Reading
Holon-Bench is an open-source benchmark framework designed to evaluate the performance of AI programming agents in open-source software maintainer workflows, covering scenarios like fix loops, regression safety, scope control, and multi-language patches.
Section 01
Holon-Bench is an open-source benchmark framework designed to evaluate the performance of AI programming agents in open-source software maintainer workflows, covering scenarios like fix loops, regression safety, scope control, and multi-language patches.
Section 02
Section 03
Current evaluations of AI programming agents mostly focus on single-shot code generation tasks, such as LeetCode-style algorithm problems. However, real-world software maintenance is far more complex—agents need to handle fix loops, understand validator feedback, control modification scope, and avoid regression issues.
Holon-Bench is designed to fill this evaluation gap. It focuses on whether AI agents can work like real maintainers, rather than whether they can write correct code snippets in one go.
Section 04
Holon-Bench is an open-source benchmark framework specifically designed to evaluate the performance of AI programming agents in open-source software maintainer workflows. It measures core capabilities that matter in real maintenance scenarios:
Section 05
Real-world bug fixes rarely succeed on the first try. Holon-Bench evaluates whether agents can:
Section 06
Does the agent only modify files that should be changed? Does it accidentally touch protected interfaces or contracts? Holon-Bench verifies this through protected reference implementations and scope checkers.
Section 07
Does fixing one bug introduce new issues? The framework includes hidden verifiers that the agent cannot see but are checked during the final evaluation.
Section 08
Supports evaluation tracks for multiple programming languages:
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