Forecasting Developer Environments with GenAI: A Research Perspective

TL;DR

This paper discusses how Generative AI models are transforming developer environments by enabling higher levels of abstraction in coding tasks, with insights from a collaborative expert meeting.

Contribution

It provides a research perspective on the challenges and opportunities of integrating GenAI into IDEs, based on expert discussions across multiple domains.

Findings

Identification of key themes for GenAI integration in IDEs

Insights into challenges faced by developers using GenAI

Opportunities for future research in Human-AI collaboration

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, a four-day intensive research meeting. Four themes emerged as areas of interest for researchers and practitioners.