Sign inGet started
Paper · arXiv

AgentBug-Smith: Automatically Reproducing Real-World Harness Bugs in Agentic Systems

Agent harness bugs exhibit unique characteristics and remain challenging for state-of-the-art software agents to repair. Progress in this area is further hindered by existing benchmarks, which contain only a small and fixed number of executable harness bugs while requiring hundreds of human hours to construct. This work presents AgentBug-Smith, an automated harness bug reproduction approach that continuously discovers and reproduces real-world harness bugs from open-source agentic systems. Across different backbone LLMs, AgentBug-Smith consistently outperforms existing bug reproduction techniques designed for general software, achieving 10.67% - 27.56% higher success rates of reproducing ...

AuthorsYiming Cheng, Alfin Wijaya Rahardja, Mengshi Zhang et al.
Primary categorycs.SE
Published29 September 2026
Last updated at source29 September 2026
cs.SEcs.AI
Embed this entry
<iframe src="https://silytics.si/embed/item/80e6c5f0-65ce-464f-99fc-faf74d443c49" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.