Database Reverse Engineering Process Research Articles

Database reverse engineering based on meta-models

Abstract Reengineering is one of the key concepts in software maintenance and evolution. It generally includes some form of reverse engineering followed by some form of forward engineering or restructuring. In the paper we focus on database reverse engineering. Model-driven software engineering promotes the idea of abstracting implementation details by focusing on: models as first class entities and automated generation of models or code from other models. In the approach meta-models are used to define the modeling languages. A database reverse engineering process can benefit of integrating meta-modeling and meta-models in the process. The plethora of models related to databases points out to the need and importance of model-to-model transformations between these models at different abstraction levels. These transformations are based on meta-models that are conformed by the source and target models of the transformations. A database reverse engineering process can be performed through a chain of model-to-model transformations based on a set of meta-models. In the paper we discuss the importance of meta-modeling in the context of database reverse engineering and present a case study illustrating an approach to database reverse engineering.

Understanding database schema evolution: A case study

Database reverse engineering (DRE) has traditionally been carried out by considering three main information sources: (1) the database schema, (2) the stored data, and (3) the application programs. Not all of these information sources are always available, or of sufficient quality to inform the DRE process. For example, getting access to real-world data is often extremely problematic for information systems that maintain private data. In recent years, the analysis of the evolution history of software programs have gained an increasing role in reverse engineering in general, but comparatively little such research has been carried out in the context of database reverse engineering. The goal of this paper is to contribute to narrowing this gap and exploring the use of the database evolution history as an additional information source to aid database schema reverse engineering. We present a tool-supported method for analyzing the evolution history of legacy databases, and we report on a large-scale case study of reverse engineering a complex information system and curate it as a benchmark for future research efforts within the community.

Reverse engineering of relational databases: Extraction of an EER model from a relational database

A methodology for extracting an extended Entity-Relationship (EER) model from a relational database is presented. Through a combination of data schema and data instance analysis, an EER model is derived which is semantically richer and more comprehensible for maintenance and design purposes than the original database. Classification schemes for relations and attributes necessary for the EER model extraction are derived and justified. These have been demonstrated to be implementable in a knowledge-based system; a working prototype system which does so is briefly discussed. In addition, cases in which human input is required are also clearly identified. This research also illustrates that the database reverse engineering process can be implemented at a high level of automation.