A knowledge-based system for performing reverse engineering of relational databases

doi:10.1016/0167-9236(93)E0047-H

Decision Support Systems

Volume 13, Issues 3–4, March 1995, Pages 295-312

https://doi.org/10.1016/0167-9236(93)E0047-H Get rights and content

Abstract

A knowledge-based system, called the Knowledge Extraction System (KES), is presented which performs the process of reverse engineering of relational databases. KES generates an extended entity-relationship (EER) model from a relational database. Within its extraction procedure, domain semantics are obtained by analyzing the data schema and data instances of an existing database, by using heuristics, or asking the user. Relations and attributes are classified into several categories and then converted into the corresponding modelling structures of the EER model. KES demonstrates how knowledge-based system technology can be applied to ease the work of database reverse engineering. It also illustrates that the reverse engineering process can be implemented at a high level of automation. To do so, KES is integrated with the target database management system so that data can be analyzed directly through dynamic SQL queries.

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A knowledge-based system for performing reverse engineering of relational databases

Abstract

Journal of Computer and System Sciences

Dat. & Knowledge Engineering

What IS-A Is and Isn't: An Analysis of Taxonomic Links in Semantic Networks

IEEE Computer

The Entity Relationship Model — Toward a Unified View of Data

ACM Transactions on Database Systems

Reverse Engineering and Design Recovery: A Taxonomy

IEEE Software

Converting a Relational Database Model into an Entity-Relationship Model

Schema Translation Using the Entity-Relationship Approach

Database Reverse Engineering: Models, techniques and strategies

An Algorithm Converting Relational Schemas to Nested Entity Relationship Schemas