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Regular Paper

Unraveling Iterative Control Structures from Business Processes

Department of Computer and Information Science, University of Macau, Macau, China
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Abstract

Iterative control structures allow the repeated execution of tasks, activities or sub-processes according to the given conditions in a process model. Iterative control structures can significantly increase the risk of triggering temporal exceptions since activities within the scope of these control structures could be repeatedly executed until a predefined condition is met. In this paper, we propose two approaches to unravel iterative control structures from process models. The first approach unravels loops based on zero-one principle. The second approach unravels loops based on branching probabilities assigned at split gateways. The proposed methods can be used to unfold structured loops, nested loops and crossing loops. Since the unfolded model does not contain any iterative control structures, it can be used for further analysis by process designers during the modeling phase. The proposed methods are implemented based on workflow graphs, and therefore they are compatible with modeling languages such as Business Process Modelling Notation (BPMN). In the experiments, the execution behavior of unfolded process models is compared against the original models based on the concept of runs. Experimental results reveal that runs generated from the original models can be correctly executed in the unfolded BPMN models that do not contain any loops.

Keywords

business process managementiterative control structureunravellingzero-one principlebranching probability

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Journal of Computer Science and Technology
Volume 36 Issue 1,
January 2021
Pages 158-190
DOI: 10.1007/s11390-020-9516-3
Cite this article:
Si Y-W, Yung W-H. Unraveling Iterative Control Structures from Business Processes. Journal of Computer Science and Technology, 2021, 36(1): 158-190. https://doi.org/10.1007/s11390-020-9516-3

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Received: 26 February 2019
Accepted: 04 December 2020
Published: 05 January 2021
© Institute of Computing Technology, Chinese Academy of Sciences 2021
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