As software systems undergo escalating complexity, the identification of bugs and defects
becomes pivotal for ensuring seamless user experiences and averting potentially costly post …

Predicting faults in software aims to detect defects before the testing phase, allowing for
better resource allocation and high-quality software development, which is a requisite for …

Effective software defect prediction is a crucial aspect of software quality assurance,
enabling the identification of defective modules before the testing phase. This study aims to …

Software defect prediction plays a crucial role in enhancing software quality while achieving
cost savings in testing. Its primary objective is to identify and send only defective modules to …

Accurate prediction of defective software modules is of great importance for prioritizing
quality assurance efforts, reasonably allocating testing resources, reducing costs and …

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 …

Context Several issues hinder software defect data including redundancy, correlation,
feature irrelevance and missing samples. It is also hard to ensure balanced distribution …

At the latest, a lot of studies have been conducted to forecast software flaws and determine if
modules are defective or not, in order to build high-quality software at a low cost before …

Machine learning methods in software engineering are becoming increasingly important as
they can improve quality and testing efficiency by constructing models to predict defects in …

Machine learning is widely used to predict software defect-prone components, facilitating
testing and improving application quality. In a recent meta-analysis on binary classification …