Automated Attribute Inference in Complex Service Workflows Based on Sharing Analysis

The properties of data and activities in business processes can be used to greatly facilitate several relevant tasks performed at design-and run-time, such as fragmentation, compliance checking, or top-down design. Business processes are often described using workflows, and we present an approach to mechanically infer business domain-specific attributes of workflow components, including data items, activities, and elements of sub-workflows, from known attributes of workflow inputs and the structure of the workflow by modeling these components as concepts and applying sharing analysis applied to a Horn clause representation of the workflow. The analysis is applicable to workflows featuring complex control and data dependencies, embedded control constructs, such as loops and branches, and embedded component services.