1 citations · 1 across the 3 of their papers we have counts for
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cs.SE2026
FastCode: Fast and Cost-Efficient Code Understanding and Reasoning
Zhonghang Li, Zongwei Li, Yuxuan Chen +5
Repository-scale code reasoning is a cornerstone of modern AI-assisted software engineering, enabling Large Language Models (LLMs) to handle complex workflows from program comprehe…
cs.SE2025
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…
cs.SE2025★ 1 cited
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…