Video Game Testing using Rendering Information and Pattern Recognition

Please enable javascript in your browser.

Taesiri, Mohammad Reza | 2017

552 Viewed

Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 49983 (19)
University: Sharif University of Technology
Department: Computer Engineering
Advisor(s): Habibi, Jafar
Abstract:
After passing many iterations of tests, video games still suffers from major bugs after they’ve been released. One of these problems is the incompatibility between the video game and target audience’s computers. In this thesis, we have proposed a testing strategy by utilizing Cloud Computing infrastructure for video games and Deep Convolutional Neural Networks. We used a simple algorithm to make the graphical output of a video game partially deterministic and thus it’s possible for us to compare different instances of the game in Draw Call level. We’ve used two separate Deep Convolutional Neural Networks for 1. detecting visual artifacts in frames and 2. comparing pairs of Draw Calls for finding possible errors and faults. Our proposed approach is able to find a range of bugs that regular methodologies are unable to find
Keywords:
Cloud Computing ; Pattern Recognition ; Deep Learning ; Convolutional Neural Network ; Deep Neural Networks ; Video Game Testing ; Automated Testing