Discovering models of behavior for concurrent workflows

Understanding the dynamic behavior of a workflow is crucial for being able to modify, maintain, and improve it. A particularly difficult aspect of some behavior is concurrency. Automated techniques which seek to mine workflow data logs to discover information about the workflows must be able to handle the concurrency that manifests itself in the workflow executions. This paper presents techniques to discover patterns of concurrent behavior from traces of workflow events. The techniques are based on a probabilistic analysis of the event traces. Using metrics for the number, frequency, and regularity of event occurrences, a determination is made of the likely concurrent behavior being manifested by the system. Discovering this behavior can help a workflow designer better understand and improve the work processes they are managing. (C) 2003 Elsevier B.V. All rights reserved.