kirancodes.me
To Proof Maintenance & Beyond!

AG3: Automated Game GUI Text Glitch Detection Based on Computer Vision

Xiaoyun Liang, Jiayi Qi, Yongqiang Gao, Chao Peng, Ping Yang

Abstract

With the advancement of device software and hardware performance, and the evolution of game engines, an increasing number of emerging high-quality games are captivating game players from all around the world who speak different languages. However, due to the vast fragmentation of the device and platform market, a well-tested game may still experience text glitches when installed on a new device with an unseen screen resolution and system version, which can significantly impact the user experience. In our testing pipeline, current testing techniques for identifying multilingual text glitches are laborious and inefficient. In this paper, we present AG3, which offers intelligent game traversal, precise visual text glitch detection, and integrated quality report generation capabilities. Our empirical evaluation and internal industrial deployment demonstrate that AG3 can detect various real-world multilingual text glitches with minimal human involvement.

BibTeX
@inproceedings{Liang-al:FSE23,
  author    = {Xiaoyun Liang and
               Jiayi Qi and
               Yongqiang Gao and
               Chao Peng and
               Ping Yang},
  title     = {{AG3:} Automated Game {GUI} Text Glitch Detection Based on Computer Vision},
  booktitle = {{ESEC/SIGSOFT} {FSE}},
  pages     = {1879--1890},
  publisher = {{ACM}},
  year      = {2023},
}

Related papers