activity
20242026
collaborators

9 papers

cs.SE2026

FastCode: Fast and Cost-Efficient Code Understanding and Reasoning

Zhonghang Li, Zongwei Li, Yuxuan Chen +5

Repository-scale code reasoning is a cornerstone of modern AI-assisted software engineering, enabling Large Language Models (LLMs) to handle complex workflows from program comprehe…

cs.SE2025

Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks

E. G. Santana, Gabriel Benjamin, Melissa Araujo +7

A growing variety of prompt engineering techniques has been proposed for Large Language Models (LLMs), yet systematic evaluation of each technique on individual software engineerin…

cs.SE2025

A Deep Dive Into Large Language Model Code Generation Mistakes: What and Why?

QiHong Chen, Jiachen Yu, Jiawei Li +3

Recent advancements in Large Language Models (LLMs) have led to their widespread application in automated code generation. However, these models can still generate defective code t…

cs.SE2025

Consider What Humans Consider: Optimizing Commit Message Leveraging Contexts Considered By Human

Jiawei Li, David Faragó, Christian Petrov +1

Commit messages are crucial in software development, supporting maintenance tasks and communication among developers. While Large Language Models (LLMs) have advanced Commit Messag…

cs.SE2025

Enhancing LLM Performance Through Debate: An Empirical Study on Multi-Agent Debate for Coding Tasks

Jina Chun, Yong Jin Chun, Qihong Chen +2

Large Language Models (LLMs) have advanced autonomous agents' planning and decision-making, yet they struggle with complex tasks requiring diverse expertise and multi-step reasonin…

cs.SE2025

Optimization is Better than Generation: Optimizing Commit Message Leveraging Human-written Commit Message

Jiawei Li, David Faragó, Christian Petrov +1

Commit messages are crucial in software development, supporting maintenance tasks and communication among developers. While Large Language Models (LLMs) have advanced Commit Messag…