Enterprise Modeling and Decision-Support for Automating the Business Rules Lifecycle

  • Authors:

  • Daniela Rosca;Sol Greenspan;Chris Wild

  • Affiliations:

  • Department of Software Engineering, Monmouth University, W. Long Branch, NJ 07764, USA. drosca@monmouth.edu;Consultant. sol.greenspan@ieee.org;Department of Computer Science, Old Dominion University, Norfolk, VA 23529-0162, USA. wild@cs.odu.edu

  • Venue:
  • Automated Software Engineering
  • Year:
  • 2002

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Abstract

Business rules represent policies, procedures and constraints regarding how an enterprise conducts its business. To get the full benefits of modeling business rules requires an approach to managing them through their full lifecycle, from acquisition through deployment and evolution. The research reported in this paper is aimed at determining what infrastructure capabilities are needed to provide this lifecycle support. The solution embodies a modeling framework that captures the structure of the enterprise, in terms of which the business rules can be expressed, and decision-support capabilities for reasoning about and deriving business rules. The paper demonstrates the possibility of automatic support of the business rules lifecycle by automatically generating business rules from the captured information, along with data representing domain assumptions in a case study (the London Ambulance System). A system was implemented to illustrate the methodology and to demonstrate the feasibility of the approach. The methodology also gives guidance on how to deal with pragmatically important situations such as rules that involve both automated and human tasks, nondeterministic rules, and goal-oriented versus operational rules.