Modeling and managing the variability of Web service-based systems

  • Authors:

  • Chang-ai Sun;Rowan Rossing;Marco Sinnema;Pavel Bulanov;Marco Aiello

  • Affiliations:

  • School of Information Engineering, University of Science and Technology Beijing, 30 Xueyuan Road, Haidian District, 100083 Beijing, China;Department of Mathematics and Computer Science, University of Groningen, P.O. Box 800, 9700 AV Groningen, The Netherlands;Department of Mathematics and Computer Science, University of Groningen, P.O. Box 800, 9700 AV Groningen, The Netherlands;Department of Mathematics and Computer Science, University of Groningen, P.O. Box 800, 9700 AV Groningen, The Netherlands;Department of Mathematics and Computer Science, University of Groningen, P.O. Box 800, 9700 AV Groningen, The Netherlands

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2010

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Abstract

Web service-based systems are built orchestrating loosely coupled, standardized, and internetworked programs. If on the one hand, Web services address the interoperability issues of modern information systems, on the other hand, they enable the development of software systems on the basis of reuse, greatly limiting the necessity for reimplementation. Techniques and methodologies to gain the maximum from this emerging computing paradigm are in great need. In particular, a way to explicitly model and manage variability would greatly facilitate the creation and customization of Web service-based systems. By variability we mean the ability of a software system to be extended, changed, customized or configured for use in a specific context. We present a framework and related tool suite for modeling and managing the variability of Web service-based systems for design and run-time, respectively. It is an extension of the COVAMOF framework for the variability management of software product families, which was developed at the University of Groningen. Among the novelties and advantages of the approach are the full modeling of variability via UML diagrams, the run-time support, and the low involvement of the user. All of which leads to a great deal of automation in the management of all kinds of variability.