6 papers
Cloak and Detonate: Scanner Evasion and Dynamic Detection of Agent Skill Malware
Zimo Ji, Congying Xu, Zongjie Li +4
LLM coding agents increasingly rely on third-party agent skills from public marketplaces, which execute with the agent's privileges and create a software supply-chain attack surfac…
Coding Agents Are Guessing: Measuring Action-Boundary Violations in Underspecified DevOps Instructions
Zimo Ji, Zekai Zhang, Congying Xu +4
LLM coding agents are increasingly deployed to act autonomously on real production infrastructure. They execute shell commands, modify repositories, and call operational APIs. Howe…
MR-Coupler: Automated Metamorphic Test Generation via Functional Coupling Analysis
Congying Xu, Hengcheng Zhu, Songqiang Chen +3
Metamorphic testing (MT) is a widely recognized technique for alleviating the oracle problem in software testing. However, its adoption is hindered by the difficulty of constructin…
MR-Adopt: Automatic Deduction of Input Transformation Function for Metamorphic Testing
Congying Xu, Songqiang Chen, Jiarong Wu +4
While a recent study reveals that many developer-written test cases can encode a reusable Metamorphic Relation (MR), over 70% of them directly hard-code the source input and follow…
Can Emulating Semantic Translation Help LLMs with Code Translation? A Study Based on Pseudocode
Songqiang Chen, Congying Xu, Jingyi Chen +3
Although large language models (LLMs) show promising potential in code translation, they still struggle to generate accurate translations using the commonly adopted direct code-to-…
Towards Verifiably Safe Tool Use for LLM Agents
Aarya Doshi, Yining Hong, Congying Xu +3
Large language model (LLM)-based AI agents extend LLM capabilities by enabling access to tools such as data sources, APIs, search engines, code sandboxes, and even other agents. Wh…