Database Reverse Engineering

Credits This text is based on results of three R&D projects, namely TRAMIS, addressing the base-lines of transformational support to database engineering [Hainaut 1992], PHENIX, dedicated to AI techniques for Database Reverse The current shape and contents of this text is strongly influenced by the work of the DB-MAIN team: Vincent Englebert (Meta tools, Voyager 2), Jean Henrard (reverse engineering, program understanding), Jean-Marc Hick (repository, GUI, DB evolution control), Didier Roland (tool assistants, design process modeling). Besides their theoretical contribution, the rich DB-MAIN CASE environment, of which they are the architects and craftmen, transforms the material of this book into practical methods and techniques that can be most helpful for practitioners. Quite naturally, they must be considered as co-authors of this text. Summary This chapter is an introduction to the problem of database reverse engineering (DBRE), considered as a specific, but general purpose, activity of information system engineering, and particularly system reengineering. To give it as large a scope as possible, we have developed general principles that can easily be specialized for any actual data management system, ranging from simple file managers (COBOL or RPG) to modern DB managers such as relational systems and OO DBMS. These principles are organized as a general DBRE methodology that is built in a systematic way. This methodology can be specialized according to specific DBMS models. It can be used to compare methodologies proposed in the literature and through reverse engineering CASE tools. First, the baselines of the realm are developed: what are the problems (1), how to describe and transform technical and semantic data structures (2), and where are the problem coming from (3). Then, the principles of a generic methodology are developed (4). It comprises two main processes, namely Data Structure Extraction (5), through which the complete technical structures are elicited, and Data Structure Conceptualization (6), that tries to interpret these data structures into conceptual terms. The methodology is specialized according to some popular data models (7) and the way in which current CASE technology can support the processes is discussed (8). A short, but realistic, case study of database reeingineering is presented (9). A state of the art and bibliographic notes (10) close the presentation.

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