No-redundant Metrics for UML Class Diagram Structural Complexity

Abstract

In software engineering it is widely acknowledged that the usage of metrics at the initial phases of the object oriented software life cycle can help designers to make better decisions and to predict external quality attributes, such as maintainability. Following this idea we have carried out three controlled experiments to ascertain if any correlation exists between the structural complexity and the size of UML class diagrams and their maintainability. We used 8 metrics for measuring the structural complexity of class diagrams due to the usage of UML relationships, and 3 metrics to measure their size. With the aim of determining which of these metrics are really relevant to be used as class diagrams maintainability indicators, we present in this work a study based on Principal Component Analysis. The obtained results show that the metrics related to associations, aggregations, generalizations and dependencies, are the most relevant whilst those related to size seem to be redundant.

On the Application of Information Entropy-based Multi-attribute Decision in UML Class Diagram Metrics

“…In order to highlight the comparative, the numerical results of this paper expanded ten times in Figure 1. Values of Understandability, analyzability and maintainability in Table 5, came from experiments of M. Genero [11][12][13][14][15][16][17][18][19][20]. …”

“…On the condition of getting permission from M. Genero, we also use the same former twenty-seven UML class diagrams related to bank information systems as material [11][12][13][14][15][16][17][18][19][20]. M. Genero, et al carry out some comprehensive controlled experiments [11][12][13][14][15][16][17][18][19][20].…”

“…During the last several years, many different metrics for class diagrams have been suggested [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]. These metrics help software developers to analyze reliability, maintainability and complexity of systems in the early phase of the OO software lifecycle.…”

“…Genero also discusses a group of indicators to measure the complexity of class diagrams [11][12][13][14][15][16][17][18][19][20]. They are the respective total number of classes (NC), attributes (NA), methods (NM), associations relationships (NAssoc), aggregation relationships (NAgg), dependency relationships (NDep), generalization relationships (NGen), generalization hierarchies (NGenH), and aggregation hierarchies (NAggH); respective percentage of the NAssoc, NAgg, NDep, and NGen with respect to the NC whose results can be abbreviated as NAssocVC, NAggVC, NDepVC, and NgenVC respectively; the respective maximum DIT and Hagg value whose results can be abbreviated as MaxDIT and MaxHagg respectively.…”

A Structural Complexity Measure for UML Class Diagrams

“…Genero proposed new metrics to cover the necessity of measuring these relationships [6]. Manso and Genero used 8 metrics for measuring the structural complexity and the size of UML class diagrams and their maintainability [7]. But they did not give a single complexity measuring integrate all these metrics.…”