Delivering high-quality software products is a challenging task. It needs proper coordination
from various teams in planning, execution, and testing. Many software products have high …

Recent years have experienced sustained focus in research on software defect prediction
that aims to predict the likelihood of software defects. Moreover, with the increased interest …

Context: Automated software defect prediction (SDP) methods are increasingly applied,
often with the use of machine learning (ML) techniques. Yet, the existing ML-based …

Several prediction approaches are contained in the arena of software engineering such as
prediction of effort, security, quality, fault, cost, and re-usability. All these prediction …

The agricultural sector and environmental safety both work hand in hand to promote
sustainability in important issues like soil health, plant nutrition, food safety, and security …

In order to improve software reliability, software defect prediction is applied to the process of
software maintenance to identify potential bugs. Traditional methods of software defect …

Software defect prediction can assist developers in finding potential bugs and reducing
maintenance cost. Traditional approaches usually utilize software metrics (Lines of Code …

Software Defect Prediction (SDP) models are built using software metrics derived from
software systems. The quality of SDP models depends largely on the quality of software …

Abstract Machine Learning (ML) algorithms have been increasingly replacing people in
several application domains—in which the majority suffer from data imbalance. In order to …

There is always a desire for defect-free software in order to maintain software quality for
customer satisfaction and to save testing expenses. As a result, we examined various known …