where small failuresmay result in huge financial and/or human losses. Having a control functionis one way to guarantee system correctness.The work presented in this thesis concerns verification and synthesis of suchsystems using the supervisory control theory proposed by Ramadge and Wonham. Supervisory control theory provides a general framework to automaticallycalculate control functions for discrete event systems. Given a model of thesystem, the plant to be controlled, and a specification of the desired behaviour,it is possible to automatically compute, i.e. synthesise, a supervisor that ensuresthat the specification is satisfied.Usually, systems are modular and consist of several components interactingwith each other. Calculating a supervisor for such a system in the straightforwardway involves constructing the complete model of the considered system, whichmay lead to the inherent complexity problem known as the state-space explosionproblem. This problem occurs as the number of states grows exponentially withthe number of components, which makes it intractable to examine the globalstates of a system due to lack of memory and time.One way to alleviate the state-space explosion problem is to use a compositionalapproach. A compositional approach exploits the modular structure of asystem to reduce the size of the model. This thesis mainly focuses on developingabstraction methods for the compositional approach in a way that the finalverification and synthesis results are the same as it would have been for the nonabstractedsystem. The algorithms have been implemented in the discrete eventsystem software tool Supremica and have been applied to verify and computememory efficient supervisors for several large industrial models