A static change impact analysis approach based on metrics and visualizations to support the evolution of workflow repositories

In ever-changing business environments, organizations continuously refine their processes to benefit from and meet the constraints of new technology, new business rules, and new market requirements. Workflow management systems (WFMSs) support organizations in evolving their processes by providing them with technological mechanisms to design, enact, and monitor workflows. However, workflows repositories often grow and start to encompass a variety of interdependent workflows. Without appropriate tool support, keeping track of such interdependencies and staying aware of the impact of a change in a workflow schema becomes hard. Workflow designers are often blindsided by changes that end up inducing side- and ripple-effects. This poses threats to the reliability of the workflows and ultimately hampers the evolvability of the workflow repository as a whole. In this paper, the authors introduce a change impact analysis approach based on metrics and visualizations to support the evolution of workflow repositories. They implemented the approach and later integrated it as a module in the HP Operations Orchestration (HP OO) WFMS. The authors conducted an exploratory study in which they thoroughly analyzed the workflow repositories of 8 HP OO customers. They characterized the customer repositories from a change impact perspective and compared them against each other. The authors were able to spot the workflows with high change impact among thousands of workflows in each repository. They also found that while the out-of-the-box repository included in HP OO had 10 workflows with high change impact, customer repositories included 11 (+10%) to 35 (+250%) workflows with this same characteristic. This result indicates the extent to which customers should put additional effort in evolving their repositories. The authors' approach contributes to the body of knowledge on static workflow evolution and complements existing dynamic workflow evolution approaches. Their techniques also aim to help organizations build more flexible and reliable workflow repositories.