Auto-Documenation for Software Development

TL;DR

Autodoc is an AI-powered tool that leverages deep learning to automatically generate meaningful documentation from code snippets, enhancing developer productivity and code maintainability.

Contribution

This paper introduces Autodoc, a novel deep learning-based system that automatically translates code into descriptive comments and integrates seamlessly with IDEs and hosting platforms.

Findings

Autodoc can generate accurate code comments using deep learning.

The tool integrates with IDEs and Git platforms for streamlined documentation.

Autodoc improves documentation speed and quality in software development.

Abstract

Software documentation is an essential but labor intensive task that often requires a dedicated team of developers to ensure coverage and accuracy. Good documentation will help shorten the development cycle and improve the overall team efficiency as well as maintainability. In today's crowd-driven development environment, good documentation can go a long way in building a developer community from scratch. To that end, we took the first steps in building a tool called Autodoc that can assist software developers in writing better documentation faster. Autodoc goes beyond traditional boilerplate template generation. Our integrated tool uses Deep Learning methods to construct a semantic understanding of the code. Just like machine translation in natural languages, Autodoc can translate snippets of code to comments, and insert them as short summaries inside the docstring. We also demonstrate the integration of Autodoc as an IDE plugin as well as a web hook from within software hosting platforms when submitting auto-documented code to user's Git repository.