8 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.SE2026
TDD-Agent: Test-Driven Reasoning for Code Generation
Hongyue Yu, Kefan Li, Jiakun Li +4
Large Language Models (LLMs) have achieved remarkable progress in code generation, yet ensuring correctness in complex, repository-level tasks remains challenging. Existing approac…
cs.SE2026
Escaping the Self-Repair Trap: Improving Test Oracle Generation via Dual-Context Awareness
Kefan Li, Hongyue Yu, Yuan Yuan
Large Language Models (LLMs) have shown strong potential for regression-oracle completion, where a test prefix is given and the current program version is treated as expected behav…
cs.SE2024★ 8 cited
Large Language Models as Test Case Generators: Performance Evaluation and Enhancement
Kefan Li, Yuan Yuan
Code generation with Large Language Models (LLMs) has been extensively studied and achieved remarkable progress. As a complementary aspect to code generation, test case generation…