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cloud.google.com·6h ago
AI Research
arXiv CS.AI·Aug 19·5 min read
The Working Set of a Coding Agent: Coherence Debt in Repository-Scale Tasks
TL;DR
A coding agent's ability to maintain coherence in repository-scale tasks is hindered by coherence debt, which arises when necessary facts are unavailable. The study reveals that withholding critical information leads to incorrect outputs, emphasizing the importance of fact availability during code edits.
✦ Why It Matters
Ensure critical facts are available during code edits to avoid incorrect outputs and improve coding agent performance.
Key Takeaways
- Maintain availability of critical facts during code edits.
- Recognize that missing facts lead to incorrect outputs.
- Avoid reliance on outdated conventions in coding.
- Test models with varying configurations to assess performance.
How It Works
The study models coding tasks as a coupled-fact graph, where each edit requires access to recent context or parametric memory. When facts are withheld, agents experience coherence debt, leading to incorrect outputs.
The research demonstrates that agents often fabricate code or guess values when they lack necessary information.