From the 1 of 5 linked papers with an AI index.
1 citations · 1 across the 2 of their papers we have counts for
5 papers
When is LLM-Based Program Reasoning Correct? A Completion Semantics for LLM-Based Code Inference
Zhiyuan Liu, Yihe Li, Trevor E. Carlson +3
The paper defines a completion semantics for reasoning about incomplete code fragments generated by large language models, and introduces a witness-generation workflow to validate…
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…
Persistent Iterators with Value Semantics
Yihe Li, Gregory J. Duck
Iterators are a fundamental programming abstraction for traversing and modifying elements in containers in mainstream imperative languages such as C++. Iterators provide a uniform…
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…
Fully Randomized Pointers
Sai Dhawal Phaye, Gregory J. Duck, Roland H. C. Yap +1
Memory errors continue to be a critical concern for programs written in low-level programming languages such as C and C++. Many different memory error defenses have been proposed,…