SLR_Games_Testing_Studies_2010_2025

This dataset contains the list of primary studies analyzed in a Systematic Literature Review (SLR) on automated software testing for digital games and virtual simulators, covering the period from 2010 to 2025. The dataset includes 54 selected studies after applying predefined inclusion and exclusion criteria. For each study, the dataset provides structured information such as publication metadata, type of algorithms used (e.g., Machine Learning, Deep Learning, Computer Vision), testing categories (e.g., functional, visual, gameplay), tools and frameworks, evaluation metrics, platforms, and reported challenges and benefits. The data were extracted and classified following established guidelines for systematic literature reviews in software engineering. This dataset aims to support transparency, reproducibility, and further research in the area of automated testing for games and simulators.