KS-Diff: A Key Structure Based Difference Detection Method for Process Models

Abstract

Detecting difference between two process models is a recurrent operation in business process management. A process model has multiple features, such as structure, behavior, and resource. Most of the existing methods only focus on one feature, which results in the loss of information in terms of other features. To provide more information on process difference to users, this paper proposes KS-Diff which can detect both structural and behavioral differences between two process models. First, the process models are transformed into their corresponding task-based process structure trees (TPSTs). Then, the one-hot codes are used to encode all leaf nodes of TPST, and the non-leaf nodes are encoded by the combination of one-hot codes of their child nodes. Next, the common key structure of two process models is extracted based on the one-hot encoding. Finally, the structural and behavioral differences are extracted on the basis of this common key structure. The efficiency study is provided to show the efficiency of KS-Diff.