ORIGINAL RESEARCH article
Front. Artif. Intell.
Sec. Machine Learning and Artificial Intelligence
Volume 8 - 2025 | doi: 10.3389/frai.2025.1662220
This article is part of the Research TopicAdvancing AI-Driven Code Generation and Synthesis: Challenges, Metrics, and Ethical ImplicationsView all articles
A Quantum-Inspired, Biomimetic, and Fractal Framework for Self-Healing AI Code Generation: Bridging Responsible Automation and Emergent Intelligence
Provisionally accepted
- 1VMC MAR COM Inc. DBA HeyDonto, Knoxville, United States
- 2Department of Computer Science, Islamic Azad University, South Tehran Branch, Tehran, Iran
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AI-powered code generation systems available today are ill-suited for deployment in agile software development contexts due to various limitations. The paper proposes a self-healing counterpart framework based on quantum-inspired optimization, biomimetic and fractal principles to solve these fundamental issues. Our Quantum Solution Space Manager keeps more than one candidate solution in superposition states. In doing so, it achieves 94.7% code correctness (versus 87.3%) with respect to a leading approach. The biomimetic error detection system, inspired by biological immune mechanisms, has a sensitivity of 95.2 per cent, with a false-positive rate of 2.3 per cent. Effectively, 94.7 per cent of detected errors are automatically corrected. Fractal optimization allows for a considerable 89.4% success rate during cross-architectural propagation while distributed intelligence networks allow different intelligences and agents to learn together. The framework is validated as effective through an analysis of 15,000 software engineering tasks across five domains. This helps reduce the critical error rate by 54% and the remaining development time by 41%, along with notable improvements in maintainability and security metrics. The results lay down the path for adaptive software development systems to create a responsible automation and emergent intelligence.
Keywords: Self-healing AI systems, Quantum-inspired optimization, Biomimetic computing, Fractal scalability, Adaptive code generation
Received: 10 Jul 2025; Accepted: 30 Sep 2025.
Copyright: © 2025 Nehzati. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Mohammadreza Nehzati, reza.nehzati2023@gmail.com
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