Cohesion and reuse in an object-oriented system
SSR '95 Proceedings of the 1995 Symposium on Software reusability
Software metrics (2nd ed.): a rigorous and practical approach
Software metrics (2nd ed.): a rigorous and practical approach
A cohesion measure for object-oriented classes
Software—Practice & Experience
Applying UML and Patterns: An Introduction to Object-Oriented Analysis and Design and the Unified Process
A Metrics Suite for Object Oriented Design
IEEE Transactions on Software Engineering
Chidamber and Kemerer's Metrics Suite: A Measurement Theory Perspective
IEEE Transactions on Software Engineering
OOMeter: A Software Quality Assurance Tool
CSMR '05 Proceedings of the Ninth European Conference on Software Maintenance and Reengineering
Software Component Certification: A Survey
EUROMICRO '05 Proceedings of the 31st EUROMICRO Conference on Software Engineering and Advanced Applications
Can Cohesion Predict Fault Density?
AICCSA '06 Proceedings of the IEEE International Conference on Computer Systems and Applications
Probabilistic size proxy for software effort prediction: A framework
Information and Software Technology
Hi-index | 0.00 |
Software metrics are essential for component certification and for the development of high quality software in general. Accordingly, research in the area of software metrics has been active and a wide range of metrics has been proposed. However, the variety of metrics proposed for measuring the same quality attribute suggests that there may be some sort of inconsistencies among the measurements computed using these metrics. In this paper, we report a case study considering class cohesion as a quality attribute of concern. We present the results of our empirical investigation to confirm that prominent object-oriented class cohesion metrics provide inconsistent measurements. We also present an analysis of the uncertainty that should be considered in these class cohesion measurements due to their inter-inconsistencies. Considering such uncertainty, we provide a framework for associating a probability distribution of error to the measurements computed by each metric; thus enabling the assessment of the degree of reliability of measurements of each metric when used to rank a set of classes with regard to their cohesion quality. The error probability distribution would be useful in practice where it is seldom feasible to use a large set of metrics and rather a single metric is used.