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<p><b>Abstract</b>—Powerful solutions enabling interoperability must allow applications to evolve and requirements of shared databases to change, while minimizing such changes on other integrated applications. Several approaches, such as the transparent schema evolution system (TSE) by Ra et al., schema versions by Lautemann, and integrated views by Bertino, have been proposed to make interoperability possible by using object-oriented techniques. These approaches may generate a large number of schema versions over time resulting in an excessive build-up of classes and underlying object instances, not all being necessarily still in use. This results in degradation of system performance due to the view maintenance and the storage overhead costs. In this paper, we address the problem of removing obsolete view schemas. We characterize four potential problems of schema consistency that could be caused by removal of a single derived class. We demonstrate that schema version removal is sensitive to the order in which individual classes are processed, and present a formal dependency model that captures all dependencies between classes as logic clauses and manipulates them to make decisions on class deletions and nondeletions while guaranteeing the consistency of the schema. We have also developed and proven consistent a dependency graph (DG) representation of the formal model. Lastly, we present a cost model for evaluating alternative removal patterns on DG to assure selection of the optimal solution. The proposed techniques have been implemented in our Schema View Removal (SVR) tool. Lastly, we report experimental findings for applying our techniques for consistent schema version removal on the MultiView/TSE system.</p>
Object-oriented views, schema version, transparent schema evolution, interoperability, evolving software applications, performance evaluation.
Amy J. Lee, Viviane M. Crestana-Jensen, Elke A. Rundensteiner, "Consistent Schema Version Removal: An Optimization Technique for Object-Oriented Views", IEEE Transactions on Knowledge & Data Engineering, vol. 12, no. , pp. 261-280, March/April 2000, doi:10.1109/69.842266
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