Export bibliographic data
Literature by the same author
plus on the publication server
plus at Google Scholar


Comparing Imperative and Declarative Process Models

URN to cite this document: urn:nbn:de:bvb:703-epub-3325-2

Title data

Baumann, Michaela:
Comparing Imperative and Declarative Process Models.
Bayreuth , 2017 . - 12 S.

This is the latest version of this item.

[img] PDF
MBaumann_ComparingProcessModels_DeHMiMoP17_EPub.pdf - Preprint
Available under License Deutsches Urheberrechtsgesetz .

Download (309kB)


The field of process model similarity matching is well examined for imperative process models like BPMN models, Petri nets, or EPCs where a lot of different measuring techniques exist. For the recently upcoming declarative process models, generally providing more flexibility than imperative models, however, there is a lack of comparison methods. Along with their advantage of providing more flexibility, declarative process models have a disadvantage in comprehending the models, especially the models' behavior. To overcome this problem, a comparison of imperative and declarative models is reasonable to check whether the declarative model represents a desired behavior which is easier to express and validate in an imperative notation. The work at hand provides a method based on flow dependencies, abstracting from the modeling type, for comparing two process models. It uses not only information about control-flow, but also data-based dependencies between process activities.

Further data

Item Type: Preprint, postprint
Keywords: Process Model Comparison; Process Model Similarity; Behavioral Similarity; Behavioral Profile; Flow Dependency
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IV
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Language: English
Originates at UBT: Yes
URN: urn:nbn:de:bvb:703-epub-3325-2
Date Deposited: 16 Jun 2017 09:43
Last Modified: 18 Mar 2019 13:37
URI: https://epub.uni-bayreuth.de/id/eprint/3325

Available Versions of this Item


Downloads per month over past year