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AI-assisted Coding with Cody: Lessons from Context Retrieval and Evaluation for Code Recommendations

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arxiv 2408.05344 v1 pith:RN54P7VN submitted 2024-08-09 cs.IR cs.LGcs.SE

Jan Hartman , Rishabh Mehrotra , Hitesh Sagtani , Dominic Cooney , Rafal Gajdulewicz , Beyang Liu , Julie Tibshirani , Quinn Slack This is my paper · ORCID
classification cs.IRcs.LGcs.SE
keywords codingcontextai-assistedcodediscussevaluationlessonsproviding
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In this work, we discuss a recently popular type of recommender system: an LLM-based coding assistant. Connecting the task of providing code recommendations in multiple formats to traditional RecSys challenges, we outline several similarities and differences due to domain specifics. We emphasize the importance of providing relevant context to an LLM for this use case and discuss lessons learned from context enhancements & offline and online evaluation of such AI-assisted coding systems.

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