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
