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Enhancing Aspect-Oriented Business Process Modeling with Declarative Rules
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
University of Tartu, , .
Eindhoven University of Technology, , .
2015 (English)In: International Conference on Conceptual Modelling (ER), Springer Publishing Company , 2015Conference paper (Refereed)
Abstract [en]

When managing a set of inter-related business processes, typically a number of concerns can be distinguished that are applicable to more than one single process, such as security and traceability. The proper enforcement of these cross-cutting concerns may require a specific configuration effort for each of the business processes involved. Aspect-Oriented Business Process Modelling is an approach that aims at encapsulating these concerns in a model-oriented way. However, state-of-the-art techniques lack efficient mechanisms that allow for the specification of concerns in such a way that they can be executed in parallel to other parts of the process. Moreover, existing techniques exclusively focus on the formulation of mandatory concerns. To address these limitations, this paper provides a new approach to encapsulate both optional and mandatory concerns, which can be executed concurrently with other process functionalities. One core element of the new approach is that it extends current Aspect-Oriented Business Process Modelling approaches with declarative rules. The approach is explained, formally grounded with precise semantics, and used accordingly to implement the artefacts that support the enactment of a business process in the proposed fashion. The execution environment is applied to a case from the educational domain to demonstrate the feasibility and usefulness of the underlying concepts.

Place, publisher, year, edition, pages
Springer Publishing Company , 2015.
Keyword [en]
Business Process Modelling, Aspect Orientation, Cross-Cutting Concerns, Declarative Rules
National Category
Information Systems
Research subject
Computer and Systems Sciences
URN: urn:nbn:se:su:diva-122810DOI: 10.1007/978-3-319-25264-3_8ISBN: 978-3-319-25264-3OAI: diva2:868634
Available from: 2015-11-11 Created: 2015-11-10 Last updated: 2015-11-11

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