Recent advances in the domain of software defect prediction (SDP) include the integration of
multiple classification techniques to create an ensemble or hybrid approach. This technique …

Artificial Intelligence (AI) has become a core feature of today's real-world applications,
making it a trending topic within the software engineering (SE) community. The rise in the …

Ensemble learning combines a series of base classifiers and the final result is assigned to
the corresponding class by using a majority voting mechanism. However, the base …

An essential objective of software development is to locate and fix defects ahead of
schedule that could be expected under diverse circumstances. Many software development …

Defect prediction at early stages of software development life cycle is a crucial activity of
quality assurance process and has been broadly studied in the last two decades. The early …

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 …

Ensemble learning is an algorithm that utilizes various types of classification models. This
algorithm can enhance the prediction efficiency of component models. However, the …

Abstract Software Defect Prediction (SDP) is a major research field in the software
development life cycle. The accurate SDP would assist software developers and engineers …

An accurate prediction of bugs in software projects can help in improving software projects'
quality. A simple majority voting (SMV) ensemble is an effective technique for bug prediction …

Software bugs (or malfunctions) pose a serious threat to software developers with many
known and unknown bugs that may be vulnerable to computer systems, demanding new …