7 papers
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…
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…
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
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…
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…
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…