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Business & Information Systems Engineering
Erschienen in: Business & Information Systems Engineering 1/2016

08.12.2015 | Research Paper

Criteria and Heuristics for Business Process Model Decomposition

Review and Comparative Evaluation

verfasst von: Fredrik Milani, Marlon Dumas, Raimundas Matulevičius, Naved Ahmed, Silva Kasela

Erschienen in: Business & Information Systems Engineering | Ausgabe 1/2016

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Abstract

It is generally agreed that large process models should be decomposed into sub-processes in order to enhance understandability and maintainability. Accordingly, a number of process decomposition criteria and heuristics have been proposed in the literature. This paper presents a review of the field revealing distinct classes of criteria and heuristics. The study raises the question of how different decomposition heuristics affect process model understandability and maintainability. To address this question, an experiment is conducted where two different heuristics, one based on breakpoints and the other on data objects, were used to decompose a flat process model. The results of the experiment show that, although there are minor differences, the heuristics cause very similar results in regard to understandability and maintainability as measured by various process model metrics.
Vorheriger Artikel Business Process Management
Nächster Artikel Mixed-Paradigm Process Modeling with Intertwined State Spaces

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Fußnoten
1
The list of publications can be accessed at http://​sep.​cs.​ut.​ee/​Main/​ProcessDecomposi​tion.
 
2
 
3
The values for the experiment can be accessed at http://​sep.​cs.​ut.​ee/​Main/​ProcessDecomposi​tion.
 
4
The statistical analysis can be accessed at http://​sep.​cs.​ut.​ee/​Main/​ProcessDecomposi​tion.
 
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Metadaten
Titel
Criteria and Heuristics for Business Process Model Decomposition
Review and Comparative Evaluation
verfasst von
Fredrik Milani
Marlon Dumas
Raimundas Matulevičius
Naved Ahmed
Silva Kasela
Publikationsdatum
08.12.2015
Verlag
Springer Fachmedien Wiesbaden
Erschienen in
Business & Information Systems Engineering / Ausgabe 1/2016
Print ISSN: 2363-7005
Elektronische ISSN: 1867-0202
DOI
https://doi.org/10.1007/s12599-015-0413-1

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