Detecting approximate clones in business process model repositories

La Rosa, Marcello, Dumas, Marlon, Ekanayake, Chathura C., García-Bañuelos, Luciano, Recker, Jan C., & ter Hofstede, Arthur H.M. (2015) Detecting approximate clones in business process model repositories. Information Systems, 49, pp. 102-125.

View at publisher


Empirical evidence shows that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication arises for example when the repository covers multiple variants of the same processes or due to copy-pasting. Previous work has addressed the problem of efficiently retrieving exact clones that can be refactored into shared subprocess models. This article studies the broader problem of approximate clone detection in process models. The article proposes techniques for detecting clusters of approximate clones based on two well-known clustering algorithms: DBSCAN and Hi- erarchical Agglomerative Clustering (HAC). The article also defines a measure of standardizability of an approximate clone cluster, meaning the potential benefit of replacing the approximate clones with a single standardized subprocess. Experiments show that both techniques, in conjunction with the proposed standardizability measure, accurately retrieve clusters of approximate clones that originate from copy-pasting followed by independent modifications to the copied fragments. Additional experiments show that both techniques produce clusters that match those produced by human subjects and that are perceived to be standardizable.

Impact and interest:

7 citations in Scopus
6 citations in Web of Science®
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

5 since deposited on 27 Oct 2014
2 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 78047
Item Type: Journal Article
Refereed: Yes
Keywords: business process model, clone detection, model collection, repository, standardization
DOI: 10.1016/
ISSN: 0306-4379
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Decision Support and Group Support Systems (080605)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600) > Information Systems Development Methodologies (080608)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Current > Schools > School of Information Systems
Copyright Owner: Copyright 2014 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, Volume 49, (April 2015), DOI: 10.1016/
Deposited On: 27 Oct 2014 22:10
Last Modified: 06 May 2017 07:07

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page