7 citations · 19 across the 11 of their papers we have counts for
5 papers · 1 filter
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…
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),…
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…
On the Evaluation of Large Language Models in Unit Test Generation
Lin Yang, Chen Yang, Shutao Gao +8
Unit testing is an essential activity in software development for verifying the correctness of software components. However, manually writing unit tests is challenging and time-con…
Advancing Code Coverage: Incorporating Program Analysis with Large Language Models
Chen Yang, Junjie Chen, Bin Lin +2
Automatic test generation plays a critical role in software quality assurance. While the recent advances in Search-Based Software Testing (SBST) and Large Language Models (LLMs) ha…