Software fault prediction (SFP) aims to improve software quality with a possible minimum
cost and time. Various machine learning models have been proposed in the past for …

Previously, many researchers have performed analysis of various techniques for the
software fault prediction (SFP). Oddly, the majority of such studies have shown the limited …

Imbalance learning is a challenging task for most standard machine learning algorithms.
The Synthetic Minority Oversampling Technique (SMOTE) is a well-known preprocessing …

Abstract The object of Software Defect Prediction (SDP) is to identify modules that are prone
to defect. This is achieved by training prediction models with datasets obtained by mining …

Software fault prediction is a key area in the field of software engineering. Fault can occur in
any stage of software development but if it is not correctly identified and removed, it may …

This paper investigates the potential of COVID-19 detection using cough, breathing, and
voice patterns. Speech-based features, such as MFCC, zero crossing rate, spectral centroid …

Software fault prediction is the process of identifying the software modules which are more
likely to be defective or faulty before the testing phase of software development life-cycle …

Class imbalance is the major hurdle for machine learning-based systems. Data set is the
backbone of machine learning and must be studied to handle the class imbalance. The …

Software is becoming more complex, and lengthier in size, and needs to be updated on a
time basis. But the constant change in codes has a high chance of arising faults that …

The concern about the software development and maintenance costs increased the interest
in defect predictions. It is possible to create classifiers capable of identifying software …