Poison Valleys: Diagnosing Path-Dependent Failure in LLM Code Repair
When code-repair agents fail, final tests reveal that a patch is wrong but not which earlier commitment caused it or which software obligation failed. Poison Valleys traces this path in 1,844 model requests on two synthetic Python cases: PersistQueue adds atomic batch claiming to a disk-backed queue, while Dijkstra adds source-sensitive filtering to shortest-path search. We define plausible but incorrect software mechanisms, place each in a model's hypothesis, implementation plan, or both, and evaluate the generated code with an Oracle and targeted diagnostic coordinates. Moving the misconception from hypothesis to plan increased failure by 32.2% in PersistQueue and 28.9% in Dijkstra afte...
| Authors | Veljko Skarich |
|---|---|
| Primary category | cs.SE |
| Published | 15 October 2026 |
| Last updated at source | 15 October 2026 |
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