Kunsong Zhao

Orcid: 0000-0001-9886-0460

According to our database1, Kunsong Zhao authored at least 18 papers between 2020 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2023
Detecting multi-type self-admitted technical debt with generative adversarial network-based neural networks.
Inf. Softw. Technol., June, 2023

The impact of class imbalance techniques on crashing fault residence prediction models.
Empir. Softw. Eng., March, 2023

VGX: Large-Scale Sample Generation for Boosting Learning-Based Software Vulnerability Analyses.
CoRR, 2023

Extended Abstract of Graph4Web: A Relation-Aware Graph Attention Network for Web Service Classification.
Proceedings of the IEEE International Conference on Software Analysis, 2023

DeepInfer: Deep Type Inference from Smart Contract Bytecode.
Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023

2022
Effort-Aware Just-in-Time Bug Prediction for Mobile Apps Via Cross-Triplet Deep Feature Embedding.
IEEE Trans. Reliab., 2022

Dual Gated Graph Attention Networks with Dynamic Iterative Training for Cross-Lingual Entity Alignment.
ACM Trans. Inf. Syst., 2022

<i>Graph4Web</i>: A relation-aware graph attention network for web service classification.
J. Syst. Softw., 2022

Exploiting gated graph neural network for detecting and explaining self-admitted technical debts.
J. Syst. Softw., 2022

A compositional model for effort-aware Just-In-Time defect prediction on android apps.
IET Softw., 2022

Effort-aware cross-project just-in-time defect prediction framework for mobile apps.
Frontiers Comput. Sci., 2022

2021
Simplified Deep Forest Model Based Just-in-Time Defect Prediction for Android Mobile Apps.
IEEE Trans. Reliab., 2021

A comprehensive investigation of the impact of feature selection techniques on crashing fault residence prediction models.
Inf. Softw. Technol., 2021

Just-in-time defect prediction for Android apps via imbalanced deep learning model.
Proceedings of the SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing, 2021

Predicting Crash Fault Residence via Simplified Deep Forest Based on A Reduced Feature Set.
Proceedings of the 29th IEEE/ACM International Conference on Program Comprehension, 2021

2020
Imbalanced metric learning for crashing fault residence prediction.
J. Syst. Softw., 2020

Simplified Deep Forest Model based Just-In-Time Defect Prediction for Android Mobile Apps.
Proceedings of the 20th IEEE International Conference on Software Quality, 2020

A Contextual Alignment Enhanced Cross Graph Attention Network for Cross-lingual Entity Alignment.
Proceedings of the 28th International Conference on Computational Linguistics, 2020


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