Mixing paradigms for more comprehensible models

Abstract

Petri nets efficiently model both data- and control-flow. Control-flow is either modeled explicitly as flow of a specific kind of data, or implicit based on the data-flow. Explicit modeling of control-flow is useful for well-known and highly structured processes, but may make modeling of abstract features of models, or processes which are highly dynamic, overly complex. Declarative modeling, such as is supported by Declare and DCR graphs, focus on control-flow, but does not specify it explicitly; instead specifications come in the form of constraints on the order or appearance of tasks. In this paper we propose a combination of the two, using colored Petri nets instead of plain Petri nets to provide full data support. The combined approach makes it possible to add a focus on data to declarative languages, and to remove focus from the explicit control-flow from Petri nets for dynamic or abstract processes. In addition to enriching both procedural processes in the form of Petri nets and declarative processes, we also support a flow from modeling only abstract data- and control-flow of a model towards a more explicit control-flow model if so desired. We define our combined approach, and provide considerations necessary for enactment. Our approach has been implemented in CPN Tools 4. © 2013 Springer-Verlag.