… analyze the performance of supervised machine learning techniques on software defect
prediction by using NASA … Machine learning techniques used in this research are: Naïve Bayes (…

… ML techniques can potentially … efficiency of defect prediction by automatically learning
patterns from large amounts of data. Performance evaluation is critical in applying ML techniques …

… Software Defect Prediction is a sub-branch that … study, five of machine learning classification
algorithms were conducted on with PYTHON programming language on defect prediction …

… NASA Data Program provided five separate datasets for this investigation. For performance
evaluation, accuracy, AUC and other metrics are used. A mixed strategy is adopted in this …

… Dataset used in this work was obtained from a publicly available repository from NASA Promise
[… This paper evaluated software defect prediction accuracy using different ML algorithms. …

… In order to improve accuracy of software defects predictions, this study analyses five NASA
… monitoring and performance analysis; operations research models and bibliometric network …

… The public NASA datasets, which consist of information related to several NASA projects,
deployed in this research for evaluation. In recent years, these datasets have drawn a great …

… It comprises of three subsections ie software metrics, datasets and performance evaluation
… achieved from NASA MDP. The use of NN for software defect prediction is encouraging [xxxix…

… discriminate analysis and classification tree. They investigated several data mining algorithms
for software fault prediction on public NASA datasets and they used method level metrics. …

… KEEL tool and validated using k fold cross validation technique. Datasets used in this …
NASA Promise dataset repository. Seven datasets were selected for defect prediction analysis. …