By Topic

Delta abstractions: A technique for managing database states in runtime debugging of active database rules

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Urban, S.D. ; Dept. of Comput. Sci. & Eng., Arizona State Univ., Tempe, AZ, USA ; Ben Abdellatif, T. ; Dietrich, S.W. ; Sundermier, A.

Delta abstractions are introduced as a mechanism for managing database states during the execution of active database rules. Delta abstractions build upon the use of object deltas, capturing changes to individual objects through a system-supported, collapsible type structure. The object delta structure is implemented using object-oriented concepts such as encapsulation and inheritance so that all database objects inherit the ability to transparently create and manage delta values. Delta abstractions provide an additional layer to the database programmer for organizing object deltas according to different language components that induce database changes, such as methods and active rules. As with object deltas, delta abstractions are transparently created and maintained by the active database system. We define different types of delta abstractions as views of object deltas and illustrate how the services of delta abstractions can be used to inspect the state of active rule execution. An active rule analysis and debugging tool has been implemented to demonstrate the use of object deltas and delta abstractions for dynamic analysis of active rules at runtime.

Published in:

Knowledge and Data Engineering, IEEE Transactions on  (Volume:15 ,  Issue: 3 )