35 citations · 98 across the 9 of their papers we have counts for
9 papers
An Empirical Analysis of Compatibility Issues for Industrial Mobile Games
Zihe Song, Yingfeng Chen, Lei Ma +4
Detecting and fixing compatibility issues is critical for mobile game development. The rapid evolution of mobile operating systems and device fragmentation make it challenging for…
DyCL: Dynamic Neural Network Compilation Via Program Rewriting and Graph Optimization
Simin Chen, Shiyi Wei, Cong Liu +1
DL compiler's primary function is to translate DNN programs written in high-level DL frameworks such as PyTorch and TensorFlow into portable executables. These executables can then…
HateModerate: Testing Hate Speech Detectors against Content Moderation Policies
Jiangrui Zheng, Xueqing Liu, Guanqun Yang +5
To protect users from massive hateful content, existing works studied automated hate speech detection. Despite the existing efforts, one question remains: do automated hate speech…
TestAug: A Framework for Augmenting Capability-based NLP Tests
Guanqun Yang, Mirazul Haque, Qiaochu Song +2
The recently proposed capability-based NLP testing allows model developers to test the functional capabilities of NLP models, revealing functional failures that cannot be detected…
GLIB: Towards Automated Test Oracle for Graphically-Rich Applications
Ke Chen, Yufei Li, Yingfeng Chen +3
Graphically-rich applications such as games are ubiquitous with attractive visual effects of Graphical User Interface (GUI) that offers a bridge between software applications and e…
An Empirical Analysis of UI-based Flaky Tests
Alan Romano, Zihe Song, Sampath Grandhi +2
Flaky tests have gained attention from the research community in recent years and with good reason. These tests lead to wasted time and resources, and they reduce the reliability o…
VET: Identifying and Avoiding UI Exploration Tarpits
Wenyu Wang, Wei Yang, Tianyin Xu +1
Despite over a decade of research, it is still challenging for mobile UI testing tools to achieve satisfactory effectiveness, especially on industrial apps with rich features and l…
MULDEF: Multi-model-based Defense Against Adversarial Examples for Neural Networks
Siwakorn Srisakaokul, Yuhao Zhang, Zexuan Zhong +3
Despite being popularly used in many applications, neural network models have been found to be vulnerable to adversarial examples, i.e., carefully crafted examples aiming to mislea…
Testing Untestable Neural Machine Translation: An Industrial Case
Wujie Zheng, Wenyu Wang, Dian Liu +6
Neural Machine Translation (NMT) has been widely adopted recently due to its advantages compared with the traditional Statistical Machine Translation (SMT). However, an NMT system…