Chao Ni

According to our database, Chao Ni authored at least 38 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Multitask-Based Evaluation of Open-Source LLM on Software Vulnerability.

Xin Yin, Chao Ni, Shaohua Wang

IEEE Trans. Software Eng., November, 2024

Enhancing Bug-Inducing Commit Identification: A Fine-Grained Semantic Analysis Approach.

Lingxiao Tang, Chao Ni, Qiao Huang, Lingfeng Bao

IEEE Trans. Software Eng., November, 2024

Federated Learning for Software Engineering: A Case Study of Code Clone Detection and Defect Prediction.

Yanming Yang, Xing Hu, Zhipeng Gao, Jinfu Chen, Chao Ni, Xin Xia, David Lo

IEEE Trans. Software Eng., February, 2024

Natural Is the Best: Model-Agnostic Code Simplification for Pre-trained Large Language Models.

Yan Wang, Xiaoning Li, Tien N. Nguyen, Shaohua Wang, Chao Ni, Ling Ding

Proc. ACM Softw. Eng., 2024

Enhancing Discriminative Tasks by Guiding the Pre-trained Language Model with Large Language Model's Experience.

Xin Yin, Chao Ni, Xiaodan Xu, Xinrui Li, Xiaohu Yang

CoRR, 2024

Learning-based Models for Vulnerability Detection: An Extensive Study.

Chao Ni, Liyu Shen, Xiaodan Xu, Xin Yin, Shaohua Wang

CoRR, 2024

Rectifier: Code Translation with Corrector via LLMs.

Xin Yin, Chao Ni, Tien N. Nguyen, Shaohua Wang, Xiaohu Yang

CoRR, 2024

CasModaTest: A Cascaded and Model-agnostic Self-directed Framework for Unit Test Generation.

Chao Ni, Xiaoya Wang, Liushan Chen, Dehai Zhao, Zhengong Cai, Shaohua Wang, Xiaohu Yang

CoRR, 2024

MegaVul: A C/C++ Vulnerability Dataset with Comprehensive Code Representation.

Chao Ni, Liyu Shen, Xiaohu Yang, Yan Zhu, Shaohua Wang

CoRR, 2024

Natural Is The Best: Model-Agnostic Code Simplification for Pre-trained Large Language Models.

Yan Wang, Xiaoning Li, Tien Nguyen, Shaohua Wang, Chao Ni, Ling Ding

CoRR, 2024

MegaVul: A C/C++ Vulnerability Dataset with Comprehensive Code Representations.

Chao Ni, Liyu Shen, Xiaohu Yang, Yan Zhu, Shaohua Wang

Proceedings of the 21st IEEE/ACM International Conference on Mining Software Repositories, 2024

ThinkRepair: Self-Directed Automated Program Repair.

Xin Yin, Chao Ni, Shaohua Wang, Zhenhao Li, Limin Zeng, Xiaohu Yang

Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis, 2024

2023

Boosting multi-objective just-in-time software defect prediction by fusing expert metrics and semantic metrics.

Xiang Chen, Hongling Xia, Wenlong Pei, Chao Ni, Ke Liu

J. Syst. Softw., December, 2023

Code-line-level Bugginess Identification: How Far have We Come, and How Far have We Yet to Go?

Zhaoqiang Guo, Shiran Liu, Xutong Liu, Wei Lai, Mingliang Ma, Xu Zhang, Chao Ni, Yibiao Yang, Yanhui Li, Lin Chen, Guoqiang Zhou, Yuming Zhou

ACM Trans. Softw. Eng. Methodol., July, 2023

Automatic Identification of Crash-inducing Smart Contracts.

Chao Ni, Cong Tian, Kaiwen Yang, David Lo, Jiachi Chen, Xiaohu Yang

Proceedings of the IEEE International Conference on Software Analysis, 2023

C³: Code Clone-Based Identification of Duplicated Components.

Yanming Yang, Ying Zou, Xing Hu, David Lo, Chao Ni, John C. Grundy, Xin Xia

Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023

Distinguishing Look-Alike Innocent and Vulnerable Code by Subtle Semantic Representation Learning and Explanation.

Chao Ni, Xin Yin, Kaiwen Yang, Dehai Zhao, Zhenchang Xing, Xin Xia

Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023

Boosting Just-in-Time Defect Prediction with Specific Features of C/C++ Programming Languages in Code Changes.

Chao Ni, Xiaodan Xu, Kaiwen Yang, David Lo

Proceedings of the 20th IEEE/ACM International Conference on Mining Software Repositories, 2023

Unifying Defect Prediction, Categorization, and Repair by Multi-Task Deep Learning.

Chao Ni, Kaiwen Yang, Yan Zhu, Xiang Chen, Xiaohu Yang

Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering, 2023

Function-Level Vulnerability Detection Through Fusing Multi-Modal Knowledge.

Chao Ni, Xinrong Guo, Yan Zhu, Xiaodan Xu, Xiaohu Yang

Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering, 2023

FVA: Assessing Function-Level Vulnerability by Integrating Flow-Sensitive Structure and Code Statement Semantic.

Chao Ni, Liyu Shen, Wei Wang, Xiang Chen, Xin Yin, Lexiao Zhang

Proceedings of the 31st IEEE/ACM International Conference on Program Comprehension, 2023

An Empirical Study of the Apache Voting Process on Open Source Community Governance.

Jisheng Wang, Lingfeng Bao, Chao Ni

Proceedings of the 14th Asia-Pacific Symposium on Internetware, 2023

2022

Revisiting Supervised and Unsupervised Methods for Effort-Aware Cross-Project Defect Prediction.

Chao Ni, Xin Xia, David Lo, Xiang Chen, Qing Gu

IEEE Trans. Software Eng., 2022

Just-In-Time Defect Prediction on JavaScript Projects: A Replication Study.

Chao Ni, Xin Xia, David Lo, Xiaohu Yang, Ahmed E. Hassan

ACM Trans. Softw. Eng. Methodol., 2022

Defect Identification, Categorization, and Repair: Better Together.

Chao Ni, Kaiwen Yang, Xin Xia, David Lo, Xiang Chen, Xiaohu Yang

CoRR, 2022

The best of both worlds: integrating semantic features with expert features for defect prediction and localization.

Chao Ni, Wei Wang, Kaiwen Yang, Xin Xia, Kui Liu, David Lo

Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022

Detecting and Defending CSRF at API-Level.

Shun Wang, Chao Ni, Jianbo Wang, Changhai Nie

Proceedings of the IEEE International Symposium on Software Reliability Engineering Workshops, 2022

2021

Revisiting heterogeneous defect prediction methods: How far are we?

Xiang Chen, Yanzhou Mu, Ke Liu, Zhanqi Cui, Chao Ni

Inf. Softw. Technol., 2021

2020

Do different cross-project defect prediction methods identify the same defective modules?

Xiang Chen, Yanzhou Mu, Yubin Qu, Chao Ni, Meng Liu, Tong He, Shangqing Liu

J. Softw. Evol. Process., 2020

Revisiting Dependence Cluster Metrics based Defect Prediction.

Qiguo Huang, Xiang Chen, Zhengliang Li, Chao Ni, Qing Gu

Proceedings of the 32nd International Conference on Software Engineering and Knowledge Engineering, 2020

2019

Multitask defect prediction.

Chao Ni, Xiang Chen, Xin Xia, Qing Gu, Yingquan Zhao

J. Softw. Evol. Process., 2019

An empirical study on pareto based multi-objective feature selection for software defect prediction.

Chao Ni, Xiang Chen, Fangfang Wu, Yuxiang Shen, Qing Gu

J. Syst. Softw., 2019

Software defect number prediction: Unsupervised vs supervised methods.

Xiang Chen, Dun Zhang, Yingquan Zhao, Zhanqi Cui, Chao Ni

Inf. Softw. Technol., 2019

Revisiting Heterogeneous Defect Prediction: How Far Are We?

Xiang Chen, Yanzhou Mu, Chao Ni, Zhanqi Cui

CoRR, 2019

Multi-project Regression based Approach for Software Defect Number Prediction.

Qiguo Huang, Chao Ni, Xiang Chen, Qing Gu, Kaibo Cao

Proceedings of the 31st International Conference on Software Engineering and Knowledge Engineering, 2019

2017

A Cluster Based Feature Selection Method for Cross-Project Software Defect Prediction.

Chao Ni, Wangshu Liu, Xiang Chen, Qing Gu, Daoxu Chen, George Q. Huang

J. Comput. Sci. Technol., 2017

FeSCH: A Feature Selection Method using Clusters of Hybrid-data for Cross-Project Defect Prediction.

Chao Ni, Wangshu Liu, Qing Gu, Xiang Chen, Daoxu Chen

Proceedings of the 41st IEEE Annual Computer Software and Applications Conference, 2017

2009

Bottom-up fabrication of special parylene films based on selective growth on Au-coated surface.

Yi Zhou, Fei Ding, Chao Ni, Wei Wang, Wengang Wu

Proceedings of the 4th IEEE International Conference on Nano/Micro Engineered and Molecular Systems, 2009