10 citations · 11 across the 11 of their papers we have counts for
12 papers
When is LLM-Based Program Reasoning Correct? A Completion Semantics for LLM-Based Code Inference
Zhiyuan Liu, Yihe Li, Trevor E. Carlson +3
Due to token and cognitive limits, Large Language Models (LLMs) typically perform program reasoning over incomplete code fragments/prompts rather than complete programs. Such reaso…
Understanding the (In)Security of Vibe-Coded Applications
Junquan Deng, Zhiyu Fan, Ruijie Meng
Recent advances in large language models (LLMs) have enabled vibe coding, an emerging software development paradigm in which users create applications primarily through natural-lan…
VeriGrey: Greybox Agent Validation
Yuntong Zhang, Sungmin Kang, Ruijie Meng +2
Agentic AI has been a topic of great interest recently. A Large Language Model (LLM) agent involves one or more LLMs in the back-end. In the front end, it conducts autonomous decis…
Reachability Across the NL/PL Boundary: A Taxonomy-Driven Dataflow Model for LLM-Integrated Applications
Zihao Xu, Xiao Cheng, Ruijie Meng +1
LLM API calls have become a standard programming primitive, but they create a program boundary that disrupts traditional dataflow analysis. A runtime value may be inserted into a n…
To Defend Against Cyber Attacks, We Must Teach AI Agents to Hack
Terry Yue Zhuo, Yangruibo Ding, Wenbo Guo +1
For over a decade, cybersecurity has relied on human labor scarcity to limit attackers to high-value targets manually or generic automated attacks at scale. Building sophisticated…
Agentic Verification of Software Systems
Haoxin Tu, Huan Zhao, Yahui Song +3
Automatically generated code is gaining traction recently, owing to the prevalence of Large Language Models (LLMs). Further, the AlphaProof initiative has demonstrated the possibil…
Large Language Model Powered Symbolic Execution
Yihe Li, Ruijie Meng, Gregory J. Duck
Large Language Models (LLMs) have emerged as a promising alternative to traditional static program analysis methods, such as symbolic execution, offering the ability to reason over…
AFLNet Five Years Later: On Coverage-Guided Protocol Fuzzing
Ruijie Meng, Van-Thuan Pham, Marcel Böhme +1
Protocol implementations are stateful which makes them difficult to test: Sending the same test input message twice might yield a different response every time. Our proposal to con…
Large Language Model assisted Hybrid Fuzzing
Ruijie Meng, Gregory J. Duck, Abhik Roychoudhury
Greybox fuzzing is one of the most popular methods for detecting software vulnerabilities, which conducts a biased random search within the program input space. To enhance its effe…
Program Environment Fuzzing
Ruijie Meng, Gregory J. Duck, Abhik Roychoudhury
Computer programs are not executed in isolation, but rather interact with the execution environment which drives the program behaviors. Software validation methods thus need to cap…
Greybox Fuzzing of Distributed Systems
Ruijie Meng, George Pîrlea, Abhik Roychoudhury +1
Grey-box fuzzing is the lightweight approach of choice for finding bugs in sequential programs. It provides a balance between efficiency and effectiveness by conducting a biased ra…
Linear-time Temporal Logic guided Greybox Fuzzing
Ruijie Meng, Zhen Dong, Jialin Li +2
Software model checking is a verification technique which is widely used for checking temporal properties of software systems. Even though it is a property verification technique,…