BonsAIDE: An Extended Vision for Human–AI Interaction in IDEs

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Authors: David Moreno-Lumbreras, Raula Gaikovina Kula, Christoph Treude
Cited by: 2
References: 20

Abstract

AI-driven coding assistants are transforming software development, yet their full potential in Integrated Development Environments (IDEs) remains underutilized. A key challenge is their tendency to hallucinate, producing plausible but incorrect code and leading developers down unintended paths. Current static file-based IDEs also lack support for tracking the provenance of AI-generated code or integrating version control in ways that match the dynamic and iterative nature of AI-assisted workflows. Consequently, developers lack tools to systematically manage, refine, and validate Generative AI (GenAI) code, making correctness, maintainability, and trust difficult to ensure. Inspired by the art of Japanese Bonsai gardening—emphasizing balance, structure, and pruning—we propose a new paradigm: an IDE where AI is free to generate, and developers guide evolution by pruning and shaping alternatives. We present BonsAIDE, a prototype that supports branching, comparison, and pruning of AI-generated code. In an initial study with 10 participants, we observed: (1) diverse exploration strategies across identical tasks; (2) high tool acceptance with low perceived difficulty; (3) benefits of branching and pruning, including clutter reduction and parallel exploration; and (4) concrete feedback on desired features such as side-by-side diffs and improved navigation. These findings motivate future research on provenance, prompt-aware navigation, and scalable human–AI interaction.

Fields of Study & Subjects

Scientific Computing and Data Management Software Engineering Research Machine Learning in Materials Science

Publication details

Journal / source
ACM Transactions on Software Engineering and Methodology
Publisher
Association for Computing Machinery (ACM)
Volume
35
Issue
9
Pages
1–25
Publication date
27 January 2026
Language
EN