A systematic literature review on software defect prediction using artificial intelligence: Datasets, Data Validation Methods, Approaches, and Tools

J Pachouly, S Ahirrao, K Kotecha… - … Applications of Artificial …, 2022 - Elsevier
Delivering high-quality software products is a challenging task. It needs proper coordination
from various teams in planning, execution, and testing. Many software products have high …

Software fault prediction using data mining, machine learning and deep learning techniques: A systematic literature review

I Batool, TA Khan - Computers and Electrical Engineering, 2022 - Elsevier
Software fault/defect prediction assists software developers to identify faulty constructs, such
as modules or classes, early in the software development life cycle. There are data mining …

BPDET: An effective software bug prediction model using deep representation and ensemble learning techniques

SK Pandey, RB Mishra, AK Tripathi - Expert Systems with Applications, 2020 - Elsevier
In software fault prediction systems, there are many hindrances for detecting faulty modules,
such as missing values or samples, data redundancy, irrelevance features, and correlation …

Empirical evaluation of the performance of data sampling and feature selection techniques for software fault prediction

SC Rathi, S Misra, R Colomo-Palacios… - Expert Systems with …, 2023 - Elsevier
Abstract Context: The application of Software Fault Prediction (SFP) in the software
development life cycle to predict the faulty class at the early stage has piqued the interest of …

Ensemble machine learning paradigms in software defect prediction

T Sharma, A Jatain, S Bhaskar, K Pabreja - Procedia Computer Science, 2023 - Elsevier
Predicting faults in software aims to detect defects before the testing phase, allowing for
better resource allocation and high-quality software development, which is a requisite for …

A novel four-way approach designed with ensemble feature selection for code smell detection

I Kaur, A Kaur - IEEE Access, 2021 - ieeexplore.ieee.org
Purpose: Code smells are residuals of technical debt induced by the developers. They
hinder evolution, adaptability and maintenance of the software. Meanwhile, they are very …

Software fault prediction with imbalanced datasets using SMOTE-Tomek sampling technique and Genetic Algorithm models

M Gupta, K Rajnish, V Bhattacharjee - Multimedia Tools and Applications, 2024 - Springer
Over the years, there has been a considerable discussion regarding machine learning (ML)
techniques to forecast software faults. It can be challenging to choose a suitable machine …

[PDF][PDF] Influence of Class Imbalance and Resampling on Classification Accuracy of Chronic Kidney Disease Detection.

AO Salau, ED Markus, TA Assegie… - Mathematical …, 2023 - academia.edu
Accepted: 22 October 2022 Chronic kidney disease is one of the leading causes of death
around the world. Early detection of chronic kidney disease is crucial to the reduction of …

DBOS_US: a density-based graph under-sampling method to handle class imbalance and class overlap issues in software fault prediction

K Bhandari, K Kumar, AL Sangal - The Journal of Supercomputing, 2024 - Springer
Improving software quality by predicting faults during the early stages of software
development is a primary goal of software fault prediction (SFP). Various machine learning …

Software defects prediction at method level using ensemble learning techniques

AM Ibrahim, H Abdelsalam… - International Journal of …, 2023 - journals.ekb.eg
Creating error-free software artifacts is essential to increase software quality and potential re-
usability. However, testing software artifacts to find defects and fix them is time-consuming …