AI-assisted Coding with Cody: Lessons from Context Retrieval and Evaluation for Code Recommendations
Reviewed by Pith T0 review T1 audit T2 compute T3 formal T4 kernel pith:RN54P7VNrecord.jsonopen to challenge →
classification
cs.IR
cs.LGcs.SE
keywords
codingcontextai-assistedcodediscussevaluationlessonsproviding
read the original abstract
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.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.