Fast detection of exact clones in business process model repositories

Dumas, Marlon, Garcia-Banuelos, Luciano, La Rosa, Marcello, & Uba, Reina (2013) Fast detection of exact clones in business process model repositories. Information Systems, 38(4), pp. 619-633.

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As organizations reach higher levels of business process management maturity, they often find themselves maintaining very large process model repositories, representing valuable knowledge about their operations. A common practice within these repositories is to create new process models, or extend existing ones, by copying and merging fragments from other models. We contend that if these duplicate fragments, a.k.a. ex- act clones, can be identified and factored out as shared subprocesses, the repository’s maintainability can be greatly improved. With this purpose in mind, we propose an indexing structure to support fast detection of clones in process model repositories. Moreover, we show how this index can be used to efficiently query a process model repository for fragments. This index, called RPSDAG, is based on a novel combination of a method for process model decomposition (namely the Refined Process Structure Tree), with established graph canonization and string matching techniques. We evaluated the RPSDAG with large process model repositories from industrial practice. The experiments show that a significant number of non-trivial clones can be efficiently found in such repositories, and that fragment queries can be handled efficiently.

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17 citations in Scopus
11 citations in Web of Science®
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ID Code: 49408
Item Type: Journal Article
Refereed: Yes
Keywords: clone, process model, exact match, index
DOI: 10.1016/
ISSN: 0306-4379
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > DATA FORMAT (080400) > Data Structures (080403)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)
Divisions: Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 Elsevier
Copyright Statement: This is the author’s version of a work that was accepted for publication in Information Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Information Systems, [VOL 38, ISSUE 4, (2013)] DOI: 10.1016/
Deposited On: 28 Mar 2012 22:01
Last Modified: 07 Sep 2016 03:46

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