This paper proposes to improve compositional nonblocking verification of discrete event systems through the use of special events. Compositional verification involves abstraction to simplify parts of a system during verification. Normally, this abstraction is based on the set of events not used in the remainder of the system, i. e., in the part of the system not being simplified. Here, it is proposed to exploit more knowledge about the remainder of the system and check how events are being used. Always enabled events, selfloop-only events, failing events, and blocked events are easy to detect and often help with simplification even though they are used in the remainder of the system. Abstraction rules from previous work are generalised, and experimental results demonstrate the applicability of the resulting algorithm to verify several industrial-scale discrete event system models, while achieving better state-space reduction than before.

This report proposes to improve compositional nonblocking verification through the use of two special event types: always enabled and selfloop-only events. Compositional verification involves abstraction to simplify parts of a system during verification. Normally, this abstraction is based on the set of events not used in the remainder of the system. Here, it is proposed to exploit more knowledge about the system and abstract events even though they are used in the remainder of the system. This can lead to more simplification than was previously possible. Abstraction rules from previous work are extended to respect the new special events and proofs show these rules still preserve nonblocking. The rules have been implemented in Waters and experimental results demonstrate that these extended simplification rules help verify several industrial-scale discrete event system models while achieving better state-space reduction than before.2

We talk in this paper about using state machines and refinement to characterise the visualisation of a computation. We use Z specifications to give examples of systems in the usual way, and then use Z schemas to also represent states and transitions in state machines, which we consider to be a particular kind of visualisation of a specified system. We have investigated the principle of substitutivity and the idea of downward simulation to check whether or not a refinement relation exists between the specification and the state machine. We are looking at this because we believe that the soundness of the visualisation can be captured by such a refinement relationship.

For validation or for communication with a client, it is useful to create a visualisation of a specification. It is important that the visualisation does not mislead the user. In this work we look at how to characterise the conditions for a micro-chart visualisation to be sound. This is done by introducing a new operator to the micro-chart semantics, allowing us to use Z data refinement to find a refinement relation between a Z specification and its (claimed sound) micro-chart visualisation. If the relation does not hold, then the visualisation is not sound.

Abstract-For validation or for communication with a client, it is useful to create a visualisation of a specification. It is important that the visualisation does not mislead the user. In this work we look at how to characterise the conditions for a micro-chart visualisation to be sound. This is done by introducing a new operator to the micro-chart semantics, allowing us to use Z data refinement to find a refinement relation between a Z specification and its (claimed sound) micro-chart visualisation. If the relation does not hold, then the visualisation is not sound.