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

CONTEXT: Software metrics may be used in fault prediction models to improve software
quality by predicting fault location. OBJECTIVE: This paper aims to identify software metrics …

Defect prediction is proposed to assist practitioners effectively prioritize limited Software
Quality Assurance (SQA) resources on the most risky files that are likely to have post-release …

Software defect prediction is one of the most active research areas in software engineering.
We can build a prediction model with defect data collected from a software project and …

App Stores, such as Google Play or the Apple Store, allow users to provide feedback on
apps by posting review comments and giving star ratings. These platforms constitute a …

Highly imbalanced data typically make accurate predictions difficult. Unfortunately, software
defect datasets tend to have fewer defective modules than non-defective modules. Synthetic …

Defect prediction models are a well-known technique for identifying defect-prone files or
packages such that practitioners can allocate their quality assurance efforts (eg, testing and …

Many software defect prediction approaches have been proposed and most are effective in
within-project prediction settings. However, for new projects or projects with limited training …

Defect prediction models help software quality assurance teams to effectively allocate their
limited resources to the most defect-prone software modules. A variety of classification …

Cross-Project Defect Prediction (CPDP) as a means to focus quality assurance of software
projects was under heavy investigation in recent years. However, within the current state-of …