18 citations · 18 across the 8 of their papers we have counts for
5 papers · 1 filter
Are We Testing the Wrong Quantum Bugs? A Study of Fault Representation Gaps in Quantum Software Testing
Asif Mohammed Saad, Ahsanul Ameen Sabit, Jonah Brandenburgh +3
Quantum software relies on compilers, intermediate representations, and execution frameworks that transform programs before execution. Faults in these components can change the beh…
Tensor Algebraic Property Skeletons: Amplifying Property-Based Testing for AI Compilers
Yuxin Qiu, Ben Limpanukorn, Seongmin Lee +3
Deep learning (DL) compilers such as TVM and ONNX-MLIR lower tensor computation graphs into optimized executables for target backends. Testing these compilers has made substantial…
Finding Compiler-Platform Interaction Bugs in Deep Learning Pipelines via Cross-Layer Constraints
Yuxin Qiu, Jiyuan Wang, Ronak Badhe +3
The growing deployment of artificial intelligence (AI) necessitates robust deep learning (DL) compilers, such as TVM and ONNX-MLIR. These compilers take as input high-level AI mode…
Isolating Recurring Backend-Dependent Abnormal Patterns on NISQ Quantum Devices
Zhenyu Qi, Haotang Li, Mominul Islam +3
Quantum hardware remains highly susceptible to noise, making compilation a critical step for obtaining reliable execution on existing devices. Today's quantum compilers approximate…
Needle in the Repo: A Benchmark for Maintainability in AI-Generated Repository Edits
Haichao Zhu, Qian Zhang, Jiyuan Wang +2
AI coding agents can now complete complex programming tasks, but existing evaluations largely emphasize behavioral correctness and often overlook maintainability risks such as weak…