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Modeling and Managing Variability in Process-Based Service Compositions

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Part of the book series:Lecture Notes in Computer Science ((LNPSE,volume 7084))

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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 dependenciesbetween 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.

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Authors and Affiliations

  1. Faculty of Information and Communication Technology, Swinburne University of Technology, Melbourne, Australia

    Tuan Nguyen, Alan Colman & Jun Han

Authors
  1. Tuan Nguyen

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  2. Alan Colman

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  3. Jun Han

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Editor information

Editors and Affiliations

  1. Institute of Software Technology and Interactive Systems, Vienna University of Technology, Favoritenstraße 9-11, 1010, Vienna, Austria

    Gerti Kappel

  2. College of Information Technology, Zayed University, P.O. Box 19282, Dubai, UAE

    Zakaria Maamar

  3. HP Labs - Services Research Lab, 1501 Page Mill Road, 94304, Palo Alto, CA, USA

    Hamid R. Motahari-Nezhad

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© 2011 Springer-Verlag Berlin Heidelberg

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Nguyen, T., Colman, A., Han, J. (2011). Modeling and Managing Variability in Process-Based Service Compositions. In: Kappel, G., Maamar, Z., Motahari-Nezhad, H.R. (eds) Service-Oriented Computing. ICSOC 2011. Lecture Notes in Computer Science, vol 7084. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25535-9_27

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