31 citations · 48 across the 7 of their papers we have counts for
6 papers · 1 filter
C2RustXW: Program-Structure-Aware C-to-Rust Translation via Program Analysis and LLM
Yanyan Yan, Yang Feng, Jiangshan Liu +4
The growing adoption of Rust for its memory safety and performance has increased the demand for effective migration of legacy C codebases. However, existing rule-based translators…
Large Language Models for Unit Test Generation: Achievements, Challenges, and Opportunities
Bei Chu, Yang Feng, Kui Liu +5
Unit tests help detect faults and prevent regressions, but writing them manually is costly. Automated unit test generation involves constructing inputs that exercise the code and o…
PALM: Synergizing Program Analysis and LLMs to Enhance Rust Unit Test Coverage
Bei Chu, Yang Feng, Kui Liu +4
Unit testing is essential for ensuring software reliability and correctness. Classic Search-Based Software Testing (SBST) methods and concolic execution-based approaches for genera…
PanicFI: An Infrastructure for Fixing Panic Bugs in Real-World Rust Programs
Yunbo Ni, Yang Feng, Zixi Liu +2
The Rust programming language has garnered significant attention due to its robust safety features and memory management capabilities. Despite its guaranteed memory safety, Rust pr…
MultiTest: Physical-Aware Object Insertion for Testing Multi-sensor Fusion Perception Systems
Xinyu Gao, Zhijie Wang, Yang Feng +3
Multi-sensor fusion stands as a pivotal technique in addressing numerous safety-critical tasks and applications, e.g., self-driving cars and automated robotic arms. With the contin…
Benchmarking Robustness of AI-Enabled Multi-sensor Fusion Systems: Challenges and Opportunities
Xinyu Gao, Zhijie Wang, Yang Feng +3
Multi-Sensor Fusion (MSF) based perception systems have been the foundation in supporting many industrial applications and domains, such as self-driving cars, robotic arms, and unm…