Content area

Abstract

Automated documentation of programming source code is a challenging task with significant practical and scientific implications for the developer community. We present a large language model (LLM)-based application that developers can use as a support tool to generate basic documentation for any publicly available repository. Over the last decade, several papers have been written on generating documentation for source code using neural network architectures. With the recent advancements in LLM technology, some open-source applications have been developed to address this problem. However, these applications typically rely on the OpenAI APIs, which incur substantial financial costs, particularly for large repositories. Moreover, none of these open-source applications offer a fine-tuned model or features to enable users to fine-tune. Additionally, finding suitable data for fine-tuning is often challenging. Our application addresses these issues which is available at https://pypi.org/project/readme-ready/.

Details

1009240
Title
Free and Customizable Code Documentation with LLMs: A Fine-Tuning Approach
Publication title
arXiv.org; Ithaca
Publication year
2024
Publication date
Dec 1, 2024
Section
Computer Science
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2024-12-03
Milestone dates
2024-12-01 (Submission v1)
Publication history
 
 
   First posting date
03 Dec 2024
ProQuest document ID
3138989510
Document URL
https://www.proquest.com/working-papers/free-customizable-code-documentation-with-llms/docview/3138989510/se-2?accountid=208611
Full text outside of ProQuest
Copyright
© 2024. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2024-12-04
Database
2 databases
  • ProQuest One Academic
  • ProQuest One Academic