Model-driven development of adaptive service-based systems with aspects and rules

  • Authors:

  • Jian Yu;Quan Z. Sheng;Joshua K. Y. Swee

  • Affiliations:

  • School of Computer Science, The University of Adelaide, SA, Australia;School of Computer Science, The University of Adelaide, SA, Australia;School of Computer Science, The University of Adelaide, SA, Australia

  • Venue:
  • WISE'10 Proceedings of the 11th international conference on Web information systems engineering
  • Year:
  • 2010

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Abstract

Service-oriented computing (SOC) has become a dominant paradigm in developing distributed Web-based software systems. Besides the benefits such as interoperability and flexibility brought by SOC, modern service-based software systems are frequently required to be highly adaptable in order to cope with rapid changes and evolution of business goals, requirements, as well as physical context in a dynamic business environment. Unfortunately, adaptive systems are still difficult to build due to its high complexity. In this paper, we propose a novel approach called MoDAR to support the development of dynamically adaptive service-based systems (DASS). Especially in this approach, we first model the functionality of a system by two constituent parts: i) a stable part called the base model described using business processes, and ii) a volatile part called the variable model described using business rules. This model reflects the fact that business processes and rules are two significant and complementary aspects of business requirements, and business rules are usually much more volatile than business processes. We then use an aspect-oriented approach to weave the base model and variable model together so that they can evolve independently without interfering with each other. A model-driven platform has been implemented to support the development lifecycle of a DASS from specification, design, to deployment and execution. Systems developed with the MoDAR platform are running on top of a BPEL process engine and a Drools rule engine. Experimentation shows that our approach brings high adaptability and maintainability to service-based systems with reasonable performance overhead.