Graph theory and model collection management: conceptual framework and runtime analysis of selected graph algorithms
Analysing conceptual models is a frequent task of business process management (BPM), for instance to support comparison or integration of business processes, to check business processes for compliance or weaknesses, or to tailor conceptual models for different audiences. As recently, many companies...
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| Published in | Information systems and e-business management Vol. 13; no. 1; pp. 69 - 106 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.02.2015
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1617-9846 1617-9854 |
| DOI | 10.1007/s10257-014-0243-6 |
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| Abstract | Analysing conceptual models is a frequent task of business process management (BPM), for instance to support comparison or integration of business processes, to check business processes for compliance or weaknesses, or to tailor conceptual models for different audiences. As recently, many companies have started to maintain large model collections and analysing such collections manually may be laborious, practitioners have articulated a demand for automatic model analysis support. Hence, BPM scholars have proposed a plethora of different model analysis techniques. As virtually any conceptual model can be interpreted as a mathematical graph and model analysis techniques often include some kind of graph problem, in this paper, we introduce a graph algorithm based model analysis framework that can be accessed by specialized model analysis techniques. To prove that basic graph algorithms are feasible to support such a framework, we conduct a performance analysis of selected graph algorithms. |
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| AbstractList | Analysing conceptual models is a frequent task of business process management (BPM), for instance to support comparison or integration of business processes, to check business processes for compliance or weaknesses, or to tailor conceptual models for different audiences. As recently, many companies have started to maintain large model collections and analysing such collections manually may be laborious, practitioners have articulated a demand for automatic model analysis support. Hence, BPM scholars have proposed a plethora of different model analysis techniques. As virtually any conceptual model can be interpreted as a mathematical graph and model analysis techniques often include some kind of graph problem, in this paper, we introduce a graph algorithm based model analysis framework that can be accessed by specialized model analysis techniques. To prove that basic graph algorithms are feasible to support such a framework, we conduct a performance analysis of selected graph algorithms. |
| Author | Breuker, Dominic Steinhorst, Matthias Delfmann, Patrick Dietrich, Hanns-Alexander |
| Author_xml | – sequence: 1 givenname: Dominic surname: Breuker fullname: Breuker, Dominic organization: WWU Muenster - ERCIS – sequence: 2 givenname: Patrick surname: Delfmann fullname: Delfmann, Patrick organization: WWU Muenster - ERCIS – sequence: 3 givenname: Hanns-Alexander surname: Dietrich fullname: Dietrich, Hanns-Alexander organization: WWU Muenster - ERCIS – sequence: 4 givenname: Matthias surname: Steinhorst fullname: Steinhorst, Matthias email: matthias.steinhorst@ercis.uni-muenster.de, Steinhorst@ercis.uni-muenster.de organization: WWU Muenster - ERCIS |
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| CitedBy_id | crossref_primary_10_1016_j_dam_2019_02_023 crossref_primary_10_1007_s10257_018_00394_4 crossref_primary_10_18034_apjee_v11i1_780 crossref_primary_10_1155_2015_524328 |
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| Keywords | Model collection management Business process modeling Graph algorithms Model analysis |
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