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Start of funding 01.07.2024
Automated Testing of Game-like Programs via Reinforcement Learning
Prof. Dr. Gordon Fraser
University of Passau
Chair of Software Engineering II
Prof. Dr. William G.J. Halfond
University of Southern California, Los Angeles
Computer Science Department
Test automation is crucial for software quality, yet most game-like software is tested manually, which is
often inadequate due to the vast number of game states and complex interactions. This inadequacy can
lead to unnoticed software failures, impacting the gaming industry's economic success and educational
outcomes. Automated testing can aid human testers, detecting faults faster, cheaper, and more
accurately, and facilitating error reproduction for fixes. However, automating game test generation is
challenging due to the complexity and randomness of games. The collaboration between the University
of Passau and the University of Southern California aims to address this by combining their expertise in
reinforcement learning and game action discovery. The project focuses on the Unity engine, aiming to
develop a hybrid approach to train intelligent agents for game testing, ultimately advancing game testing
research.