Fault handling in industry 4.0: definition, process and applications

H Webert, T Döß, L Kaupp, S Simons - Sensors, 2022 - mdpi.com
The increase of productivity and decrease of production loss is an important goal for modern
industry to stay economically competitive. For that, efficient fault management and quick …

Detecting refactoring type of software commit messages based on ensemble machine learning algorithms

D Al-Fraihat, Y Sharrab, AR Al-Ghuwairi, N Sbaih… - Scientific Reports, 2024 - nature.com
Refactoring is a well-established topic in contemporary software engineering, focusing on
enhancing software's structural design without altering its external behavior. Commit …

Classification of bugs in cloud computing applications using machine learning techniques

N Tabassum, A Namoun, T Alyas, A Tufail, M Taqi… - Applied Sciences, 2023 - mdpi.com
In software development, the main problem is recognizing the security-oriented issues within
the reported bugs due to their unacceptable failure rate to provide satisfactory reliability on …

Software defect prediction using a bidirectional LSTM network combined with oversampling techniques

NAA Khleel, K Nehéz - Cluster Computing, 2024 - Springer
Software defects are a critical issue in software development that can lead to system failures
and cause significant financial losses. Predicting software defects is a vital aspect of …

[HTML][HTML] Developing bug severity prediction models using word2vec

R Agrawal, R Goyal - International Journal of Cognitive Computing in …, 2021 - Elsevier
Bug tracking systems use repositories to keep track of the bugs to improve software quality.
A manual analysis of each bug and classifying it according to its severity is an …

Nature-based prediction model of bug reports based on Ensemble Machine Learning Model

SA Alsaedi, AY Noaman, AAA Gad-Elrab… - IEEE Access, 2023 - ieeexplore.ieee.org
In software development systems, the maintenance process of software systems attracted
the attention of researchers due to its importance in fixing the defects discovered in the …

Clebpi: Contrastive learning for bug priority inference

WY Wang, CH Wu, J He - Information and Software Technology, 2023 - Elsevier
Context: Automated bug priority inference (BPI) can reduce the time overhead of bug
triagers for priority assignments, improving the efficiency of software maintenance. Objective …

Risk levels classification of near-crashes in Naturalistic driving data

HAH Naji, Q Xue, N Lyu, X Duan, T Li - Sustainability, 2022 - mdpi.com
Identifying dangerous events from driving behavior data has become a vital challenge in
intelligent transportation systems. In this study, we compared machine and deep learning …

[PDF][PDF] An Assessment of Eclipse Bugs' Priority and Severity Prediction Using Machine Learning

MQ Shatnawi, B Alazzam - International Journal of …, 2022 - researchgate.net
The reliability and quality of software programs remains to be an important and challenging
aspect of software design. Software developers and system operators spend huge time on …

A novel vulnerability severity assessment method for source code based on a graph neural network

J Hao, S Luo, L Pan - Information and Software Technology, 2023 - Elsevier
Context Vulnerability severity assessment is an important part of vulnerability management
that can help security personnel determine the priority of vulnerability repair work. Objective …