Recent reviews of the literature indicate the need for empirical studies on cross-project
defect prediction (CPDP) that would allow aggregation of the evidence and improve …

Recent reviews of the literature indicate the need for empirical studies on cross-project
defect prediction (CPDP) that would allow aggregation of the evidence and improve …

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 …

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 …

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 …

Background: Cross project defect prediction (CPDP) recently gained considerable attention,
yet there are no systematic efforts to analyse existing empirical evidence. Objective: To …

Recently, most studies have considered the default value for hyper parameters of the
classification methods used by cross-project defect prediction (CPDP) methods. However, in …

Background. Recent years have seen an increasing interest in cross-project defect
prediction (CPDP), which aims to apply defect prediction models built on source projects to a …

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 …

Cross-project defect prediction (CPDP) forecasts flaws in a target project through defect
prediction models (DPM) trained by defect data of another project. However, CPDP has a …