Code smells detection helps in improving understandability and maintainability of software
while reducing the chances of system failure. In this study, six machine learning algorithms
have been applied to predict code smells. For this purpose, four code smell datasets (God-
class, Data-class, Feature-envy, and Long-method) are considered which are generated
from 74 open-source systems. To evaluate the performance of machine learning algorithms
on these code smell datasets, 10-fold cross validation technique is applied that predicts the …

Code smells detection helps in improving understandability and maintainability of software
while reducing the chances of system failure. In this study, six machine learning algorithms
have been applied to predict code smells. For this purpose, four code smell datasets (God-
class, Data-class, Featureenvy, and Long-method) are considered which are generated from
74 open-source systems. To evaluate the performance of machine learning algorithms on
these code smell datasets, 10-fold cross validation technique is applied that predicts the …