On Automated Assistants for Software Development: The Role of LLMs

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...

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Veröffentlicht in:IEEE/ACM International Conference on Automated Software Engineering : [proceedings] S. 1737 - 1741
Hauptverfasser: Leung, Mira, Murphy, Gail
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 11.09.2023
Schlagworte:
artificial intelligence
Automation
Large language models
Machine learning
Productivity
Software
Software development management
software development productivity
Software engineering
Switches
Systematics
Turning
ISSN:2643-1572
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Zusammenfassung: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.
ISSN:2643-1572
DOI:10.1109/ASE56229.2023.00035