P2 On Automated Assistants for Software Development: The Role of LLMs
论软件开发中的自动化助手：大语言模型的作用
ASE 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE)2023匹配度 3/10 · 论文聚焦基于LLM的软件开发自动化助手与人类记忆模型框架，属于开发者工具/软件工程方向，与用户核心的静态分析、形式化验证、浮点/贝叶斯程序分析及其与LLM交叉无直接关系；虽涉及LLM辅助编程，但更偏LLM助手能力与认知框架，而非程序分析技术。引用 12inbox
Software developers handle many complex tasks that include gathering and applying domain knowledge, coordinating subtasks, designing interfaces, turning ideas into elegant code, and more. They must switch contexts between these tasks, incurring more cognitive costs. Recent advances in large language models (LLMs) open up new possibilities for moving beyond the support provided by automated assistants (AAs) available today. In this paper, we explore if a human memory model can provide a framework for the systematic investigation of AAs for software development based on LLMs and other new technologies.
@inproceedings{LeungM23,
title = {On Automated Assistants for Software Development: The Role of LLMs},
author = {Mira Leung and Gail Murphy},
booktitle = {ASE},
year = {2023},
doi = {10.1109/ase56229.2023.00035}
}