47 citations · 47 across the 1 of their papers we have counts for
6 papers
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…
A Comprehensive Study on Challenges in Deploying Deep Learning Based Software
Zhenpeng Chen, Yanbin Cao, Yuanqiang Liu +3
Deep learning (DL) becomes increasingly pervasive, being used in a wide range of software applications. These software applications, named as DL based software (in short as DL soft…
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…
CoMID: Context-based Multi-Invariant Detection for Monitoring Cyber-Physical Software
Yi Qin, Tao Xie, Chang Xu +2
Cyber-physical software continually interacts with its physical environment for adaptation in order to deliver smart services. However, the interactions can be subject to various e…
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…
Mining Behavioral Patterns from Millions of Android Users
Xuanzhe Liu, Huoran Li, Xuan Lu +4
The prevalence of smart mobile devices has promoted the popularity of mobile applications (a.k.a. apps). Supporting mobility has become a promising trend in software engineering re…