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An execution model for limited ambiguity rules and its application to derived data update
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Source ACM Transactions on Database Systems (TODS) archive
Volume 20 ,  Issue 4  (December 1995) table of contents
Pages: 365 - 413  
Year of Publication: 1995
ISSN:0362-5915
Authors
I.-Min A. Chen  Lawrence Berkeley Lab, Berkeley, CA
Richard Hull  Univ. of Colorado, Boulder
Dennis McLeod  Univ. of Southern California, Los Angeles
Publisher
ACM  New York, NY, USA
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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.


REFERENCES

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CHIN, I. A., HULL, R., AND McLEOD, D.1993. On using ambiguous rules to update derived data. USC Tech. Rep. USC-CS-93-535.
 
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REVIEW

"Ferdi W. J. Put : Reviewer"

In the traditional approach to modification of derived data, base data are updated explicitly by users, which in turn may cause updates to the derived data. However, it is also desirable that users can modify derived data directly. In this pap  more...

Collaborative Colleagues:
I.-Min A. Chen: colleagues
Richard Hull: colleagues
Dennis McLeod: colleagues