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 inInformation systems and e-business management Vol. 13; no. 1; pp. 69 - 106
Main Authors Breuker, Dominic, Delfmann, Patrick, Dietrich, Hanns-Alexander, Steinhorst, Matthias
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2015
Springer Nature B.V
Subjects
Online AccessGet full text
ISSN1617-9846
1617-9854
DOI10.1007/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.
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
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  surname: Breuker
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  givenname: Hanns-Alexander
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  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
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SubjectTerms Algorithms
Business
Business and Management
Business process management
Business process reengineering
Collection
Collection management
Computer simulation
Graph theory
Graphs
Information systems
Information Systems Applications (incl.Internet)
IT in Business
Management
Mathematical models
Original Article
Process controls
Studies
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Title Graph theory and model collection management: conceptual framework and runtime analysis of selected graph algorithms
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