Abstract
Nowadays software metrics are used for detecting software quality, including RFC (response for a class) at the app level. However, only their average values (point estimates) are known for detecting the quality of software systems. Also, it is known that RFC depends on the CBO (coupling between object classes) and WMC (weighted methods per class) metrics. That is why we propose a technique to detect the software quality of applications (apps) based on the confidence and prediction intervals of nonlinear regression for RFC depending on CBO and WMC predictors. According to this technique, the RFC value for the app inside the confidence interval indicates its medium quality. The RFC value for the app between the borders of the confidence and prediction intervals indicates its high quality. The RFC value for the app higher than the upper border of the prediction interval indicates its low quality. We give an example of using a proposed technique to detect the software quality of open-source apps developed in Java.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call