Database Complexity Metrics

Abstract

Metrics are useful mechanisms for improving the quality of soji`vvare products and also for determim.ng the best ways ro help practitioners and researchers. UnfortunateLy, almost all the metrics put forward focus on program characteristz`cs disregardz.ng databases. However, databases are becomz`ng more compLex, and it is necessary to measure schemata complexity in order to understand, monz.tor, control, predict and z.mprove database development and ma"zntenance projects. In fizz's paper, we will present dierent measures in order to measure the complexz-ty that aJTects the maintainabz"Iz.ty of the relational, object-relatz`onal and active database schemas. However it is not enough to propose the metrics, a formaL validatz.on is also needed for know!ng thez.r mathematz.caL characteristics. We wz.II present the two main tendencz.es in metrics formal validation, axz`omatz.c approaches and measurement theory" However, research !nto sofiware measurement is needed from a theoretz`caL but also jrom a practical point of view ( (121). For thz`s reason, we wz`LL also present some of the experz ments that we have developedfor the dijferent ia`nds of databases.

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Cite this paper

@inproceedings{Calero2001DatabaseCM, title={Database Complexity Metrics}, author={Coral Calero and Mario Piattini and Marcela Genero}, booktitle={QUATIC}, year={2001} }