Quality Evaluation and Improvement Framework for Database Schemas - Using Defect Taxonomies

Jonathan Lemaitre, Jean-Luc Hainaut

Résultats de recherche: Contribution dans un livre/un catalogue/un rapport/dans les actes d'une conférenceArticle dans les actes d'une conférence/un colloque

178 Téléchargements (Pure)

Résumé

Just like any software artefact, database schemas can (or should) be evaluated against quality criteria such as understandability, expressiveness, maintainability and evolvability. Most quality evaluation approaches rely on global metrics counting simple pattern instances in schemas. Recently, we have developed a new approach based on the identification of semantic classes of definite patterns. The members of a class are proved to be semantically equivalent (through the use of semantics preserving transformations) but are assigned different quality scores according to each criteria. In this paper, we explore in more detail the concept of bad pattern by proposing an intuitive taxonomy of defective patterns together with, for each of them, a better alternative. We identify four main classes of defects, namely complex constructs, redundant constructs, foreign constructs and irregular constructs. For each of them, we develop some representative examples and we discuss ways of improvement against three quality criteria: simplicity, expressiveness and evolvability. This taxonomy makes it possible to apply the framework to quality assessment and improvement in a simple and intuitive way.
langue originaleAnglais
titreCAISE 2011
Etat de la publicationNon publié - 2011

Empreinte digitale Examiner les sujets de recherche de « Quality Evaluation and Improvement Framework for Database Schemas - Using Defect Taxonomies ». Ensemble, ils forment une empreinte digitale unique.

Contient cette citation