Analysis and re-configuration of decision logic in adaptive and data-intensive processes (Short paper)

Abstract

Decision logic related to business processes can be specified with decision tables. Current approaches analyze decision tables in isolation without considering the dependencies with other tables, related tasks, and data flows. This paper presents an approach to integrate data flows with DMN and BPMN models in adaptive and data-intensive processes. We use feature modeling to specify interdependencies among decision logic models in one or multiple business process tasks. We created a constraint-based algorithm that encodes the feature-based specification and propagates decisions among decision logic models according to the process data flow. Therefore, an integrated process model can be configured and its data flow integrity can be guaranteed during process execution.