Schema Evolution publication categorizer

It is often difficult to obtain a good conceptual understanding of a legacy database, especially when there is a lack of documentation. Database reverse engineering attempts to provide solutions for this problem. It is the part of system maintenance work that produces a sufficient understanding of a legacy database and its application domain to allow appropriate changes to be made. However, research on database reverse engineering has largely ignored design and evaluation issues of their methods (i.e., foundations and processes). This research proposes a framework for the design and evaluation of reverse engineering methods of relational databases. This framework consists of eight criteria: 1) the situation chosen as the basis for reverse engineering, 2) the conceptual model chosen to represent the reverse engineering results, 3) the prerequisites of the database to be reverse engineered, 4) the thoroughness of domain semantics acquisition, 5) rules and heuristics employed by the reverse engineering process, 6) performance efficiency of the reverse engineering process, 7) completeness and robustness and 8) validation. These criteria are important to be considered in designing reverse engineering methods, so that they can perform reverse engineering for a broad range of legacy databases at a high level of automation and provide a conceptual schema that is semantically rich and correct.