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A systematic literature review on software defect prediction using artificial intelligence: Datasets, Data Validation Methods, Approaches, and Tools
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 …
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
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 …
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
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 …
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
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 …
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
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 …
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 …
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
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 …
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.
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 …
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
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 …
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 …
usability. However, testing software artifacts to find defects and fix them is time-consuming …