Context: Automated software defect prediction (SDP) methods are increasingly applied,
often with the use of machine learning (ML) techniques. Yet, the existing ML-based …

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 (SDP) is the process of detecting defectprone software modules
before the testing stage. The testing stage in the software development life cycle is …

Software analysis and prediction system development is the significant and much-needed
field of software testing in software engineering. The automatic software predictors analyze …

Defect prediction is a technique introduced to optimize the testing phase of the software
development pipeline by predicting which components in the software may contain defects …

Cross‐project defect prediction (CPDP) is a mainstream method estimating the most defect‐
prone components of software with limited historical data. Several studies investigate how …

Software defect prediction is the process of identification of defects early in the life cycle so
as to optimize the testing resources and reduce maintenance efforts. Defect prediction works …

Software defect prediction involves predicting which components in a software program, like
classes or functions, are likely to have defects, based on metrics that describe those …

Software defect prediction is the process of identifying defective files and modules that need
rigorous testing. In the literature, several secondary studies including systematic reviews …

1. Background Software defects might be the cause of several problems during software
maintenance or development, they could lead to major damage and important loss of …