21 citations · 21 across the 7 of their papers we have counts for
7 papers
Combating Missed Recalls in E-commerce Search: A CoT-Prompting Testing Approach
Shengnan Wu, Yongxiang Hu, Yingchuan Wang +6
Search components in e-commerce apps, often complex AI-based systems, are prone to bugs that can lead to missed recalls - situations where items that should be listed in search res…
An Image is Worth a Thousand Toxic Words: A Metamorphic Testing Framework for Content Moderation Software
Wenxuan Wang, Jingyuan Huang, Jen-tse Huang +4
The exponential growth of social media platforms has brought about a revolution in communication and content dissemination in human society. Nevertheless, these platforms are being…
Prism: Revealing Hidden Functional Clusters from Massive Instances in Cloud Systems
Jinyang Liu, Zhihan Jiang, Jiazhen Gu +6
Ensuring the reliability of cloud systems is critical for both cloud vendors and customers. Cloud systems often rely on virtualization techniques to create instances of hardware re…
Identifying Performance Issues in Cloud Service Systems Based on Relational-Temporal Features
Wenwei Gu, Jinyang Liu, Zhuangbin Chen +7
Cloud systems are susceptible to performance issues, which may cause service-level agreement violations and financial losses. In current practice, crucial metrics are monitored per…
Validating Multimedia Content Moderation Software via Semantic Fusion
Wenxuan Wang, Jingyuan Huang, Chang Chen +5
The exponential growth of social media platforms, such as Facebook and TikTok, has revolutionized communication and content publication in human society. Users on these platforms c…
Detecting Deep Neural Network Defects with Data Flow Analysis
Jiazhen Gu, Huanlin Xu, Yangfan Zhou +3
Deep neural networks (DNNs) are shown to be promising solutions in many challenging artificial intelligence tasks. However, it is very hard to figure out whether the low precision…
DeepProf: Performance Analysis for Deep Learning Applications via Mining GPU Execution Patterns
Jiazhen Gu, Huan Liu, Yangfan Zhou +1
Deep learning applications are computation-intensive and often employ GPU as the underlying computing devices. Deep learning frameworks provide powerful programming interfaces, but…