Automated API Documentation Validation & Enhancement Leveraging Semantic Graph Analysis and Reinforcement Learning
Year: 2025
Type: article
Abstract: **Abstract:** This paper introduces a novel framework for automating the validation and enhancement of API documentation. Existing approaches often rely on manual review or rudimentary static analysis, struggling to capture nuanced inconsistencies and gaps. Our system, utilizing semantic graph analysis and reinforcement learning (RL), dynamically constructs a knowledge graph representing API functionality, identifies discrepancies between code and documentation, and autonomously suggests improvements. This approach enables proactive documentation maintenance, reduced developer friction, and accelerated API adoption, impacting software development productivity and reducing technical support costs. We predict a 20% reduction in developer onboarding time and a 10% decrease in support tickets related to API usage within two years of implementation. --- *This document is a part of the Freederia Research Archive. Explore our complete collection of advanced research at [en.freederia.com](https://en.freederia.com), or visit our main portal at [freederia.com](https://freederia.com) to learn more about our mission and other initiatives.*
Source: Figshare
Authors: KYUNGJUN, LIM, Researcher, Freederia AI
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6902265118
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