INFORMATION CHANGE THE WORLD

International Journal of Information Engineering and Electronic Business(IJIEEB)

ISSN: 2074-9023 (Print), ISSN: 2074-9031 (Online)

Published By: MECS Press

IJIEEB Vol.6, No.1, Feb. 2014

Class Complexity Metric to Predict Understandability

Full Text (PDF, 1120KB), PP.69-76


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Author(s)

Kumar Rajnish

Index Terms

Complexity;Metrics;Object-Oriented;Classes;Understandability;Methods; Instance variables

Abstract

This paper presents a new class complexity metric of an Object-Oriented (OO) program which is used to predict the understandability of classes. The propose complexity metric is evaluated theoretically against Weyuker's properties to analyze the nature of metric and empirically evaluated against three small projects developed by Post Graduate (PG)/Under Graduate (UG) teams. Least Square Regression Analysis technique is performed to arrive at the result and find correlation coefficient of propose metric with the Degree of Understandability. The result indicates that the propose metric is a good predictor of understandability of classes. JHAWK TOOL (Java Code Metrics Tool) were used to evaluate the parameters values involved in propose metric and for analyzing the results of projects, Matlab6.1 and IBM SPSS software were used.

Cite This Paper

Kumar Rajnish,"Class Complexity Metric to Predict Understandability", IJIEEB, vol.6, no.1, pp.69-76, 2014. DOI: 10.5815/ijieeb.2014.01.08

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