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Information Resources Management Association
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Agile Development of Rule Systems

Agile Development of Rule Systems
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Author(s): Joachim Baumeister (University of Wuerzburg, Germany), Dietmar Seipel (University of Wuerzburg, Germany) and Frank Puppe (University of Wuerzburg, Germany)
Copyright: 2009
Pages: 20
Source title: Handbook of Research on Emerging Rule-Based Languages and Technologies: Open Solutions and Approaches
Source Author(s)/Editor(s): Adrian Giurca (Brandenburg Technology University at Cottbus, Germany), Dragan Gasevic (Athabasca University, Canada) and Kuldar Taveter (University of Melbourne, Australia)
DOI: 10.4018/978-1-60566-402-6.ch011


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The engineering of rule-based systems was a relevant issue in the past decades and has become more attractive recently due to the emergence of intelligent applications on the web. For example, web application servers including rule engines and the rule-based description of (semantic) web services. This development allows for a natural formalization of business logic but also poses new challenges with respect to the acquisition and evolution of rule-based knowledge. Although, a lot of research has been done in the past, the practical engineering and life cycle of larger rule-based systems still remains to be a difficult and complex task. State-of-the-art tools for rule development provide extensive support for the engineering, the analysis and debugging of such systems, but a simple and easily adoptable methodology is missing. In the best case, such a methodology should be well understood even with little training and should provide techniques to ensure quality, evolutionary health, and cost control of a rule base project. We present an agile methodology for the development and evolution of rule-based systems. Intuitive concepts like the system metaphor, the planning game, and the implementation cycle make its adoption to arbitrary projects very easy. With the promotion of continuous techniques such as automated testing and refactoring we cope with evolutionary aspects of knowledge bases.

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