Research group on MACHINE LEARNING

Faculty of Mathematics and Computer Science, Babes-Bolyai University, Romania

1. Anamaria Briciu, Mihaiela Lupea, Gabriela Czibula, Istvan Gergely Czibula, Enriching the semantic representation of the source code with natural language-based features from comments for improving the performance of software defect prediction, 19th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2024), pp. 132-143 (WoS Proceedings)
2. Gabriela Czibula, Ioana-Gabriela Chelaru, Arthur Molnar, Istvan Gergely Czibula, PreSTyDe: Improving the performance of within-project defects prediction by learning to classify types of software faults19th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2024), pp. 214-225 (WoS Proceedings)
3. Gabriela Czibula, Andrei Mihai, Paul-Dumitru Orășan, Istvan-Gergely Czibula, Eugen Mihuleț, Sorin Burcea, SepConv-ens: An ensemble of separable convolution-based deep learning models for temporal weather radar echo extrapolation, 28th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2024), accepted for publication (WoS Proceedings)
4. Anamaria Briciu, Mihaiela Lupea, Gabriela Czibula, Istvan Gergely Czibula, Improved software defect prediction by combining natural language-based features from comments with conceptual features extracted from the source code, Communications in Computer and Information Science, Springer, 2024, to be published (indexed Scopus)
5. Ioana-Gabriela Chelaru, Gabriela Czibula, Arthur Molnar, Istvan Gergely Czibula, Enhancing the Performance of Software Defects Predictors using Defect Taxonomies, Communications in Computer and Information Science, Springer, 2024, to be published (indexed Scopus)