Software defect prediction is one of the most popular research topics in software
engineering. It aims to predict defect‐prone software modules before defects are discovered …

Software fault/defect prediction assists software developers to identify faulty constructs, such
as modules or classes, early in the software development life cycle. There are data mining …

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 …

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 …

Abstract Context: The application of Software Fault Prediction (SFP) in the software
development life cycle to predict the faulty class at the early stage has piqued the interest of …

Context: Software defect number prediction (SDNP) can rank the program modules
according to the prediction results and is helpful for the optimization of testing resource …

A fuzzy neural network (FNN) is an effective learning system that combines neural network
and fuzzy logic, which has achieved great success in nonlinear system modeling. However …

The performance of software defect prediction (SDP) models depend on the quality of
considered software features. Redundant features and irrelevant features may reduce the …

Abstract Machine learning-based Vulnerability detection is an active research topic in
software security. Different traditional machine learning-based and deep learning-based …

Cross-project defect prediction (CPDP) uses the labeled data from external source software
projects to compensate the shortage of useful data in the target project, in order to build a …