Information flow metrics analysis in object oriented programming and metrics validation process by RAA algorithm

Abstract

Transparent data flow metrics and control flow metrics had no main concern which to be handled by a compiler. Nowadays similar hardware and multithreaded coding is increased. Consequently, both data flow and control flow become more important in analyses the reusability and maintainability. The present analysis of source code and the ability of metrics are incompetent to predict the actual amount of information flow complexity in the modules. In this work, object oriented metric IF-C focuses on the improved information flow complexity estimation method, which is used to evaluate the data flows in object oriented source code and decrease the effort of maintainability and reusability. The object oriented information flow complexity incorporates various internal and external flows in object orientation. The adequacy of software metrics is validated by the rule accuracy algorithm which is based on rule induction technique. The technique applied in the software metrics dataset that has been selected using fitness proportionate selection algorithm. The competence and efficacy of the software metrics have verified by the predefined rules. The rules have if and then clause which hold metrics adequacy standards.