1 citations · 1 across the 3 of their papers we have counts for
5 papers
Optimization-Aware Test Generation for Deep Learning Compilers
Qingchao Shen, Zan Wang, Haoyang Ma +5
Deep Learning (DL) compilers have been widely utilized to optimize DL models for efficient deployment across various hardware. Due to their vital role in the DL ecosystem, ensuring…
An Empirical Study of Bugs in Data Visualization Libraries
Weiqi Lu, Yongqiang Tian, Xiaohan Zhong +4
Data visualization (DataViz) libraries play a crucial role in presentation, data analysis, and application development, underscoring the importance of their accuracy in transformin…
Bounded Exhaustive Random Program Generation for Testing Solidity Compilers
Haoyang Ma, Alastair F. Donaldson, Qingchao Shen +3
By July 2025, smart contracts collectively manage roughly $120 billion in assets. With Solidity remaining the dominant language for smart contract development, the correctness of S…
From Informal to Formal -- Incorporating and Evaluating LLMs on Natural Language Requirements to Verifiable Formal Proofs
Jialun Cao, Yaojie Lu, Meiziniu Li +9
The research in AI-based formal mathematical reasoning has shown an unstoppable growth trend. These studies have excelled in mathematical competitions like IMO and have made signif…
A Tale of Two DL Cities: When Library Tests Meet Compiler
Qingchao Shen, Yongqiang Tian, Haoyang Ma +5
Deep Learning (DL) compilers typically load a DL model and optimize it with intermediate representation.Existing DL compiler testing techniques mainly focus on model optimization s…