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

  • Jonathan Lemaitre
  • Jean-Luc Hainaut
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6741)


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.


Conceptual data schema quality schema improvement schema evaluation schema transformation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jonathan Lemaitre
    • 1
  • Jean-Luc Hainaut
    • 1
  1. 1.Laboratory of Database Application Engineering - PReCISE research Center Faculty of Computer ScienceUniversity of NamurNamurBelgium

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