The Future of Development Environments with AI Foundation Models: NII Shonan Meeting 222 Report
Xing Hu, Raula Gaikovina Kula, Christoph Treude
TL;DR
This report discusses how AI foundation models are transforming development environments by enabling higher levels of abstraction and improving tasks like coding, testing, and review within IDEs, based on expert discussions.
Contribution
It provides a comprehensive overview of the challenges and opportunities in integrating AI foundation models into IDEs, highlighting future research directions.
Findings
AI models enhance code generation and review
Increased abstraction levels change developer-AI interaction
Identified key challenges in AI integration into IDEs
Abstract
Generative Artificial Intelligence (GenAI) models are achieving remarkable performance in various tasks, including code generation, testing, code review, and program repair. The ability to increase the level of abstraction away from writing code has the potential to change the Human-AI interaction within the integrated development environment (IDE). To explore the impact of GenAI on IDEs, 33 experts from the Software Engineering, Artificial Intelligence, and Human-Computer Interaction domains gathered to discuss challenges and opportunities at Shonan Meeting 222. This is the report
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSoftware Engineering Research · Software Engineering Techniques and Practices · AI-based Problem Solving and Planning