68 citations · 93 across the 39 of their papers we have counts for
13 papers · 1 filter
A Comprehensive Study of Deep Learning Model Fixing Approaches
Hanmo You, Zan Wang, Zishuo Dong +3
Deep Learning (DL) has been widely adopted in diverse industrial domains, including autonomous driving, intelligent healthcare, and aided programming. Like traditional software, DL…
QMon: Monitoring the Execution of Quantum Circuits with Mid-Circuit Measurement and Reset
Ning Ma, Jianjun Zhao, Foutse Khomh +2
Unlike classical software, where logging and runtime tracing can effectively reveal internal execution status, quantum circuits possess unique properties, such as the no-cloning th…
M2QCode: A Model-Driven Framework for Generating Multi-Platform Quantum Programs
Xiaoyu Guo, Shinobu Saito, Jianjun Zhao
With the growing interest in quantum computing, the emergence of quantum supremacy has marked a pivotal milestone in the field. As a result, numerous quantum programming languages…
QuanBench: Benchmarking Quantum Code Generation with Large Language Models
Xiaoyu Guo, Minggu Wang, Jianjun Zhao
Large language models (LLMs) have demonstrated good performance in general code generation; however, their capabilities in quantum code generation remain insufficiently studied. Th…
Is Measurement Enough? Rethinking Output Validation in Quantum Program Testing
Jiaming Ye, Xiongfei Wu, Shangzhou Xia +2
As quantum computing continues to emerge, ensuring the quality of quantum programs has become increasingly critical. Quantum program testing has emerged as a prominent research are…
When Abstraction Breaks Physics: Rethinking Modular Design in Quantum Software
Jianjun Zhao
Abstraction is a fundamental principle in classical software engineering, which enables modularity, reusability, and scalability. However, quantum programs adhere to fundamentally…
NovaQ: Improving Quantum Program Testing through Diversity-Guided Test Case Generation
Tiancheng Jin, Shangzhou Xia, Jianjun Zhao
Quantum programs are designed to run on quantum computers, leveraging quantum circuits to solve problems that are intractable for classical machines. As quantum computing advances,…
Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees
Guanqin Zhang, Kota Fukuda, Zhenya Zhang +4
The vulnerability of neural networks to adversarial perturbations has necessitated formal verification techniques that can rigorously certify the quality of neural networks. As the…
Quantum-Based Software Engineering
Jianjun Zhao
Quantum computing has demonstrated the potential to solve computationally intensive problems more efficiently than classical methods. Many software engineering tasks, such as test…
QuanUML: Towards A Modeling Language for Model-Driven Quantum Software Development
Xiaoyu Guo, Shinobu Saito, Jianjun Zhao
This paper introduces QuanUML, an extension of the Unified Modeling Language (UML) tailored for quantum software systems. QuanUML integrates quantum-specific constructs, such as qu…
Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification
Kota Fukuda, Guanqin Zhang, Zhenya Zhang +2
Formal verification is a rigorous approach that can provably ensure the quality of neural networks, and to date, Branch and Bound (BaB) is the state-of-the-art that performs verifi…
A Black-box Testing Framework for Oracle Quantum Programs
Peixun Long, Jianjun Zhao
Oracle quantum programs are a fundamental class of quantum programs that serve as a critical bridge between quantum computing and classical computing. Many important quantum algori…
Unveiling Code Clones in Quantum Programming: An Empirical Study with Qiskit
Kenta Manoku, Jianjun Zhao
Code clones, referring to identical or similar code fragments, have long posed challenges in classical programming, impacting software quality, maintainability, and scalability. Ho…