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.

Mira Leung

University of British Columbia

Gail Murphy

University of British Columbia

Canada