Transfer Convolutional Neural Network for Cross-Project Defect Prediction
Applied Sciences, 2019 Cross-project defect prediction (CPDP) is a practical solution that allows software defect prediction (SDP) to be used earlier in the software lifecycle.
Shaojian Qiu +4 more
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Prediction of Cross Project Defects using Ensemble based Multinomial Classifier [PDF]
EAI Endorsed Transactions on Scalable Information Systems, 2020 BACKGROUND: The availability of defect related data of different projects leads to cross project defect prediction an open issue. Many studies have focused on analyzing and improving the performance of Cross project defect prediction.OBJECTIVE: The ...
Lipika Goel +3 more
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Cross-Project Defect Prediction Method Based on Instance Filtering and Transfer [PDF]
Jisuanji gongcheng, 2020 In cross-project software defect prediction,original datasets collected and labeled by humans are often corrupted by noisy,and large distribution differences exist between data of the source project and target project.To address the problem,this paper ...
FAN Guisheng, DIAO Xuyang, YU Huiqun, CHEN Liqiong
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Impact of Hyperparameter Optimization on Cross-Version Defect Prediction: An Empirical Study [PDF]
Jisuanji kexue yu tansuo, 2023 In the field of machine learning, hyperparameters are one of the key factors that affect prediction performance. Previous studies have shown that optimizing hyperparameters can improve the performance of inner-version defect prediction and cross-project ...
HAN Hui, YU Qiao, ZHU Yi
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A Cross-Project Defect Prediction Model Based on Deep Learning With Self-Attention
IEEE Access, 2022 Cross-project defect prediction technique is a hot topic in the field of software defect research because of the huge difference in data distribution between source project and target project.
Wanzhi Wen +6 more
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Deep Learning-Based Defect Prediction for Mobile Applications
Sensors, 2022 Smartphones have enabled the widespread use of mobile applications. However, there are unrecognized defects of mobile applications that can affect businesses due to a negative user experience. To avoid this, the defects of applications should be detected
Manzura Jorayeva +3 more
doaj +1 more source
Too trivial to test? An inverse view on defect prediction to identify methods with low fault risk [PDF]
PeerJ Computer Science, 2019 Background Test resources are usually limited and therefore it is often not possible to completely test an application before a release. To cope with the problem of scarce resources, development teams can apply defect prediction to identify fault-prone ...
Rainer Niedermayr +2 more
doaj +2 more sources
Using active learning selection approach for cross-project software defect prediction
Connection Science, 2022 Cross-project defect prediction (CPDP) technology can effectively ensure software quality, which plays an important role in software engineering. When encountering a newly developed project with insufficient training data, CPDP can be used to build ...
Wenbo Mi, Yong Li, Ming Wen, Youren Chen
doaj +1 more source
An Empirical Study on Software Defect Prediction Using CodeBERT Model
Applied Sciences, 2021 Deep learning-based software defect prediction has been popular these days. Recently, the publishing of the CodeBERT model has made it possible to perform many software engineering tasks.
Cong Pan, Minyan Lu, Biao Xu
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Dimensional Reduction on Cross Project Defect Prediction [PDF]
Journal of Physics: Conference Series, 2020 Abstract The complexity of the software can increase the possibility of defects. Defective software can cause high losses. The software containing defects can cause large losses. Most software developers don’t document their work properly so that making it difficult to analyse software development history data. The cross-project software
A Saifudin, Y Yulianti
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