Automated attribute inference in complex service workflows based on sharing analysis

Abstract

The properties of data and activities in workflows can be used to greatly facilitate several relevant tasks performed at design- and run-time, such as fragmentation, conformance checking, or top-down design. We present an approach to mechanically infer domain attributes of workflow components, such as data items, activities, or elements of sub-workflows, based on basic characteristics of workflow inputs, the structure of the workflow, and the results of 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. As Service-Oriented Computing is quite often used to implement workflows, we relate the techniques we present with the technologies and approach taken by SOC.