The challenge of generating and evolving real-life like synthetic data when real data is not available - a systematic literature reviewTitle and Abstract Analysis and Full Text Analysis results

The objective of this Systematic Literature Review (SLR) is to identify existing approaches for creating and evolving synthetic data
without using real-life data. The research team consisted of four researchers. Screening, quality assessment, and data extraction were
conducted in pairs.
Our search found 1013 publications in IEEE Xplore, ACM Digital Library, and SCOPUS. We extracted data from 75 of those
publications and identified 37 approaches that answer our research question partly.
Further research is necessary to enhance the existing approaches to the point where either one or a combination of them answers
the full research question of this SLR.