Class cohesion refers to the degree of the relatedness of the members in a class. It is considered as one of most important object-oriented software attributes. Several metrics have been proposed in the literature in order to measure class cohesion in objectoriented systems. They capture class cohesion in terms of connections among members within a class. The major existing class cohesion metrics are essentially based on instance variables usage criteria. It is only a special and a restricted way of capturing class cohesion. We believe, as stated in many papers, that class cohesion should not exclusively be based on common instance variables usage criteria. We introduce, in this paper, a new criterion, which focuses on interactions between class methods. We developed a cohesion measurement tool for Java programs and performed a case study on several systems. The obtained results demonstrate that our new class cohesion metric, based on the proposed cohesion criteria, captures several pairs of related methods, which are not captured by the existing cohesion metrics.

In this paper, we investigate empirically the relationship between object-oriented design metrics and testability of classes. We address testability from the point of view of unit testing effort. We collected data from three open source Java software systems for which JUnit test cases exist. To capture the testing effort of classes, we used metrics to quantify the corresponding JUnit test cases. Classes were classified, according to the required unit testing effort, in two categories: high and low. In order to evaluate the relationship between object-oriented design metrics and unit testing effort of classes, we used logistic regression methods. We used the univariate logistic regression analysis to evaluate the individual effect of each metric on the unit testing effort of classes. The multivariate logistic regression analysis was used to explore the combined effect of the metrics. The performance of the prediction models was evaluated using Receiver Operating Characteristic analysis. The results indicate that: 1) complexity, size, cohesion and (to some extent) coupling were found significant predictors of the unit testing effort of classes and 2) multivariate regression models based on object-oriented design metrics are able to accurately predict the unit testing effort of classes.

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Aspect-Oriented Software Development is a promising new software engineering paradigm. It promotes, in particular, improved separation of crosscutting concerns into single units called aspects. AspectJ, the most used aspect-oriented programming language, represents an extension of Java. In fact, existing objectoriented programming languages suffer from a serious limitation in modularizing adequately crosscutting concerns. Many concerns crosscut several classes in an object-oriented system. Moreover, several metrics have been proposed in order to assess object-oriented software quality attributes. However, these metrics do not cover the new abstractions and complexity dimensions introduced by the aspect paradigm. As a consequence, new metrics must be developed to assess aspectoriented systems quality attributes. Cohesion is considered as one of the most important software quality attributes. Cohesion refers to the degree of relatedness between members of a software component. We propose, in this paper, a new approach for aspect cohesion measurement based on dependencies analysis. We introduce several cohesion criteria taking into account aspects' features and capturing various dependencies between their members. We also propose a new aspect cohesion metric and compare it, using several case studies, to few existing aspect cohesion metrics.

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