8 citations · 9 across the 3 of their papers we have counts for
3 papers
cs.SE2025★ 1 cited
The Prompt Alchemist: Automated LLM-Tailored Prompt Optimization for Test Case Generation
Shuzheng Gao, Chaozheng Wang, Cuiyun Gao +4
Test cases are essential for validating the reliability and quality of software applications. Recent studies have demonstrated the capability of Large Language Models (LLMs) to gen…
cs.SE2024
A Systematic Evaluation of Large Code Models in API Suggestion: When, Which, and How
Chaozheng Wang, Shuzheng Gao, Cuiyun Gao +4
API suggestion is a critical task in modern software development, assisting programmers by predicting and recommending third-party APIs based on the current context. Recent advance…
cs.SE2024★ 8 cited
ComplexCodeEval: A Benchmark for Evaluating Large Code Models on More Complex Code
Jia Feng, Jiachen Liu, Cuiyun Gao +4
In recent years, the application of large language models (LLMs) to code-related tasks has gained significant attention. However, existing evaluation benchmarks often focus on limi…