6 citations · 9 across the 6 of their papers we have counts for
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cs.SE2024
A Large-scale Empirical Study on Fine-tuning Large Language Models for Unit Testing
Ye Shang, Quanjun Zhang, Chunrong Fang +3
Unit testing plays a pivotal role in software development, improving software quality and reliability. However, generating effective test cases manually is time-consuming, promptin…
cs.SE2024★ 1 cited
TestBench: Evaluating Class-Level Test Case Generation Capability of Large Language Models
Quanjun Zhang, Ye Shang, Chunrong Fang +3
Software testing is a crucial phase in the software life cycle, helping identify potential risks and reduce maintenance costs. With the advancement of Large Language Models (LLMs),…
cs.SE2024★ 6 cited
TestART: Improving LLM-based Unit Testing via Co-evolution of Automated Generation and Repair Iteration
Siqi Gu, Quanjun Zhang, Kecheng Li +5
Unit testing is crucial for detecting bugs in individual program units but consumes time and effort. Recently, large language models (LLMs) have demonstrated remarkable capabilitie…