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