63 citations · 211 across the 29 of their papers we have counts for
29 papers
PATCH: Empowering Large Language Model with Programmer-Intent Guidance and Collaborative-Behavior Simulation for Automatic Bug Fixing
Yuwei Zhang, Zhi Jin, Ying Xing +5
Bug fixing holds significant importance in software development and maintenance. Recent research has made substantial strides in exploring the potential of large language models (L…
HITS: High-coverage LLM-based Unit Test Generation via Method Slicing
Zejun Wang, Kaibo Liu, Ge Li +1
Large language models (LLMs) have behaved well in generating unit tests for Java projects. However, the performance for covering the complex focal methods within the projects is po…
An Evaluation of Requirements Modeling for Cyber-Physical Systems via LLMs
Dongming Jin, Shengxin Zhao, Zhi Jin +4
Cyber-physical systems (CPSs) integrate cyber and physical components and enable them to interact with each other to meet user needs. The needs for CPSs span rich application domai…
EvoCodeBench: An Evolving Code Generation Benchmark Aligned with Real-World Code Repositories
Jia Li, Ge Li, Xuanming Zhang +2
How to evaluate Large Language Models (LLMs) in code generation is an open question. Existing benchmarks demonstrate poor alignment with real-world code repositories and are insuff…
Enhancing Code Generation Performance of Smaller Models by Distilling the Reasoning Ability of LLMs
Zhihong Sun, Chen Lyu, Bolun Li +4
Large Language Models (LLMs) have recently made significant advances in code generation through the 'Chain-of-Thought' prompting technique. This technique empowers the model to aut…
IRCoCo: Immediate Rewards-Guided Deep Reinforcement Learning for Code Completion
Bolun Li, Zhihong Sun, Tao Huang +5
Code completion aims to enhance programming productivity by predicting potential code based on the current programming context. Recently, pretrained language models (LMs) have beco…