Table oriented metrics for relational databases
Developing and selecting high quality software applications are fundamental. It is important that the software applications can be evaluated for every relevant quality characteristic using validated metrics. Software engineers have been putting forward hundreds of quality metrics for software programs, disregarding databases. However, software data aspects are important because the size of data and their system nature contribute to many aspects of a systems quality. In this paper, we proposed some internal metrics to measure relational databases which influence its complexity. Considering the main characteristics of a relational table, we can propose the number of attributes (NA) of a table, the depth of the referential tree (DRT) of a table, and the referential degree (RD) of a table. These measures are characterized using measurement theory, particularly the formal framework proposed by Zuse. As many important issues faced by the software engineering community can only be addressed by experimentation, an experiment has been carried out in order to validate these metrics.
metrics databases quality gqm formal validation empirical validation