Predicting software maintainability by using object-oriented metrics

dc.contributor.author	Dagpinar, Melis	en_US
dc.date.accessioned	2024-08-13T20:15:58Z
dc.date.available	2024-08-13T20:15:58Z
dc.date.copyright	2003	en_US
dc.date.issued	2003
dc.degree.department	Department of Computer Science
dc.degree.level	Master of Science M.Sc.	en
dc.description.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.
dc.format.extent	67 pages
dc.identifier.uri	https://hdl.handle.net/1828/17617
dc.rights	Available to the World Wide Web	en_US
dc.title	Predicting software maintainability by using object-oriented metrics	en_US
dc.type	Thesis	en_US

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