Paper Info
Title
GLIB: towards automated test oracle for graphically-rich applications
Abstract
ABSTRACTGraphically-rich applications such as games are ubiquitous with attractive visual effects of Graphical User Interface (GUI) that offers a bridge between software applications and end-users. However, various types of graphical glitches may arise from such GUI complexity and have become one of the main component of software compatibility issues. Our study on bug reports from game development teams in NetEase Inc. indicates that graphical glitches frequently occur during the GUI rendering and severely degrade the quality of graphically-rich applications such as video games. Existing automated testing techniques for such applications focus mainly on generating various GUI test sequences and check whether the test sequences can cause crashes. These techniques require constant human attention to captures non-crashing bugs such as bugs causing graphical glitches. In this paper, we present the first step in automating the test oracle for detecting non-crashing bugs in graphically-rich applications. Specifically, we propose GLIB based on a code-based data augmentation technique to detect game GUI glitches. We perform an evaluation of GLIB on 20 real-world game apps (with bug reports available) and the result shows that GLIB can achieve 100% precision and 99.5% recall in detecting non-crashing bugs such as game GUI glitches. Practical application of GLIB on another 14 real-world games (without bug reports) further demonstrates that GLIB can effectively uncover GUI glitches, with 48 of 53 bugs reported by GLIB having been confirmed and fixed so far.
Year
DOI
Venue
2021
10.1145/3468264.3468586
Foundations of Software Engineering
Keywords
DocType
Citations 
Automated Test Oracle, Game Testing, GUI Testing, Deep Learning
Conference
1
PageRank 
References 
Authors
0.35
23
6
Name
Order
Citations
PageRank
Ke Chen120.69
Yufei Li210712.31
yingfeng chen36913.64
Changjie Fan45721.37
Zhipeng Hu5123.48
Wei Yang643720.57