Check Swinburne's subscriptions for full text availabilityPermanent link: http://hdl.handle.net/1959.3/211029
- Title
- Modeling and managing variability in process-based service compositions
- Author(s)
- Nguyen, Tuan; Colman, Alan; Han, Jun
- Abstract
- Variability in process-based service compositions needs to be explicitly modeled and managed in order to facilitate service/process customization and increase reuse in service/process development. While related work has been able to capture variability and variability dependencies within a composition, these approaches fail to capture variability dependencies between the composition and partner services. Consequently, these approaches cannot address the situation when a composite service is orchestrated from partner services some of which are customizable. In this paper, we propose a feature-based approach that is able to effectively model variability within and across compositions. The approach is supported by a process development methodology that enables the systematic reuse and management of variability. We develop a prototype system supporting extended BPMN 2.0 to demonstrate the feasibility of our approach.
- Publication Type
- Conference paper
- Research Centre
- Swinburne University of Technology. Faculty of Information and Communication Technologies
- Source
- Lecture notes in computer science: proceedings of the 9th International Conference on Service-Oriented Computing (ICSOC 2011), Paphos, Cyprus, 05-08 December 2011 / Gerti Kappel, Zakaria Maamar and Hamid R. Motahari-Nezhad (eds.), Vol. 7084, pp. 404-420
- Publication Year
- 2011
- FOR Code(s)
- 08 Information and Computing Sciences
- Keyword(s)
- Feature modeling; MDE; Model Driven Engineering; Model mapping; Process variability; Service composition; Service variability; Software Product Line; SPL; Variability management
- Publisher
- Springer
- Publisher URL
- http://dx.doi.org/10.1007/978-3-642-25535-9_27
- Copyright
- Copyright © Springer-Verlag Berlin Heidelberg 2011.
- ISBN
- 9783642255342
- ISSN
- 0302-9743 (series ISSN)
- Peer Reviewed
