arXiv AI
Precedent or Intent? What Coding Agents Follow When Evolving Existing Code
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Zero2Repo: Can Coding Agents Build Repositories from Scratch?
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arXiv AI
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A Unified Issue Resolution Benchmark for Requirement Clarification, Planning, and Code Generation for Coding Agents
arXiv:2608. 09072v1 Announce Type: cross Abstract: Large language model-powered coding agents are increasingly used to modify existing code repositories, for example, by adding features or fixing bugs.
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The Impact of Configuring Agentic AI Coding Tools on Build-vs-Buy Decisions: A Study Protocol
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How Do Coding-Agent Harnesses Self-Evolve? An Empirical Study of Retrospective Adaptation
The paper investigates how coding agents can self‑evolve their harnesses—software, configuration, and instructions—by reviewing completed sessions and proposing changes. Using Claude Code on 30 SWE‑bench issues, the authors analyzed 125 proposals from the etro skill, implemented 24, and evaluated 12 changes on subsequent tasks. The results show mixed effectiveness: some changes eliminated targeted problems, others reduced or had no impact, and some added unrelated work, indicating that self‑evolution requires mechanisms to assess and refine changes.
arXiv AI
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Agentic Synthesis against Counterexample-Supplemented Sketches
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arXiv AI
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RepoTrace: Improving Requirement Tracing in Multi-Round Agent Interactions
arXiv:2610.35333v1 Announce Type: cross Abstract: Code agents have become increasingly capable of performing software engineering tasks through interaction with software environments. However, agents...