Technical Report: Refining Case Models Using Cardinality Constraints
This work provides an incremental improvement for business process management practitioners dealing with semi-structured, knowledge-intensive processes by better handling data object cardinalities.
This paper addresses the limitation of existing knowledge-intensive business process models in handling data object cardinalities. It extends an existing case management approach to incorporate data object associations and cardinality constraints, leading to refined data access semantics and synchronized processing of multiple data objects.
Traditionally, business process management focuses on structured, imperative processes. With the increasing importance of knowledge work, semi-structured processes are entering center stage. Existing approaches to modeling knowledge-intensive business processes use data objects but fail to sufficiently take into account data object cardinalities. Hence, they cannot guarantee that cardinality constraints are respected, nor use such constraints to handle concurrency and multiple activity instances during execution. This paper extends an existing case management approach with data object associations and cardinality constraints. The results facilitate a refined data access semantics, lower and upper bounds for process activities, and synchronized processing of multiple data objects. The execution semantics is formally specified using colored Petri nets. The effectiveness of the approach is shown by a compiler translating case models to colored Petri nets and by a dedicated process execution engine.