Cross-project defect prediction: a literature review
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 …
modules of a software project based on historical data collected from previous versions of …
Class imbalance reduction (CIR): a novel approach to software defect prediction in the presence of class imbalance
Software defect prediction (SDP) is the technique used to predict the occurrences of defects
in the early stages of software development process. Early prediction of defects will reduce …
in the early stages of software development process. Early prediction of defects will reduce …
Hybrid Model to Address Class Imbalance Problems in Software Defect Prediction using Advanced Computing Technique
One of the most well-known study areas in computer science is software defect prediction. It
aims to find defects occurring from the method level code, so it can be used to better …
aims to find defects occurring from the method level code, so it can be used to better …
A cross-project defect prediction model based on deep learning with self-attention
W Wen, R Zhang, C Wang, C Shen, M Yu… - IEEE …, 2022 - ieeexplore.ieee.org
Cross-project defect prediction technique is a hot topic in the field of software defect
research because of the huge difference in data distribution between source project and …
research because of the huge difference in data distribution between source project and …
Classification Algorithms for Software Defect Prediction: A Systematic Literature Review
MJ Hemández-Molinos… - 2021 9th …, 2021 - ieeexplore.ieee.org
Within Software Engineering, it is essential to build quality software. An obstacle to the after
mentioned are the defects that can be found in any phase of software development. That is …
mentioned are the defects that can be found in any phase of software development. That is …
[PDF][PDF] The effect of the imbalanced training dataset on the quality of classification of lithotypes via whole core photos
D Makienko, I Seleznev, I Safonov - Creative Commons License …, 2020 - ceur-ws.org
Nowadays machine learning methods play an important role in many industries. However,
the effectiveness of the predictive models depends on the quality of data sets used to train …
the effectiveness of the predictive models depends on the quality of data sets used to train …
Deep convolutional neural networks for age and gender estimation using an imbalanced dataset of human face images
İ Akgül - Neural Computing and Applications, 2024 - Springer
Automatic age and gender estimation provides an important information to analyze real-
world applications such as human–machine interaction, system access, activity recognition …
world applications such as human–machine interaction, system access, activity recognition …
Prevalence of machine learning techniques in software defect prediction
Abstract Software Defect Prediction (SDP) is a popular research area which plays an
important role for software quality. It works as an indicator of whether a software module is …
important role for software quality. It works as an indicator of whether a software module is …
[PDF][PDF] Effect of SMOTE Variants on Software Defect Prediction Classification Based on Boosting Algorithm
Detecting software defects early on is critical for avoiding significant financial losses.
However, building accurate software defect prediction models can be challenging due to …
However, building accurate software defect prediction models can be challenging due to …
Ensemble Based-Cross Project Defect Prediction
R **dal, A Ahmad, A Aditya - Ubiquitous Intelligent Systems: Proceedings …, 2022 - Springer
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 …
within-project defect prediction (WPDP) and cross project defect prediction (CPDP). In this …