Rasoi: Visual Diffs for Evaluating Structural Changes Made by Coding Agents
Story 8, from arXiv
Rasoi is a tool that uses visual diffs to help developers understand how coding agents change a codebase's structure. It was tested with 12 developers and showed promise in identifying unexpected restructurings and ensuring changes stay within scope.
Key points
- Rasoi maps how a codebase's architecture evolves after each agent edit.
- It lets developers inspect added, modified, or removed architectural elements.
- A week-long study with 12 developers found visual diffs helped identify scope issues and unexpected restructuring.
- The tool's value lies in helping developers evaluate changes confidently, not just trusting the agent.
- Rasoi supports code comprehension and human oversight in AI-assisted development.
Why it matters
As coding agents become more involved in software development, understanding their structural impact is critical. Rasoi provides a way for developers to visually assess these changes, ensuring that automated edits don't introduce hidden issues or architectural drift.
Counterpoint
The study was limited to 12 developers across varied domains, which may not represent broader usage or long-term effectiveness.
Sources
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