Supplementary Data: Self-Healing Cloud Infrastructure Systematic Literature Review (108-Study Mapping, Quality Scores, and Risk of Bias Ratings)

Supplementary dataset for the systematic literature review "Self-Healing Cloud Infrastructure: A Systematic Review of Machine Learning Approaches for Autonomous Detection, Diagnosis, and Recovery" submitted to the Journal of Cloud Computing (Springer Nature). This CSV file contains the complete 108-study corpus mapping with the following fields per study: study identifier (D1-D15, R1-R17, H1-H14, S1-S21, E1-E29, C1-C12), BibTeX reference key, first author, publication year, venue type (journal/conference/preprint/workshop/thesis), self-healing phase assignment (DETECT/DIAGNOSE/DECIDE/RECOVER/Enabling Technologies/Cross-Phase Integration), primary ML technique, CASP quality assessment score (0-12), and PROBAST-adapted risk of bias ratings across four domains (Data Selection, Feature Engineering, Model Evaluation, Analysis Reporting).