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Programmers often search for usage examples for API methods. A tool thatcould generate realistic, idiomatic, and contextual usage examples for one ormore APIs would be immensely beneficial to developers. Such a tool wouldrelieve the need for a deep understanding of the API landscape, augmentexisting documentation, and help discover interactions among APIs. We presentCodeScholar, a tool that generates idiomatic code examples demonstrating thecommon usage of API methods. It includes a novel neural-guided search techniqueover graphs that grows the query APIs into idiomatic code examples. Our userstudy demonstrates that in 70% of cases, developers prefer CodeScholargenerated examples over state-of-the-art large language models (LLM) likeGPT3.5. We quantitatively evaluate 60 single and 25 multi-API queries from 6popular Python libraries and show that across-the-board CodeScholar generatesmore realistic, diverse, and concise examples. In addition, we show thatCodeScholar not only helps developers but also LLM-powered programmingassistants generate correct code in a program synthesis setting.

CodeScholar: Growing Idiomatic Code Examples