Knowledge-Based AOP Framework for Business Rule Aspects in Business Process

  • Park, Chan-Kyu (Intelligent Robot Research Division, ETRI) ;
  • Choi, Ho-Jin (Department of Software Engineering, Information and Communications University) ;
  • Lee, Dan-Hyung (Department of Software Engineering, Information and Communications University) ;
  • Kang, Sung-Won (Department of Software Engineering, Information and Communications University) ;
  • Cho, Hyun-Kyu (Intelligent Robot Research Division, ETRI) ;
  • Sohn, Joo-Chan (Intelligent Robot Research Division, ETRI)
  • Received : 2006.05.26
  • Published : 2007.08.31

Abstract

In recent years, numerous studies have identified and explored issues related to web-service-oriented business process specifications, such as business process execution language (BPEL). In particular, business rules are an important cross-cutting concern that should be distinguished from business process instances. In this paper, we present a rule-based aspect oriented programming (AOP) framework where business rule aspects contained in business processes can be effectively separated and executed. This is achieved by using a mechanism of the business rule itself at the business rule engine instead of using existing programming language-based AOP technologies. Through some illustrative examples, this work also introduces a method by which business rule aspects, separated through an external rule engine, can be represented and evaluated. We also demonstrate how they can be dynamically woven and executed by providing an implementation example which uses two open-source-based products, the Mandarax rules engine and Bexee BPEL engine.

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