Using an LLM to Help With Code Understanding
Carnegie Mellon University · Google (United States)
Abstract
Understanding code is challenging, especially when working in new and complex development environments. Code comments and documentation can help, but are typically scarce or hard to navigate. Large language models (LLMs) are revolutionizing the process of writing code. Can they do the same for helping understand it? In this study, we provide a first investigation of an LLM-based conversational UI built directly in the IDE that is geared towards code understanding. Our IDE plugin queries OpenAI's GPT-3.5-turbo model with four high-level requests without the user having to write explicit prompts: to explain a highlighted section of code, provide details of API calls used in the code, explain key domain-specific…
Citation impact
- FWCI
- 186.81
- Percentile
- 100%
- References
- 58
Authors
5Topics & keywords
- Plug-in
- Computer science
- Code (set theory)
- Documentation
- World Wide Web
- Domain (mathematical analysis)
- Process (computing)
- Software engineering