Human-AI Experience in Integrated Development Environments: A Systematic Literature Review
Maps what is known about human–AI interaction inside the IDE, and where the field's evidence actually stops.
Abstract
The integration of Artificial Intelligence (AI) into Integrated Development Environments (IDEs) is reshaping software development, fundamentally altering how developers interact with their tools. This shift marks the emergence of Human-AI Experience in Integrated Development Environment (in-IDE HAX), a field that explores the evolving dynamics of Human-Computer Interaction in AI-assisted coding environments. Despite rapid adoption, research on in-IDE HAX remains fragmented, which highlights the need for a unified overview of current practices, challenges, and opportunities. To provide a structured overview of existing research, we conduct a systematic literature review of 90 studies, summarizing current findings and outlining areas for further investigation. We organize key insights from reviewed studies into three aspects: Impact, Design, and Quality of AI-based systems inside IDEs. Impact findings show that AI-assisted coding enhances developer productivity but also introduces challenges, such as verification overhead and over-reliance. Design studies show that effective interfaces surface context, provide explanations and transparency of suggestion, and support user control. Quality studies document risks in correctness, maintainability, and security. For future research, priorities include productivity studies, design of assistance, and audit of AI-generated code. The agenda calls for larger and longer evaluations, stronger audit and verification assets, broader coverage across the software life cycle, and adaptive assistance under user control.
- Type
- Review
- Venue
- Empirical Software Engineering
- First public
- 8 Mar 2025
- arXiv
- 2503.06195
- Authors
- Agnia SergeyukIlya ZakharovEkaterina KoshchenkoMaliheh Izadi
- Direction
More from Human–AI Experience
Developer Needs and Feasible Features for AI Assistants in IDEs
Asks developers what they actually want from in-IDE assistance, then sorts those wants by what is feasible to build.
AI in Software Engineering: Perceived Roles and Their Impact on Adoption
Developers cast AI tools either as an inanimate instrument or as a human-like teammate — and the more roles they assign one, the more useful they find it.
Full Line Code Completion: Bringing AI to Desktop
Multi-token completion running entirely on the developer's own machine — the latency, memory and syntax limits that shaped it, and what it changed in the IDE.