TRIM: Reducing AI-Generated CodeSlop via Agent Trajectory Minimization

Key points

It defines CodeSlop by functional behavior rather than surface style, such as verbosity or duplication. Any edit that can be removed while tests still pass counts as CodeSlop.
The cause is the agent's search process. Once it finds a correct solution, there is no reason to roll back the attempted edits, so they remain in the final patch.
Telling the agent to reduce its own patch was unstable. In 3.8% to 44.9% of cases it broke behavior or made the patch larger.
TRIM uses the task history, not the final patch, as the search space because the temporal order of edits approximates dependency structure.
It uses a hierarchical approach that tries to remove large chunks first, confirms success, and then splits more finely if needed, so the verification cost is about half that of Delta Debugging.
On SWE-Bench-Verified, it preserved correctness on 327 of 330 successful patches, or 99.1%, and 18 patches became exactly identical to the human-written reference patch.

External research summaries. These are not HDATF publications or measured product results.