Analyzing and Identifying Potential Areas of Improvement in Object Oriented Metrics

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Object oriented programming has taken a major role in the development of large, complex systems. Software quality of these systems is of prime importance to many stakeholders. One approach is to use object oriented metrics to predict and control the quality of these systems. Many metrics have been proposed in the literature to monitor specific object oriented traits. However due to the sheer numbers of metrics available it becomes a difficult task to pick and choose relevant metrics for applying to specific needs. This motivated us to analyze the object oriented metrics that have been proposed and group them based on various factors. Our analysis would help developers and managers to pick the right choice of metrics for their need. It will also help researchers of object oriented metrics to identify potential areas which they could focus upon
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Object Oriented Metrics; Software Quality; Cohesion; Coupling; Inheritance; Polymorphism; Data Encapsulation; Data Abstraction

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