Software defect prediction is a crucial area of study focused on enhancing software quality
and cutting down on software upkeep expenses. Cross Project Defect Prediction (CPDP) is …

Existing models on defect prediction are trained on historical limited data which has been
studied from a variety of pioneering and researchers. Cross-project defect prediction, which …

Software Defect Prediction (SDP) is crucial for enhancing software quality and minimizing
issues after release. The advent of machine learning, particularly in Cross-Project Defect …

The feasibility of building a software defect prediction (SDP) model in the absence of
previous records has been increased by the introduction of the Cross-Project Defect …

Background: Software defect prediction models aim at identifying the potential faulty
modules of a software project based on historical data collected from previous versions of …

Software defect prediction is critical for improving software quality and reducing
maintenance costs. In recent years, Cross-Project software defect prediction has garnered …

Abstract In Software Testing, there are typically two ways to predict defects in the software—
within-project defect prediction (WPDP) and cross project defect prediction (CPDP). In this …

Ensuring software quality, when every industry depends on software, is of utmost
importance. Software bugs can have grave consequences and thus identifying and fixing …

Software defect prediction (SDP) is the process of detecting fault-prone classes or modules
in a software system. It helps in allocating resources before the testing phase more …

In the traditional software defect prediction methodology, the historical record (dataset) of the
same project is partitioned into training and testing data. In a practical situation where the …