… that the best classification accuracy for Decision Tree was … of code smell prediction rules
were extracted using Decision … Finally, code smell prediction rules were generated using DT. …

… They generated four code smell datasets and 74 Java … code smell and different features
that is software metrics. The research provides decision rules of Code Smell, for any code smell …

… In this paper, we proposed a code smell prediction approach … , we use three kinds of
tree-based algorithms: Decision Tree, … In the Long Method dataset, the prediction rules to predict …

… The best results have been achieved by using decision tree … extracted the prediction rules
for each type of code smell according … A large set of software metrics are used as independent …

… and software metrics. In a … Experimental results obtained by applying the Decision tree
algorithm to the four code smell … Generating Code-Smell Prediction Rules Using Decision …

… smells and with code smell-related metrics. We use both code smell metrics extracted via …
technical analyses of the software projects, and later, the tool generates an output in the …

… for each code smell [9]; (ii) these techniques generate different … source code metrics of 100
JavaScript projects using InCode … tive model of simple decision trees that are not very well …

… and deep learning approaches with the software metrics. … They found that the decision tree
algorithm achieved better … Extraction of Prediction Rules of Code Smell using Decision Tree …

… software metrics and the likelihood of a class to change in the future. Afterwards, they build
a change prediction … -fold validation, required the generation of 1,000 confusion matrices for …

… Tools do not consider essential software metrics like size, … machine learning algorithms are
strategically generated to reach … forest use predictions from these decision trees created from …