M. Kneidinger, M. Feneberger, R. Plösch: Using GPT-4 for Source Code Documentation, 50th Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA), Paris, France, August 28-30, 2024. poster
Writing good software documentation imposes significant effort. Large Language Models (LLMs) could potentially streamline that process, though. So, the question arises whether current LLMs are able to generate valid code documentation for classes and methods on basis of the bare code. According to literature, various such models have the capability to generate documentation that is on par with or even superior to reference documentation. In our experimental study using zero-shot prompting, we found that the model GPT-4 by OpenAI leads to poor results when measuring similarity to the reference documentation on class level. Thus, GPT-4 is not yet usable for generating class documentation. On method level, however, the model achieved higher similarity ratings and can be considered applicable for the use case.