Article in Proceedings INPROC-2016-37

BibliographySkouradaki, Marigianna; Andrikopoulos, Vasilios; Kopp, Oliver; Leymann, Frank: RoSE: Reoccurring Structures Detection in BPMN 2.0 Process Model Collections.
In: OTM Confederated International Conferences ''On the Move to Meaningful Internet Systems".
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 263-281, english.
Springer International Publishing, October 18, 2016.
ISBN: 10.1007/978-3-319-48472-3_15.
Article in Proceedings (Conference Paper).
CR-SchemaD.2.9 (Software Engineering Management)
I.2.8 (Problem Solving, Control Methods, and Search)
F.2.2 (Nonnumerical Algorithms and Problems)
KeywordsBPMN 2.0; Process similarity; Graph matching; Structural similarity; Business process management

The detection of structural similarities of process models is frequently discussed in the literature. The state-of-the-art approaches for structural similarities of process models presume a known subgraph that is searched in a larger graph, and utilize behavioral and textual semantics to achieve their goal. In this paper we propose an approach to detect reoccurring structures in a collection of BPMN2.0 process models, without the knowledge of a subgraph to be searched, and by focusing solely on the structural characteristics of the process models. The proposed approach deals with the problems of subgraph isomorphism, frequent pattern discovery and maximum common subgraph isomorphism, which are mentioned as NP-hard in the literature. In this work we present a formal model and a novel algorithm for the detection of reoccurring structures in a collection of BPMN 2.0 process models. We then apply the algorithm to a collection of 1,806 real-world process models and provide a quantitative and qualitative analysis of the results.

Department(s)University of Stuttgart, Institute of Architecture of Application Systems
Entry dateOctober 30, 2016
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