Clone detection in repositories of business process models

Abstract

Abstract. As organizations reach to higher levels of business process manage-ment maturity, they often find themselves maintaining repositories of hundreds or even thousands of process models, representing valuable knowledge about their operations. Over time, process model repositories tend to accumulate duplicate fragments (also called clones) as new process models are created or extended by copying and merging fragments from other models. This calls for methods to de-tect clones in process models, so that these clones can be refactored as separate subprocesses in order to improve maintainability. This paper presents an indexing structure to support the fast detection of clones in large process model reposito-ries. The proposed index is based on a novel combination of a method for process model decomposition (specifically the Refined Process Structure Tree), with es-tablished graph canonization and string matching techniques. Experiments show that the algorithm scales to repositories with hundreds of models. The experimen-tal results also show that a significant number of non-trivial clones can be found in process model repositories taken from industrial practice. 1