Causal message sequence charts

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)4703 LNCS166-18

Realizability of Dynamic MSC Languages

We introduce dynamic communicating automata (DCA), an extension of communicating finite-state machines that allows for dynamic creation of processes. Their behavior can be described as sets of message sequence charts (MSCs). We consider the realizability problem for DCA: given a dynamic MSC grammar (a high-level MSC specification), is there a DCA defining the same set of MSCs? We show that this problem is EXPTIME-complete. Moreover, we identify a class of realizable grammars that can be implemented by finite DCA

Oclets – scenario-based modeling with Petri nets

Abstract. Scenario-based specifications are used for modeling highlycomplex, distributed systems in terms of partial runs (scenarios) the system shall have. But it is difficult to derive an implementing, operational model from a given set of scenarios, especially if concepts like anti-scenarios which must not occur are used. In this paper, we present a novel model for scenario-based specifications with Petri nets including anti-scenarios; we provide an operational semantics for our model. 1 Operational semantics for scenario-based specifications The paradigm of scenarios is widely accepted in protocol specifications using message-sequence charts (MSCs); behavior of highly-complex distributed systems is decomposed into reasonably sized artifacts called scenarios. Some classes of MSC specifications can be transformed into Petri nets [7], but usually an implementation has to be checked against an MSC specification. Life-sequence charts (LSCs) [5] extend the MSC paradigm by adding behavioral preconditions, anti-scenarios, and annotations to scenarios and single actions for enforcin

Data and abstraction for scenario-based modeling with Petri nets

Scenario-based modeling is an approach for describing behaviors of a distributed system in terms of partial runs, called scenarios. Deriving an operational system from a set of scenarios is the main challenge that is typically addressed by either synthesizing system components or by providing operational semantics. Over the last years, several established scenario-based techniques have been adopted to Petri nets. Their adaptation allows for verifying scenario-based models and for synthesizing individual components from scenarios within one formal technique, by building on Petri net theory. However, current adaptations of scenarios face two limitations: a system modeler (1) cannot abstract from concrete behavior, and (2) cannot explicitly describe data in scenarios. This paper lifts these limitations for scenarios in the style of Live Sequence Charts (LSCs). We extend an existing model for scenarios, that features Petri net-based semantics, verification and synthesis techniques, and close the gap between LSCs and Petri nets further