A statistical estimation of the coupling between object metric for open-source apps developed in Java

Abstract

The coupling between objects along with other metrics, is used for evaluating the faults, vulnerabilities, and other quality indicators in software systems, including open-source ones. It is known, that a coupling between objectsvalue between oneand fouris good. However, there are apps in Java for whichthe coupling between objectsmetric value atan app level is greater than four. That is why, in our opinion, the above interval for coupling between objectsneeds to be clarified for the app level. To find the recommended values for the coupling between objects mean of an app we have proposed to apply the confidence and prediction intervals. A coupling between objectsmean value of an app from the confidence interval is good since this interval indicates how reliable the estimate is for all apps. A coupling between objectsmean value higher than an upper bound of the prediction interval may indicate that some classes are too tightly coupled with other ones in the app. We have estimated the confidence and prediction intervals of the coupling between objectsmean using normalizing transformations for the data sample from one hundredopen-source apps developed in Java hosted on GitHub. Comparisonwith the coupling between objectsmean values of three popular open-source apps developed in Java illustrate the applicability of the proposed quality indicators in the form of the confidence and prediction intervals of the coupling between objectsmean.