4 papers
Knowledge Matters: Injecting Project and Testing Knowledge into LLM-based Unit Test Generation
Anji Li, Mingwei Liu, Zhenxi Chen +5
Automated unit test generation using large language models (LLMs) holds great promise but often struggles with generating tests that are both correct and maintainable in real-world…
Are Decoder-Only Large Language Models the Silver Bullet for Code Search?
Yuxuan Chen, Mingwei Liu, Guangsheng Ou +4
Code search is essential for code reuse, allowing developers to efficiently locate relevant code snippets. The advent of powerful decoder-only Large Language Models (LLMs) has revo…
FeedbackEval: A Benchmark for Evaluating Large Language Models in Feedback-Driven Code Repair Tasks
Dekun Dai, MingWei Liu, Anji Li +5
Code repair is a fundamental task in software development, facilitating efficient bug resolution and software maintenance. Although large language models (LLMs) have demonstrated c…
Unseen-Codebases-Domain Data Synthesis and Training Based on Code Graphs
Guangsheng Ou, Qiming Zhang, Sirong Chen +9
In the context of newly release software frameworks, large language models (LLMs) often exhibit poor performance and a high rate of hallucination, as they are not exposed to such e…