Diagnosing behavioral differences between business process models: An approach based on event structures

摘要

Companies operating in multiple markets or segments often need to manage multiple variants of the same business process. Such multiplicity may stem for example from distinct products, different types of customers or regulatory differences across countries in which the companies operate. During the management of these processes, analysts need to compare models of multiple process variants in order to identify opportunities for standardization or to understand performance differences across variants. To support this comparison, this paper proposes a technique for diagnosing behavioral differences between process models. Given two process models, it determines if they are behaviorally equivalent, and if not, it describes their differences in terms of behavioral relations – like causal dependencies or conflicts – that hold in one model but not in the other. The technique is based on a translation from process models to event structures, a formalism that describes the behavior as a collection of events (task instances) connected by binary behavioral relations. A naïve version of this translation suffers from two limitations. First, it produces redundant difference statements because an event structure describing a process may contain unnecessary event duplications. Second, this translation is not directly applicable to process models with cycles as the corresponding event structure is infinite. To tackle the first issue, the paper proposes a technique for reducing the number of events in an event structure while preserving the behavior. For the second issue, relying on the theory of complete unfolding prefixes, the paper shows how to construct a finite prefix of the unfolding of a possibly cyclic process model where all possible causes of every activity is represented. Additionally, activities that can occur multiple times in an execution of the process are distinguished from those that can occur at most once. The finite prefix thus enables the diagnosis of behavioral differences in terms of activity repetition and causal relations that hold in one model but not in the other. The method is implemented as a prototype that takes as input process models in the Business Process Model and Notation (BPMN) and produces difference statements in natural language. Differences can also be graphically overlaid on the process models.