Predicting software maintainability by using object-oriented metrics
Date
2003
Authors
Dagpinar, Melis
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Abstract
This thesis presents an empirical study designed for measuring the predictive power of object-oriented metrics for determining maintainability of object-oriented software systems. The study applies different kinds of measures applied to two selected systems. These measures can be grouped into four categories: size, inheritance, cohesion, and coupling. Unlike most related studies, indirect coupling has also been taken into account in order to analyze its usefulness. Maintainability characteristics have been derived from the systems' repository logs by categorizing the logs using three groups: perfective/adaptive, corrective, and preventive. Through analyzing the relationships between metrics and maintainability characteristics by using different statistical techniques, we have found that size and import direct coupling measures are significant predictors for measuring maintainability of a class while inheritance, cohesion, and indirect/export coupling measures are not.