Algorithms for analysing related constraint business rules

  • Authors:
  • Gaihua Fu;Jianhua Shao;Suzanne M. Embury;W. Alex Gray

  • Affiliations:
  • Department of Computer Science, Cardiff University, Newport Road, Cardiff CF24 3XF, UK;Department of Computer Science, Cardiff University, Newport Road, Cardiff CF24 3XF, UK;Department of Computer Science, Unirersity of Manchester, Oxford Road, Manchester MI3 9PL, UK;Department of Computer Science, Cardiff University, Newport Road, Cardiff CF24 3XF, UK

  • Venue:
  • Data & Knowledge Engineering
  • Year:
  • 2004

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Abstract

Constraints represent a class of business rules that describe the conditions under which an organisation operates. It is common that organisations implement a large number of constraints in their supporting information systems. To remain competitive in today's ever-changing business environment, organisations are increasingly recognising the ability to evolve the implemented constraints timely and correctly. While many techniques have been proposed to assist constraint specification and enforcement in information systems, little has been done so far to help constraint evolution. In this paper, we introduce a form of constraint analysis that is particularly geared towards constraint evolution. More specifically, we propose several algorithms for determining which constraints collectively restrict a specified set of business objects, and we study their performance. Since the constraints contained in an information system are typically in large quantities and tend to be fragmented during implementation, this type of analysis is desirable and valuable in the process of their evolution.