collaborators

9 papers

cs.SE2026

Executable but Unfaithful: Mock Object, Stub, and Assertion Generation by LLMs and Coding Agents

Hao Ning, Jiahui Dong, Zhen Yang +7

Mocking is a foundational practice in unit testing, enabling developers to isolate the code under test by replacing real dependencies with simulated alternatives. Automating the ge…

cs.SE2026

Refine After Generation: Toward Correct and Concise Patches in LLM-based Program Repair

Wenqiang Luo, Jacky Keung, Xiaoyu Shi +4

Large language models (LLMs) have advanced automatic program repair (APR) to the point where agentic systems routinely resolve real-world, repository-level issues. Yet the generate…

cs.SE2026

Understanding How Enterprises Adopt the Model Context Protocol for LLM-Driven Software Engineering

Kehui Chen, Yicheng Sun, Jacky Keung +2

Large Language Models (LLMs) are increasingly used in AI-based software engineering, but their limitations in complex task execution and multi-tool coordination have driven growing…

cs.HC2026

Making Sense of Scams: Understanding Scam Conversations Through Multi-Level Alignment

Zhenyu Mao, Jacky Keung, Xiangyu Li +4

Online scams often unfold gradually through interaction, yet existing detection systems predominantly rely on snapshot-based signals and interruptive warnings, revealing two resear…

cs.SE2026

Fixturize: Bridging the Fixture Gap in Test Generation

Chengyi Wang, Pengyu Xue, Zhen Yang +8

Current Large Language Models (LLMs) have advanced automated unit test generation but face a critical limitation: they often neglect to construct the necessary test fixtures, which…

cs.CR2025

PerProb: Indirectly Evaluating Memorization in Large Language Models

Yihan Liao, Jacky Keung, Xiaoxue Ma +2

The rapid advancement of Large Language Models (LLMs) has been driven by extensive datasets that may contain sensitive information, raising serious privacy concerns. One notable th…

cs.CR2025

Exposing and Defending Membership Leakage in Vulnerability Prediction Models

Yihan Liao, Jacky Keung, Xiaoxue Ma +2

Neural models for vulnerability prediction (VP) have achieved impressive performance by learning from large-scale code repositories. However, their susceptibility to Membership Inf…

cs.SE2025

Towards Requirements Engineering for GenAI-Enabled Software: Bridging Responsibility Gaps through Human Oversight Requirements

Zhenyu Mao, Jacky Keung, Yicheng Sun +3

Context: Responsibility gaps, long-recognized challenges in socio-technical systems where accountability becomes diffuse or ambiguous, have become increasingly pronounced in GenAI-…

cs.SE2025

R2ComSync: Improving Code-Comment Synchronization with In-Context Learning and Reranking

Zhen Yang, Hongyi Lin, Xiao Yu +5

Code-Comment Synchronization (CCS) aims to synchronize the comments with code changes in an automated fashion, thereby significantly reducing the workload of developers during soft…