A Change-Sensitive Complexity Measurement for Business Process Models Based on Control Structure

Abstract

The analysis of the process model complexity has significant implications for the operation, maintenance, and optimization of processes. As process models consist of control structures with specific repetitive patterns, the complexity of the control structures often determines the process model complexity. While the existing methods for measuring the process model complexity consider most control structure complexity, some changes in branch structures cannot be reflected in the process model complexity. To address this issue, this paper considers the impact of the number and position of activities in branching structures on the process model complexity, distinguishes the connection forms between branch structures, and defines the complexity of the branching structures. We propose a new complexity measurement (CP) based on the control structures. The theoretical validity of CPs was confirmed using Weyuker’s properties, and the process structure variant model was used to experiment with its sensitivity. The findings indicate that the CP satisfies eight out of the nine properties proposed by Weyuker. Compared with the other complexity measurement methods of the process model, the CP is more sensitive to some structural changes in the process model. Therefore, when the structure of the process model changes, the CP reflects the changes in the process model complexity more accurately.