Self-Healing AI: An Autonomous Deep Learning Approach for Software Error Correction
DOI:
https://doi.org/10.63345/2tfbg044Keywords:
Self-Healing AI, Autonomous Software Repair, Deep Learning, Reinforcement Learning, Software Error Correction, AI-driven DebuggingAbstract
With the increasing complexity of modern software systems, errors and vulnerabilities
are inevitable. Traditional debugging and patching mechanisms require human
intervention, leading to delays and potential security risks. Self-healing AI presents an
innovative approach by leveraging deep learning to autonomously detect, diagnose, and
correct software errors in real time. This paper explores the mechanisms of self-healing
AI, detailing its core components, including automated bug detection, predictive error
analysis, and autonomous patch generation. By implementing reinforcement learning
and generative AI models, self-healing AI significantly enhances software resilience,
reducing downtime and improving system reliability. Empirical evaluations demonstrate
the effectiveness of this approach, highlighting its potential to revolutionize software
maintenance and cybersecurity.
Downloads
Downloads
Published
Issue
Section
License
Copyright (c) 2025 The journal retains copyright of all published articles, ensuring that authors have control over their work while allowing wide dissenmination.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Articles are published under the Creative Commons Attribution NonCommercial 4.0 License (CC BY NC 4.0), allowing others to distribute, remix, adapt, and build upon the work for non-commercial purposes while crediting the original author.
