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- # CORE: Benchmarking LLMs’ Code Reasoning Capabilities through Static Analysis Tasks
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  This repository hosts the **CoRe** benchmark, designed to evaluate the reasoning capabilities of large language models on **program analysis tasks** including data dependency, control dependency, and information flow. Each task instance is represented as a structured JSON object with detailed metadata for evaluation and reproduction.
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  For scripts, evaluation tools, and detailed instructions on running inference over CoRe, please check out our companion GitHub repository:
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  🔗 Website: [https://corebench.github.io/](https://corebench.github.io/)
 
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  🔗 Source code: [https://github.com/CoReBench/CoRe](https://github.com/CoReBench/CoRe)
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  This includes:
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  - Raw annotation data that could be used to generate various static analysis tasks
 
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+ # CoRe: Benchmarking LLMs’ Code Reasoning Capabilities through Static Analysis Tasks
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  This repository hosts the **CoRe** benchmark, designed to evaluate the reasoning capabilities of large language models on **program analysis tasks** including data dependency, control dependency, and information flow. Each task instance is represented as a structured JSON object with detailed metadata for evaluation and reproduction.
 
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  For scripts, evaluation tools, and detailed instructions on running inference over CoRe, please check out our companion GitHub repository:
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  🔗 Website: [https://corebench.github.io/](https://corebench.github.io/)
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  🔗 Source code: [https://github.com/CoReBench/CoRe](https://github.com/CoReBench/CoRe)
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+ 🔗 Paper: (https://arxiv.org/abs/2507.05269)[https://arxiv.org/abs/2507.05269]
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  This includes:
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  - Raw annotation data that could be used to generate various static analysis tasks