Defining and Validating Measures for Conceptual Data Model Quality

Authors:
Marcela Genero;Geert Poels;Mario Piattini
Affiliations:
-;-;-
Venue:
CAiSE '02 Proceedings of the 14th International Conference on Advanced Information Systems Engineering
Year:
2002

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Abstract

For assessing conceptual data model quality it is useful to have quantitative and objective measurement instruments. The scarcity of such measurement instruments leaded us to define a set of measures for structural complexity, an internal quality attribute of conceptual data models, with the idea that it is related to the external quality of such models. In order to gather empirical evidence that the proposed measures could be early quality indicators of conceptual data models, we carried out a controlled experiment. The aim of the experiment was to investigate the relation between the structural complexity of conceptual data models and maintainability sub-characteristics such as understandability and modifiability.