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RES-Q is a codebase editing benchmark based on compact, natural language instructions. The task is to, given an edit instruction and a codebase, produce a patch file that makes the correct edit to the codebase.
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The dataset was released as part of [RES-Q: Evaluating the Capability of Language Models
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### Dataset Structure
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An example of a RES-Q task instance is as follows:
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RES-Q is a codebase editing benchmark based on compact, natural language instructions. The task is to, given an edit instruction and a codebase, produce a patch file that makes the correct edit to the codebase.
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The dataset was released as part of [RES-Q: Evaluating the Code-Editing Capability of Large Language Models at the Repository Scale](https://arxiv.org/abs/[ARXIV_LINK])
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### Dataset Structure
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An example of a RES-Q task instance is as follows:
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