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Requirements After the First Edit: Mining Late Requirement Emergence and Rework in Real-World Coding-Agent Sessions

Source
arxiv.org
Author
Bowen Jiang, Haowei Cheng, Yuhong Fu, Anne Koziolek, Jialong Li, Weixing Zhang
Date

Context

Coding- benchmarks with fixed instructions can miss the rework that follows when users clarify requirements after implementation begins. Researchers examined 3,553 eligible conversation sessions and, where repository history could be replayed, measured deletion or replacement of earlier agent-written lines. Newly stated requirements were followed by roughly twice as much of this code invalidation as matched edits without new requirements. The authors explicitly treat that relationship as observational, not proof of causation. The result makes changing requirements a measurable part of agent : success includes responding to what users discover they need after seeing the first implementation. Study abstract.

Terms in this piece · Glossary
  • AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
  • eval — A repeatable test for AI quality — a set of tasks plus scoring — used the way software teams use test suites, because model output is too variable to judge by eyeballing.
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