Results 271 to 280 of about 86,307 (298)

COSTE: Complexity-based OverSampling TEchnique to alleviate the class imbalance problem in software defect prediction

Information and Software Technology, 2021
Context: Generally, there are more non-defective instances than defective instances in the datasets used for software defect prediction (SDP), which is referred to as the class imbalance problem.
Shuo Feng, J. Keung, Xiao Yu, Yan Xiao, K. Bennin, M. Kabir, Miao Zhang   +6 more
semanticscholar   +1 more source

Software Defect Prediction Based on Gated Hierarchical LSTMs

IEEE Transactions on Reliability, 2021
Software defect prediction, aimed at assisting software practitioners in allocating test resources more efficiently, predicts the potential defective modules in software products.
Hao Wang, Weiyuan Zhuang, Xiaofang Zhang
semanticscholar   +1 more source

Software Defect Prediction Based on Deep Representation Learning of Source Code From Contextual Syntax and Semantic Graph

IEEE Transactions on Reliability
Software defect prediction approaches play an essential role in the software development life cycle to help developers predict defects early, thus, preventing wasted time and effort.
Ahmed Abdu, Zhengjun Zhai, Hakim A. Abdo, Redhwan Algabri   +3 more
semanticscholar   +1 more source

Software Defect Prediction Approach Based on a Diversity Ensemble Combined With Neural Network

IEEE Transactions on Reliability
There is a severe class imbalance problem in defect datasets, with nondefective data dominating the distribution, making it easy to generate inaccurate software defect prediction models.
Jinfu Chen, Jiaping Xu, Saihua Cai, Xiaoli Wang, Haibo Chen, Zhehao Li   +5 more
semanticscholar   +1 more source

Defect-Introducing Defect Prediction Testing

IEEE International Conference on Software Quality, Reliability and Security Companion
Machine learning (ML) innovations have significantly advanced the field of defect prediction in software development, offering the potential for automated error detection across vast codebases.
Fanjiang Xu, Zeyu Sun
semanticscholar   +1 more source

Interpretability application of the Just-in-Time software defect prediction model

Journal of Systems and Software, 2022
Wei Zheng, Tianren Shen, Xiang Chen, Peiran Deng   +3 more
exaly   +2 more sources

Software defect prediction ensemble learning algorithm based on adaptive variable sparrow search algorithm

International Journal of Machine Learning and Cybernetics, 2023
Yu Tang, Q. Dai, Mengyuan Yang, Tony Du, Lifang Chen   +4 more
semanticscholar   +1 more source

Software defect prediction using hybrid techniques: a systematic literature review

Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2023
R. Malhotra, Sonali Chawla, Anjali Sharma   +2 more
semanticscholar   +1 more source

Software defect prediction employing BiLSTM and BERT-based semantic feature

Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2022
M. Uddin, Bixin Li, Z. Ali, P. Kefalas, Inayat Khan, Islam Zada   +5 more
semanticscholar   +1 more source

A Systematic Survey of Just-in-Time Software Defect Prediction

ACM Computing Surveys, 2023
Yunhua Zhao, Kostadin Damevski, Hui Chen   +2 more
exaly