Software defect prediction using ensemble learning: A systematic literature review

F Matloob, TM Ghazal, N Taleb, S Aftab… - IEEe …, 2021 - ieeexplore.ieee.org
Recent advances in the domain of software defect prediction (SDP) include the integration of
multiple classification techniques to create an ensemble or hybrid approach. This technique …

Evaluating strength properties of Eco-friendly Seashell-Containing Concrete: Comparative analysis of hybrid and ensemble boosting methods based on …

B Sadaghat, SA Ebrahimi, O Souri, MY Niar… - … Applications of Artificial …, 2024 - Elsevier
In the dynamic field of concrete technology, a discernible shift towards sustainability is
evident, prompted by the need to minimize reliance on natural resources and reduce the …

Comparative performance of eight ensemble learning approaches for the development of models of slope stability prediction

S Lin, H Zheng, B Han, Y Li, C Han, W Li - Acta Geotechnica, 2022 - Springer
Slope engineering is a complex nonlinear system. It is difficult to respond with a high level of
precision and efficiency requirements for stability assessment using conventional theoretical …

[HTML][HTML] A survey on machine learning techniques applied to source code

T Sharma, M Kechagia, S Georgiou, R Tiwari… - Journal of Systems and …, 2024 - Elsevier
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …

A survey on machine learning techniques for source code analysis

T Sharma, M Kechagia, S Georgiou, R Tiwari… - arxiv preprint arxiv …, 2021 - arxiv.org
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …

Software defect prediction analysis using machine learning techniques

A Khalid, G Badshah, N Ayub, M Shiraz, M Ghouse - Sustainability, 2023 - mdpi.com
There is always a desire for defect-free software in order to maintain software quality for
customer satisfaction and to save testing expenses. As a result, we examined various known …

Impact of hyperparameter tuning on machine learning models in stock price forecasting

KE Hoque, H Aljamaan - IEEE Access, 2021 - ieeexplore.ieee.org
Stock price forecasting has been reported as a challenging task in the scientific and financial
communities due to stock prices' nonlinear and dynamic nature. Machine learning models …

A feature selection model for software defect prediction using binary Rao optimization algorithm

K Thirumoorthy - Applied Soft Computing, 2022 - Elsevier
In this digital world, using software has become an important part of daily life and business.
The software must be rigorously tested in order to avert a financial crisis. The defect-free …

Software defect prediction using an intelligent ensemble-based model

M Ali, T Mazhar, Y Arif, S Al-Otaibi, YY Ghadi… - IEEe …, 2024 - ieeexplore.ieee.org
Software defect prediction plays a crucial role in enhancing software quality while achieving
cost savings in testing. Its primary objective is to identify and send only defective modules to …

Enhancing software defect prediction: a framework with improved feature selection and ensemble machine learning

M Ali, T Mazhar, A Al-Rasheed, T Shahzad… - PeerJ Computer …, 2024 - peerj.com
Effective software defect prediction is a crucial aspect of software quality assurance,
enabling the identification of defective modules before the testing phase. This study aims to …