4 citations · 11 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
Enhancing LLM Performance Through Debate: An Empirical Study on Multi-Agent Debate for Coding Tasks
Yong Jin Chun, Qihong Chen, Jiawei Li +1
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…
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…
An Empirical Study on Automatically Detecting AI-Generated Source Code: How Far Are We?
Hyunjae Suh, Mahan Tafreshipour, Jiawei Li +2
Artificial Intelligence (AI) techniques, especially Large Language Models (LLMs), have started gaining popularity among researchers and software developers for generating source co…
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…
Does the Order of Fine-tuning Matter and Why?
Qihong Chen, Jiawei Li, Hyunjae Suh +5
To improve the performance on a target task, researchers have fine-tuned language models with an intermediate task before the target task of interest. However, previous works have…
Automated Repair of Declarative Software Specifications in the Era of Large Language Models
Md Rashedul Hasan, Jiawei Li, Iftekhar Ahmed +1
The growing adoption of declarative software specification languages, coupled with their inherent difficulty in debugging, has underscored the need for effective and automated repa…
Test Smell: A Parasitic Energy Consumer in Software Testing
Md Rakib Hossain Misu, Jiawei Li, Adithya Bhattiprolu +3
Traditionally, energy efficiency research has focused on reducing energy consumption at the hardware level and, more recently, in the design and coding phases of the software devel…