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Dataset
Data sources: ZENODO
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Self-Healing Cloud Infrastructure Systematic Review: Reproducibility Dataset

Authors: Anjum, Mateen Ali;

Self-Healing Cloud Infrastructure Systematic Review: Reproducibility Dataset

Abstract

Reproducibility dataset for a PRISMA 2020 systematic review of machine-learning approaches to self-healing cloud infrastructure (autonomous detection, diagnosis, decision, and recovery), covering 341 included studies published 2022 to 2026 and 139 excluded records. The archive contains the master coded dataset (canonical_studies.csv), per-paper extraction records with CASP and PROBAST-adapted risk-of-bias scoring rationale, derived cross-tabulations, the title and abstract screening decision trail, a statistical re-derivation script for the Fisher exact and Wilson 95 percent confidence interval gap comparisons, and figure-generation source. Data and code only; the full methodology and rubrics are described in the associated article and its supplementary appendices.

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