An execution model for limited ambiguity rules and its application to derived data update

  • Authors:
  • I.-Min A. Chen;Richard Hull;Dennis McLeod

  • Affiliations:
  • Lawrence Berkeley Lab, Berkeley, CA;Univ. of Colorado, Boulder;Univ. of Southern California, Los Angeles

  • Venue:
  • ACM Transactions on Database Systems (TODS)
  • Year:
  • 1995

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Abstract

A novel execution model for rule application in active databases is developed and applied to the problem of updating derived data in a database represented using a semantic, object-based database model. The execution model is based on the use of “limited ambiguity rules” (LARs), which permit disjunction in rule actions. The execution model essentially performs a breadth-first exploration of alternative extensions of a user-requested update. Given an object-based database schema, both integrity constraints and specifications of derived classes and attributes are compiled into a family of limited ambiguity rules. A theoretical analysis shows that the approach is sound: the execution model returns all valid “completions” of a user-requested update, or terminates with an appropriate error notification. The complexity of the approach in connection with derived data update is considered.