Abstract
Dynamic metrics play a vital role to uncover features like dynamic binding, polymorphism, runtime cohesion, etc., whereas static metrics failed to capture these features of object-oriented (OO) programming languages. Many techniques exist in literature to perform dynamic software analysis, whereas aspect-oriented programming (AOP) has a transparent edge on other approaches. Therefore, in this paper, a new set of dynamic metrics for cohesion, complexity, and polymorphism measures of OO software is proposed. AspectJ tool evaluates these metrics by designing new aspects using aspect-oriented programming (AOP) on the Eclipse platform. Further, theoretical validation of proposed metrics is done based on Briand’s framework, and it is concluded that the proposed set of dynamic metrics satisfies all the properties of Briand’s framework and helps the software industry improve software quality.
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