DistDebug-Bench
by Yuxuan Jiang, Chenglin Liu, John Rose, Mason Miller, Ruthesh Thavamani, Juntao Wu, Yinwei Huang, Jiahao Xu, Peng Huang (OrderLab / University of Michigan)
What is DistDebug-Bench? DistDebug-Bench is a coding eval made by Yuxuan Jiang, Chenglin Liu, John Rose, Mason Miller, Ruthesh Thavamani, Juntao Wu, Yinwei Huang, Jiahao Xu, Peng Huang (OrderLab / University of Michigan). A distributed-systems diagnosis benchmark: 120 real bugs from 11 open-source systems across five languages, each with an issue report, attached evidence and a pre-fix repository snapshot. Agents must name the root-cause source blocks (file, function, line range); scoring is against 218 expert-annotated blocks, not whether a patch passes tests. The authors' NeurIPS 2026 paper and leaderboard report that the strongest Mini-SWE-Agent run reaches high file coverage but at most about 68% block coverage, with run-to-run flakiness on opaque reports. Code, evaluator, dataset and traces are public.
Editor note
A distributed-systems diagnosis benchmark: 120 real bugs from 11 open-source systems across five languages, each with an issue report, attached evidence and a pre-fix repository snapshot. Agents must name the root-cause source blocks (file, function, line range); scoring is against 218 expert-annotated blocks, not whether a patch passes tests. The authors' NeurIPS 2026 paper and leaderboard report that the strongest Mini-SWE-Agent run reaches high file coverage but at most about 68% block coverage, with run-to-run flakiness on opaque reports. Code, evaluator, dataset and traces are public.
- What it tests
- Whether coding agents can locate the code-level root cause of real distributed-system failures from issue evidence alone.
- Original source
- github.com/OrderLab/distdebug-bench
- Last updated
- Repo last push 2026-11-05
- License
- MIT
Related coding evals
- SWE-bench — Fixing real bugs in real repositories, judged by unit tests.
- HumanEval — Writing a short correct function from a docstring.
- LiveCodeBench — Code generation, self-repair and test prediction on fresh problems.
- Aider leaderboards (Polyglot) — Practical multi-language code editing.
Discussion
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