3 citations · 5 across the 6 of their papers we have counts for
5 papers · 1 filter
Dependency-Guided Repository-Level C-to-Rust Translation with Reinforcement Alignment
Jia Feng, Wenjie Gan, Cuiyun Gao +5
Automating C-to-Rust migration is critical for improving software security without sacrificing performance. Traditional rule-based methods struggle with diverse C idioms, often pro…
Can Large Language Models Reason About Complex Execution Paths? An Empirical Study on Python
Wenhan Wang, Kaibo Liu, Zeyu Sun +4
Execution path reasoning is a key step towards program semantics understanding. It is crucial for generating test cases that cover certain branches/paths, or detecting bugs that ar…
Python Symbolic Execution with LLM-powered Code Generation
Wenhan Wang, Kaibo Liu, An Ran Chen +4
Symbolic execution is a key technology in software testing, which generates test cases by collecting symbolic path constraints and then solving constraints with SMT solvers. Symbol…
HITS: High-coverage LLM-based Unit Test Generation via Method Slicing
Zejun Wang, Kaibo Liu, Ge Li +1
Large language models (LLMs) have behaved well in generating unit tests for Java projects. However, the performance for covering the complex focal methods within the projects is po…
LLM-Powered Test Case Generation for Detecting Bugs in Plausible Programs
Kaibo Liu, Zhenpeng Chen, Yiyang Liu +7
Detecting tricky bugs in plausible programs, those that pass existing test suites yet still contain bugs, remains a significant challenge in software testing. To address this probl…