[HTML][HTML] Software defect prediction using supervised machine learning and ensemble techniques: a comparative study

A Alsaeedi, MZ Khan - Journal of Software Engineering and Applications, 2019 - scirp.org
An essential objective of software development is to locate and fix defects ahead of
schedule that could be expected under diverse circumstances. Many software development …

A study of dealing class imbalance problem with machine learning methods for code smell severity detection using PCA-based feature selection technique

RS Rao, S Dewangan, A Mishra, M Gupta - Scientific Reports, 2023 - nature.com
Detecting code smells may be highly helpful for reducing maintenance costs and raising
source code quality. Code smells facilitate developers or researchers to understand several …

[HTML][HTML] Multiple-classifiers in software quality engineering: Combining predictors to improve software fault prediction ability

F Yucalar, A Ozcift, E Borandag, D Kilinc - Engineering Science and …, 2020 - Elsevier
Software development projects require a critical and costly testing phase to investigate
efficiency of the resultant product. As the size and complexity of project increases, manual …

An empirical study of ensemble techniques for software fault prediction

SS Rathore, S Kumar - Applied Intelligence, 2021 - Springer
Previously, many researchers have performed analysis of various techniques for the
software fault prediction (SFP). Oddly, the majority of such studies have shown the limited …

Severity classification of code smells using machine-learning methods

S Dewangan, RS Rao, SR Chowdhuri, M Gupta - SN Computer Science, 2023 - Springer
Code smell detection can be very useful for minimizing maintenance costs and improving
software quality. Code smells help developers/programmers, researchers to subjectively …

A cloud-based software defect prediction system using data and decision-level machine learning fusion

S Aftab, S Abbas, TM Ghazal, M Ahmad, HA Hamadi… - Mathematics, 2023 - mdpi.com
This research contributes an intelligent cloud-based software defect prediction system using
data and decision-level machine learning fusion techniques. The proposed system detects …

Severity classification of software code smells using machine learning techniques: A comparative study

A Abdou, N Darwish - Journal of Software: Evolution and …, 2024 - Wiley Online Library
Code smell is a software characteristic that indicates bad symptoms in code design which
causes problems related to software quality. The severity of code smells must be measured …

[PDF][PDF] Data and Ensemble Machine Learning Fusion Based Intelligent Software Defect Prediction System.

S Abbas, S Aftab, MA Khan, TM Ghazal… - … , Materials & Continua, 2023 - researchgate.net
The software engineering field has long focused on creating highquality software despite
limited resources. Detecting defects before the testing stage of software development can …

Neural network based software defect prediction using genetic algorithm and particle swarm optimization

SI Ayon - 2019 1st International Conference on Advances in …, 2019 - ieeexplore.ieee.org
In the arena of software engineering, software defects prediction is one of the most attractive
research topics. Here the main task is to predict if there is any bug in the software or not. For …

Hyperparameter Optimization for Software Bug Prediction Using Ensemble Learning

D Al-Fraihat, Y Sharrab, AR Al-Ghuwairi… - IEEE …, 2024 - ieeexplore.ieee.org
Software Bug Prediction (SBP) is an integral process to the software's success that involves
predicting software bugs before their occurrence. Detecting software bugs early in the …