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Ninth International Software Metrics Symposium (METRICS'03)   p. 263
Building UML Class Diagram Maintainability Prediction Models Based on Early Metrics
Marcela Genero, University of Castilla-La Mancha
Mario Piattini, University of Castilla-La Mancha
Esperanza Manso, University of Valladolid
Giovanni Cantone, Università degli Studi di Roma "Tor Vergata"

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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/METRIC.2003.1232473
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Abstract
The fact that the usage of metrics in the analysis and design of object oriented (OO) software can help designers make better decisions is gaining relevance in software measurement arena. Moreover, the necessity of having early indicators of external quality attributes, such as maintainability, based on early metrics is growing. In addition to this, the aim of the present paper is to show how early metrics which measure internal attributes, such as structural complexity and size of UML class diagrams, can be used as early class diagram maintainability indicators. For this purpose, we present a controlled experiment and its replication, which we carried out to gather the empirical data which in turn is the basis of the current study. From the results obtained, it seems that there is a reasonable chance that useful class diagram maintainability models could be built based on early metrics. Despite this fact, more empirical studies, especially using data taken form real projects performed in industrial settings, are needed in order to obtain a comprehensive body of knowledge and experience.
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Index Terms- maintainability, class diagrams, structural complexity, size, object-oriented metrics, empirical validation, controlled experiments, prediction model Citation:  Marcela Genero, Mario Piattini, Esperanza Manso, Giovanni Cantone, "Building UML Class Diagram Maintainability Prediction Models Based on Early Metrics," metrics, p. 263,  Ninth International Software Metrics Symposium (METRICS'03),  2003