collaborators

5 papers

cs.SE2026

His2Trans: A Knowledge-Guided Agentic Framework for Project-Level C-to-Rust Migration

Shengbo Wang, Mingwei Liu, Guangsheng Ou +3

C remains a major implementation language for operating systems, embedded platforms, and infrastructure software, but manual memory management continues to create security and main…

cs.SE2026

Knowledge Matters: Injecting Project and Testing Knowledge into LLM-based Unit Test Generation

Anji Li, Mingwei Liu, Zhenxi Chen +5

Automated unit test generation using large language models (LLMs) holds great promise but often struggles with generating tests that are both correct and maintainable in real-world…

cs.SE2026

AdaDec: A Uncertainty-Guided Lookahead Decoding Framework for LLM-Based Code Generation

Kaifeng He, Mingwei Liu, Chong Wang +4

Code generation with large language models (LLMs) is highly sensitive to token selection during decoding, particularly at uncertain decision points that influence program logic. Wh…

cs.AI2025

EvolMathEval: Towards Evolvable Benchmarks for Mathematical Reasoning via Evolutionary Testing

Shengbo Wang, Mingwei Liu, Zike Li +4

The rapid advancement of Large Language Models (LLMs) poses a significant challenge to existing mathematical reasoning benchmarks. However, these benchmarks tend to become easier o…

cs.SE2025

A Preliminary Study on the Robustness of Code Generation by Large Language Models

Zike Li, Mingwei Liu, Anji Li +4

Robustness is a critical factor for reliable code generation by large language models, yet most evaluations focus on correctness and overlook key issues such as missing input valid…