Zhou Yang

According to our database, Zhou Yang authored at least 73 papers between 2019 and 2026.

Collaborative distances:

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

2026

YourCoLo: Leveraging One-to-Many Relationships and Inter-Code Connections for User Review-Based Code Localization.

Kuo Chi, Changan Niu, Zhou Yang, Chuanyi Li, Yi Feng, Jidong Ge, Bin Luo, David Lo, Vincent Ng

ACM Trans. Softw. Eng. Methodol., June, 2026

LLMs Are Not a Silver Bullet: A Case Study on Software Fairness.

Xinyue Li, Sixuan Li, Ying Xiao, Jie M. Zhang, Zhou Yang, Xuanzhe Liu, Zhenpeng Chen

CoRR, April, 2026

Can LLMs Deobfuscate Binary Code? A Systematic Analysis of Large Language Models into Pseudocode Deobfuscation.

Li Hu, Xiuwei Shang, Jieke Shi, Shaoyin Cheng, Junqi Zhang, Gangyang Li, Zhou Yang, Weiming Zhang, David Lo

CoRR, April, 2026

AgentSZZ: Teaching the LLM Agent to Play Detective with Bug-Inducing Commits.

Yunbo Lyu, Jieke Shi, Hong Jin Kang, Ratnadira Widyasari, Junda He, Yuqing Niu, Chengran Yang, Junkai Chen, Zhou Yang, Julia Lawall, David Lo

CoRR, April, 2026

Towards Fair Machine Learning Software: Understanding and Addressing Model Bias Through Counterfactual Thinking.

Zichong Wang, Zhou Yang, David Lo, Wenbin Zhang

AI Ethics, April, 2026

Automated TEE Adaptation With LLMs: Identifying, Transforming, and Porting Sensitive Functions in Programs.

Ruidong Han, Zhou Yang, Chengyan Ma, Ye Liu, Yuqing Niu, Siqi Ma, Debin Gao, David Lo

IEEE Trans. Software Eng., March, 2026

Compiling Code LLMs into Lightweight Executables.

Jieke Shi, Junda He, Zhou Yang, Chengran Yang, Mykhailo V. Klymenko, Thong Hoang, Xiwei Xu, Zhenchang Xing, David Lo

CoRR, March, 2026

Finding Memory Leaks in C/C++ Programs via Neuro-Symbolic Augmented Static Analysis.

Huihui Huang, Jieke Shi, Bo Wang, Zhou Yang, David Lo

CoRR, March, 2026

Watermarking LLM Agent Trajectories.

Wenlong Meng, Chen Gong, Terry Yue Zhuo, Fan Zhang, Kecen Li, Zheng Liu, Zhou Yang, Chengkun Wei, Wenzhi Chen

CoRR, February, 2026

Hidden Licensing Risks in the LLMware Ecosystem.

Bo Wang, Yueyang Chen, Jieke Shi, Minghui Li, Yunbo Lyu, Yinan Wu, Youfang Lin, Zhou Yang

CoRR, February, 2026

Ecosystem of Large Language Models for Code.

Zhou Yang, Jieke Shi, Premkumar T. Devanbu, David Lo

ACM Trans. Softw. Eng. Methodol., January, 2026

2025

Finding Safety Violations of AI-Enabled Control Systems through the Lens of Synthesized Proxy Programs.

Jieke Shi, Zhou Yang, Junda He, Bowen Xu, Dongsun Kim, DongGyun Han, David Lo

ACM Trans. Softw. Eng. Methodol., September, 2025

Scrub It Out! Erasing Sensitive Memorization in Code Language Models via Machine Unlearning.

Zhaoyang Chu, Yao Wan, Zhikun Zhang, Di Wang, Zhou Yang, Hongyu Zhang, Pan Zhou, Xuanhua Shi, Hai Jin, David Lo

CoRR, September, 2025

Mut4All: Fuzzing Compilers via LLM-Synthesized Mutators Learned from Bug Reports.

Bo Wang, Pengyang Wang, Chong Chen, Qi Sun, Jieke Shi, Chengran Yang, Ming Deng, Youfang Lin, Zhou Yang, David Lo

CoRR, July, 2025

SLICEMATE: Accurate and Scalable Static Program Slicing via LLM-Powered Agents.

Jianming Chang, Jieke Shi, Yunbo Lyu, Xin Zhou, Lulu Wang, Zhou Yang, Bixin Li, David Lo

CoRR, July, 2025

Efficient and Green Large Language Models for Software Engineering: Literature Review, Vision, and the Road Ahead.

Jieke Shi, Zhou Yang, David Lo

ACM Trans. Softw. Eng. Methodol., June, 2025

Which Factors Make Code LLMs More Vulnerable to Backdoor Attacks? A Systematic Study.

Chenyu Wang, Zhou Yang, Yaniv Harel, David Lo

CoRR, June, 2025

Prioritizing Speech Test Cases.

Zhou Yang, Jieke Shi, Muhammad Hilmi Asyrofi, Bowen Xu, Xin Zhou, Dong-Gyun Han, David Lo

ACM Trans. Softw. Eng. Methodol., May, 2025

PTM4Tag+: Tag recommendation of stack overflow posts with pre-trained models.

Junda He, Bowen Xu, Zhou Yang, DongGyun Han, Chengran Yang, Jiakun Liu, Zhipeng Zhao, David Lo

Empir. Softw. Eng., February, 2025

AutoTEE: Automated Migration and Protection of Programs in Trusted Execution Environments.

Ruidong Han, Zhou Yang, Chengyan Ma, Ye Liu, Yuqing Niu, Siqi Ma, Debin Gao, David Lo

CoRR, February, 2025

Do Existing Testing Tools Really Uncover Gender Bias in Text-to-Image Models?

Yunbo Lyu, Zhou Yang, Yuqing Niu, Jing Jiang, David Lo

Proceedings of the 33rd ACM International Conference on Multimedia, 2025

Backdoors in Code Summarizers: How Bad Is It?

Chenyu Wang, Zhou Yang, Yaniv Harel, David Lo

Proceedings of the 40th IEEE/ACM International Conference on Automated Software Engineering, 2025

Token Sugar: Making Source Code Sweeter for LLMs through Token-Efficient Shorthand.

Zhensu Sun, Chengran Yang, Xiaoning Du, Zhou Yang, Li Li, David Lo

Proceedings of the 40th IEEE/ACM International Conference on Automated Software Engineering, 2025

"My productivity is boosted, but ..." Demystifying Users' Perception on AI Coding Assistants.

Yunbo Lyu, Zhou Yang, Jieke Shi, Jianming Chang, Yue Liu, David Lo

Proceedings of the 40th IEEE/ACM International Conference on Automated Software Engineering, 2025

2024

Gotcha! This Model Uses My Code! Evaluating Membership Leakage Risks in Code Models.

Zhou Yang, Zhipeng Zhao, Chenyu Wang, Jieke Shi, Dongsun Kim, DongGyun Han, David Lo

IEEE Trans. Software Eng., December, 2024

Large Language Models for Software Engineering: A Systematic Literature Review.

Xinyi Hou, Yanjie Zhao, Yue Liu, Zhou Yang, Kailong Wang, Li Li, Xiapu Luo, David Lo, John Grundy, Haoyu Wang

ACM Trans. Softw. Eng. Methodol., November, 2024

Stealthy Backdoor Attack for Code Models.

Zhou Yang, Bowen Xu, Jie M. Zhang, Hong Jin Kang, Jieke Shi, Junda He, David Lo

IEEE Trans. Software Eng., April, 2024

Representation Learning for Stack Overflow Posts: How Far Are We?

Junda He, Xin Zhou, Bowen Xu, Ting Zhang, Kisub Kim, Zhou Yang, Ferdian Thung, Ivana Clairine Irsan, David Lo

ACM Trans. Softw. Eng. Methodol., March, 2024

Synthesizing Efficient and Permissive Programmatic Runtime Shields for Neural Policies.

Jieke Shi, Junda He, Zhou Yang, Dorde Zikelic, David Lo

CoRR, 2024

Hotfixing Large Language Models for Code: How Far Can Parameter-Efficient Fine-Tuning Go?

Zhou Yang, David Lo

CoRR, 2024

Ecosystem of Large Language Models for Code.

Zhou Yang, Jieke Shi, David Lo

CoRR, 2024

Efficient and Green Large Language Models for Software Engineering: Vision and the Road Ahead.

Jieke Shi, Zhou Yang, David Lo

CoRR, 2024

Robustness, Security, Privacy, Explainability, Efficiency, and Usability of Large Language Models for Code.

Zhou Yang, Zhensu Sun, Terry Yue Zhuo, Premkumar T. Devanbu, David Lo

CoRR, 2024

Quality Assurance for Artificial Intelligence: A Study of Industrial Concerns, Challenges and Best Practices.

Chenyu Wang, Zhou Yang, Ze Shi Li, Daniela E. Damian, David Lo

CoRR, 2024

Baffle: Hiding Backdoors in Offline Reinforcement Learning Datasets.

Chen Gong, Zhou Yang, Yunpeng Bai, Junda He, Jieke Shi, Kecen Li, Arunesh Sinha, Bowen Xu, Xinwen Hou, David Lo, Tianhao Wang

Proceedings of the IEEE Symposium on Security and Privacy, 2024

AI Coders Are among Us: Rethinking Programming Language Grammar towards Efficient Code Generation.

Zhensu Sun, Xiaoning Du, Zhou Yang, Li Li, David Lo

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

Classifying Source Code: How Far Can Compressor-based Classifiers Go?

Zhou Yang

Proceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings, 2024

Greening Large Language Models of Code.

Jieke Shi, Zhou Yang, Hong Jin Kang, Bowen Xu, Junda He, David Lo

Proceedings of the 46th International Conference on Software Engineering: Software Engineering in Society, 2024

Assessing AI Detectors in Identifying AI-Generated Code: Implications for Education.

Wei Hung Pan, Ming Jie Chok, Jonathan Leong Shan Wong, Yung Xin Shin, Yeong Shian Poon, Zhou Yang, Chun Yong Chong, David Lo, Mei Kuan Lim

Proceedings of the 46th International Conference on Software Engineering: Software Engineering Education and Training, 2024

Curiosity-Driven Testing for Sequential Decision-Making Process.

Junda He, Zhou Yang, Jieke Shi, Chengran Yang, Kisub Kim, Bowen Xu, Xin Zhou, David Lo

Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, 2024

Unveiling Memorization in Code Models.

Zhou Yang, Zhipeng Zhao, Chenyu Wang, Jieke Shi, Dongsun Kim, DongGyun Han, David Lo

Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, 2024

2023

Towards Smaller, Faster, and Greener Language Models of Code.

Jieke Shi, Zhou Yang, Hong Jin Kang, Bowen Xu, Junda He, David Lo

CoRR, 2023

Adversarial Attacks on Code Models with Discriminative Graph Patterns.

Thanh-Dat Nguyen, Zhou Yang, Xuan-Bach Dinh Le, Patanamon Thongtanunam, David Lo

CoRR, 2023

What Do Code Models Memorize? An Empirical Study on Large Language Models of Code.

Zhou Yang, Zhipeng Zhao, Chenyu Wang, Jieke Shi, Dongsun Kim, DongGyun Han, David Lo

CoRR, 2023

Data Augmentation Approaches for Source Code Models: A Survey.

Terry Yue Zhuo, Zhou Yang, Zhensu Sun, Yufei Wang, Li Li, Xiaoning Du, Zhenchang Xing, David Lo

CoRR, 2023

APISENS- Sentiment Scoring Tool for APIs with Crowd-Knowledge.

Kisub Kim, Ferdian Thung, Ting Zhang, Ivana Clairine Irsan, Ratnadira Widyasari, Zhou Yang, David Lo

CoRR, 2023

APIHarvest: Harvesting API Information from Various Online Sources.

Ferdian Thung, Kisub Kim, Ting Zhang, Ivana Clairine Irsan, Ratnadira Widyasari, Zhou Yang, David Lo

CoRR, 2023

Towards Fair Machine Learning Software: Understanding and Addressing Model Bias Through Counterfactual Thinking.

Zichong Wang, Zhou Yang, Meikang Qiu, Israat Haque, Laura Brown, Yi He, Jianwu Wang, David Lo, Wenbin Zhang

CoRR, 2023

Prioritizing Speech Test Cases.

Zhou Yang, Jieke Shi, Muhammad Hilmi Asyrofi, Bowen Xu, Xin Zhou, DongGyun Han, David Lo

CoRR, 2023

Exploring and Repairing Gender Fairness Violations in Word Embedding-based Sentiment Analysis Model through Adversarial Patches.

Lin Sze Khoo, Jia Qi Bay, Ming Lee Kimberly Yap, Mei Kuan Lim, Chun Yong Chong, Zhou Yang, David Lo

Proceedings of the IEEE International Conference on Software Analysis, 2023

What Do Users Ask in Open-Source AI Repositories? An Empirical Study of GitHub Issues.

Zhou Yang, Chenyu Wang, Jieke Shi, Thong Hoang, Pavneet Singh Kochhar, Qinghua Lu, Zhenchang Xing, David Lo

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

NICHE: A Curated Dataset of Engineered Machine Learning Projects in Python.

Ratnadira Widyasari, Zhou Yang, Ferdian Thung, Sheng Qin Sim, Fiona Wee, Camellia Lok, Jack Phan, Haodi Qi, Constance Tan, Qijin Tay, David Lo

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

Synthesizing Speech Test Cases with Text-to-Speech? An Empirical Study on the False Alarms in Automated Speech Recognition Testing.

Julia Kaiwen Lau, Kelvin Kai Wen Kong, Julian Hao Yong, Per Hoong Tan, Zhou Yang, Zi Qian Yong, Joshua Chern Wey Low, Chun Yong Chong, Mei Kuan Lim, David Lo

Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, 2023

ASDF: A Differential Testing Framework for Automatic Speech Recognition Systems.

Daniel Hao Xian Yuen, Andrew Yong Chen Pang, Zhou Yang, Chun Yong Chong, Mei Kuan Lim, David Lo

Proceedings of the IEEE Conference on Software Testing, Verification and Validation, 2023

CCBERT: Self-Supervised Code Change Representation Learning.

Xin Zhou, Bowen Xu, DongGyun Han, Zhou Yang, Junda He, David Lo

Proceedings of the IEEE International Conference on Software Maintenance and Evolution, 2023

Supporting Collateral Evolution in Software Ecosystems.

Zhou Yang, Bowen Xu, David Lo

Proceedings of the Software Ecosystems: Tooling and Analytics, 2023

2022

BiasFinder: Metamorphic Test Generation to Uncover Bias for Sentiment Analysis Systems.

Muhammad Hilmi Asyrofi, Zhou Yang, Imam Nur Bani Yusuf, Hong Jin Kang, Ferdian Thung, David Lo

IEEE Trans. Software Eng., 2022

Mind Your Data! Hiding Backdoors in Offline Reinforcement Learning Datasets.

Chen Gong, Zhou Yang, Yunpeng Bai, Junda He, Jieke Shi, Arunesh Sinha, Bowen Xu, Xinwen Hou, Guoliang Fan, David Lo

CoRR, 2022

Aspect-Based API Review Classification: How Far Can Pre-Trained Transformer Model Go?

Chengran Yang, Bowen Xu, Junaed Younus Khan, Gias Uddin, DongGyun Han, Zhou Yang, David Lo

Proceedings of the IEEE International Conference on Software Analysis, 2022

Revisiting Neuron Coverage Metrics and Quality of Deep Neural Networks.

Zhou Yang, Jieke Shi, Muhammad Hilmi Asyrofi, David Lo

Proceedings of the IEEE International Conference on Software Analysis, 2022

Can Identifier Splitting Improve Open-Vocabulary Language Model of Code?

Jieke Shi, Zhou Yang, Junda He, Bowen Xu, David Lo

Proceedings of the IEEE International Conference on Software Analysis, 2022

Answer Summarization for Technical Queries: Benchmark and New Approach.

Chengran Yang, Bowen Xu, Ferdian Thung, Yucen Shi, Ting Zhang, Zhou Yang, Xin Zhou, Jieke Shi, Junda He, DongGyun Han, David Lo

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, 2022

Compressing Pre-trained Models of Code into 3 MB.

Jieke Shi, Zhou Yang, Bowen Xu, Hong Jin Kang, David Lo

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, 2022

PTM4Tag: sharpening tag recommendation of stack overflow posts with pre-trained models.

Junda He, Bowen Xu, Zhou Yang, DongGyun Han, Chengran Yang, David Lo

Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension, 2022

Natural Attack for Pre-trained Models of Code.

Zhou Yang, Jieke Shi, Junda He, David Lo

Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022

Curiosity-Driven and Victim-Aware Adversarial Policies.

Chen Gong, Zhou Yang, Yunpeng Bai, Jieke Shi, Arunesh Sinha, Bowen Xu, David Lo, Xinwen Hou, Guoliang Fan

Proceedings of the Annual Computer Security Applications Conference, 2022

2021

BiasRV: uncovering biased sentiment predictions at runtime.

Zhou Yang, Muhammad Hilmi Asyrofi, David Lo

Proceedings of the ESEC/FSE '21: 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2021

CrossASR++: a modular differential testing framework for automatic speech recognition.

Muhammad Hilmi Asyrofi, Zhou Yang, David Lo

Proceedings of the ESEC/FSE '21: 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2021

IncBL: Incremental Bug Localization.

Zhou Yang, Jieke Shi, Shaowei Wang, David Lo

Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering, 2021

BiasHeal: On-the-Fly Black-Box Healing of Bias in Sentiment Analysis Systems.

Zhou Yang, Harshit Jain, Jieke Shi, Muhammad Hilmi Asyrofi, David Lo

Proceedings of the IEEE International Conference on Software Maintenance and Evolution, 2021

Can Differential Testing Improve Automatic Speech Recognition Systems?

Muhammad Hilmi Asyrofi, Zhou Yang, Jieke Shi, Chu Wei Quan, David Lo

Proceedings of the IEEE International Conference on Software Maintenance and Evolution, 2021

2020

An auction-based rescue task allocation approach for heterogeneous multi-robot system.

Jieke Shi, Zhou Yang, Junwu Zhu

Multim. Tools Appl., 2020

2019

A real-time decentralized algorithm for task scheduling in multi-agent system with continuous damage.

Junwu Zhu, Jieke Shi, Zhou Yang, Bin Li

Appl. Soft Comput., 2019