SELF-HEALING FRONT-END SYSTEMS: AI-DRIVEN ANOMALY DETECTION AND AUTOMATED RECOVERY

Authors

DOI:

https://doi.org/10.30890/2567-5273.2025-38-01-042

Keywords:

interface resilience, UI self-repair, user telemetry, SPA architecture, interpretable AI, reinforcement learning, runtime patching.

Abstract

The relevance of this research is determined by the increasing complexity of modern front-end architectures, which operate in high-dynamic environments with numerous asynchronous requests, multi-level UI components, and unpredictable user interaction scen

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Published

2025-04-30

How to Cite

Горбенко, Ю. (2025). SELF-HEALING FRONT-END SYSTEMS: AI-DRIVEN ANOMALY DETECTION AND AUTOMATED RECOVERY. Modern Engineering and Innovative Technologies, 1(38-01), 162–185. https://doi.org/10.30890/2567-5273.2025-38-01-042

Issue

No. 38-01 (2025)

Section

Articles

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Copyright (c) 2025 Authors

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.