Software defect prediction with semantic and structural information of codes based on Graph Neural Networks
出版年份 2022 全文链接
标题
Software defect prediction with semantic and structural information of codes based on Graph Neural Networks
作者
关键词
-
出版物
INFORMATION AND SOFTWARE TECHNOLOGY
Volume 152, Issue -, Pages 107057
出版商
Elsevier BV
发表日期
2022-08-31
DOI
10.1016/j.infsof.2022.107057
参考文献
相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。- Predicting the precise number of software defects: Are we there yet?
- (2022) Xiao Yu et al. INFORMATION AND SOFTWARE TECHNOLOGY
- CASMS: Combining clustering with attention semantic model for identifying security bug reports
- (2022) Xiaoxue Ma et al. INFORMATION AND SOFTWARE TECHNOLOGY
- Improving Stack Overflow question title generation with copying enhanced CodeBERT model and bi-modal information
- (2022) Fengji Zhang et al. INFORMATION AND SOFTWARE TECHNOLOGY
- ST-TLF: Cross-version defect prediction framework based transfer learning
- (2022) Yanyang Zhao et al. INFORMATION AND SOFTWARE TECHNOLOGY
- Evaluating network embedding techniques’ performances in software bug prediction
- (2021) Yu Qu et al. EMPIRICAL SOFTWARE ENGINEERING
- Simplified Deep Forest Model Based Just-in-Time Defect Prediction for Android Mobile Apps
- (2021) Kunsong Zhao et al. IEEE TRANSACTIONS ON RELIABILITY
- A compositional model for effort‐aware Just‐In‐Time defect prediction on android apps
- (2021) Kunsong Zhao et al. IET Software
- Leveraging developer information for efficient effort-aware bug prediction
- (2021) Yu Qu et al. INFORMATION AND SOFTWARE TECHNOLOGY
- An empirical study on the effectiveness of data resampling approaches for cross‐project software defect prediction
- (2021) Kwabena Ebo Bennin et al. IET Software
- Investigation on the stability of SMOTE-based oversampling techniques in software defect prediction
- (2021) Shuo Feng et al. INFORMATION AND SOFTWARE TECHNOLOGY
- An exploratory study of bug prediction at the method level
- (2021) Ran Mo et al. INFORMATION AND SOFTWARE TECHNOLOGY
- A Comprehensive Survey on Graph Neural Networks
- (2020) Zonghan Wu et al. IEEE Transactions on Neural Networks and Learning Systems
- A comprehensive comparative study of clustering-based unsupervised defect prediction models
- (2020) Zhou Xu et al. JOURNAL OF SYSTEMS AND SOFTWARE
- Improving text classification with weighted word embeddings via a multi-channel TextCNN model
- (2019) Bao Guo et al. NEUROCOMPUTING
- Cross Project Defect Prediction via Balanced Distribution Adaptation Based Transfer Learning
- (2019) Zhou Xu et al. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
- Improving defect prediction with deep forest
- (2019) Tianchi Zhou et al. INFORMATION AND SOFTWARE TECHNOLOGY
- Improving Ranking-Oriented Defect Prediction Using a Cost-Sensitive Ranking SVM
- (2019) Xiao Yu et al. IEEE TRANSACTIONS ON RELIABILITY
- LDFR: Learning deep feature representation for software defect prediction
- (2019) Zhou Xu et al. JOURNAL OF SYSTEMS AND SOFTWARE
- Using K-core Decomposition on Class Dependency Networks to Improve Bug Prediction Model's Practical Performance
- (2019) Yu Qu et al. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- MAHAKIL: Diversity Based Oversampling Approach to Alleviate the Class Imbalance Issue in Software Defect Prediction
- (2018) Kwabena Ebo Bennin et al. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- Cross-company defect prediction via semi-supervised clustering-based data filtering and MSTrA-based transfer learning
- (2018) Xiao Yu et al. SOFT COMPUTING
- Software defect prediction based on kernel PCA and weighted extreme learning machine
- (2018) Zhou Xu et al. INFORMATION AND SOFTWARE TECHNOLOGY
- Deep Semantic Feature Learning for Software Defect Prediction
- (2018) Song Wang et al. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- A Comparative Study to Benchmark Cross-project Defect Prediction Approaches
- (2017) Steffen Herbold et al. IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
- Empirical analysis of network measures for effort-aware fault-proneness prediction
- (2016) Wanwangying Ma et al. INFORMATION AND SOFTWARE TECHNOLOGY
- Empirical analysis of network measures for predicting high severity software faults
- (2016) Lin Chen et al. Science China-Information Sciences
- An empirical study on software defect prediction with a simplified metric set
- (2015) Peng He et al. INFORMATION AND SOFTWARE TECHNOLOGY
- Using Software Dependency to Bug Prediction
- (2013) Peng He et al. MATHEMATICAL PROBLEMS IN ENGINEERING
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