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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 Code-Editing Large Language Model Systems at the Repository Scale](https://github.com/Qurrent-AI/RES-Q)
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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 Code-Editing Large Language Model Systems at the Repository Scale](https://arxiv.org/abs/2406.16801)
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  ### Dataset Structure
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  An example of a RES-Q task instance is as follows: