САМОВІДНОВЛЮВАНІ ФРОНТЕНД-СИСТЕМИ: ВИЯВЛЕННЯ АНОМАЛІЙ НА ОСНОВІ ШТУЧНОГО ІНТЕЛЕКТУ ТА АВТОМАТИЗОВАНЕ ВІДНОВЛЕННЯ

Yuliia Horbenko

doi:10.30890/2567-5273.2025-38-01-042

Authors

Yuliia Horbenko National Transport University https://orcid.org/0009-0004-5451-4530

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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References

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

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