Rosa, Marcello La, Dumas, Marlon, Ekanayake, Chathura C., García-Bañuelos, Luciano, Recker, Jan C. ORCID: 0000-0002-2072-5792 and ter Hofstede, Arthur H.M. (2015). Detecting approximate clones in business process model repositories. Information systems : IS ; an international journal ; data bases, 49. pp. 102-125. ISSN 0306-4379

Full text not available from this repository.
Link to the document: https://eprints.qut.edu.au/78047/

Abstract

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.

Item Type: Journal Article
Creators:
CreatorsEmailORCID
Rosa, Marcello LaUNSPECIFIEDUNSPECIFIED
Dumas, MarlonUNSPECIFIEDUNSPECIFIED
Ekanayake, Chathura C.UNSPECIFIEDUNSPECIFIED
García-Bañuelos, LucianoUNSPECIFIEDUNSPECIFIED
Recker, Jan C.UNSPECIFIEDorcid.org/0000-0002-2072-5792
ter Hofstede, Arthur H.M.UNSPECIFIEDUNSPECIFIED
URN: urn:nbn:de:hbz:38-87515
DOI: 10.1016/j.is.2014.11.010
Journal or Publication Title: Information systems : IS ; an international journal ; data bases
Publisher: Elsevier
ISSN: 0306-4379
Volume: 49
Subjects: Data processing Computer science
Management and auxiliary services
Uncontrolled Keywords:
KeywordsLanguage
business process modelEnglish
clone detectionEnglish
model collectionEnglish
repositoryEnglish
standardizationEnglish
Faculty: Faculty of Management, Economy and Social Sciences
Divisions: Faculty of Management, Economy and Social Sciences > Cologne Institute for Information Systems (CIIS)
Language: English
Date: April 2015
Full Text Status: None
Date Deposited: 20 Nov 2018 14:36
Place of Publication: Amsterdam
Refereed: Yes
Status: Published
Page Range: pp. 102-125
URI: http://kups.ub.uni-koeln.de/id/eprint/8751

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