Conceptual database design: an Entity-relationship approach
Conceptual database design: an Entity-relationship approach
Understanding relationships with attributes in entity-relationship diagrams
ICIS '99 Proceedings of the 20th international conference on Information Systems
A Hierarchical Model for Object-Oriented Design Quality Assessment
IEEE Transactions on Software Engineering
Improving Quality in Conceptual Modelling by the Use of Schema Transformations
ER '96 Proceedings of the 15th International Conference on Conceptual Modeling
A Formal Framework for ER Schema Transformation
ER '97 Proceedings of the 16th International Conference on Conceptual Modeling
Standard Transformations for the Normalization of ER Schemata
CAiSe '95 Proceedings of the 7th International Conference on Advanced Information Systems Engineering
Complexity and clarity in conceptual modeling: comparison of mandatory and optional properties
Data & Knowledge Engineering - Special issue: Quality in conceptual modeling
Perceived vs. measured quality of conceptual schemas: an experimental comparison
ER '07 Tutorials, posters, panels and industrial contributions at the 26th international conference on Conceptual modeling - Volume 83
Normalized data base structure: a brief tutorial
SIGFIDET '71 Proceedings of the 1971 ACM SIGFIDET (now SIGMOD) Workshop on Data Description, Access and Control
Transformation-based framework for the evaluation and improvement of database schemas
CAiSE'10 Proceedings of the 22nd international conference on Advanced information systems engineering
The transformational approach to database engineering
GTTSE'05 Proceedings of the 2005 international conference on Generative and Transformational Techniques in Software Engineering
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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.