activity
20222026
most citedQuantum Software Engineering: Roadmap and Challenges Ahead

68 citations · 93 across the 39 of their papers we have counts for

collaborators
Showing 2024Show all

8 papers · 1 filter

quant-ph2024

Assessing Superposition-Targeted Coverage Criteria for Quantum Neural Networks

Minqi Shao, Jianjun Zhao

Quantum Neural Networks (QNNs) have achieved initial success in various tasks by integrating quantum computing and neural networks. However, growing concerns about their reliabilit…

cs.SD2024

Zero-Shot Voice Conversion via Content-Aware Timbre Ensemble and Conditional Flow Matching

Yu Pan, Yuguang Yang, Jixun Yao +2

Despite recent advances in zero-shot voice conversion (VC), achieving speaker similarity and naturalness comparable to ground-truth recordings remains a significant challenge. In t…

cs.PL2024

Dataflow-Based Optimization for Quantum Intermediate Representation Programs

Junjie Luo, Haoyu Zhang, Jianjun Zhao

This paper proposes QDFO, a dataflow-based optimization approach to Microsoft QIR. QDFO consists of two main functions: one is to preprocess the QIR code so that the LLVM optimizer…

cs.SE2024★ 2 cited

Quantum Circuit Ansatz: Patterns of Abstraction and Reuse of Quantum Algorithm Design

Xiaoyu Guo, Takahiro Muta, Jianjun Zhao

Quantum computing holds the potential to revolutionize various fields by efficiently tackling complex problems. At its core are quantum circuits, sequences of quantum gates manipul…

cs.SE2024★ 1 cited

Quantum Concolic Testing

Shangzhou Xia, Jianjun Zhao, Fuyuan Zhang +1

This paper presents the first concolic testing framework explicitly designed for quantum programs. The framework introduces quantum constraint generation methods for quantum contro…

cs.SE2024★ 68 cited

Quantum Software Engineering: Roadmap and Challenges Ahead

Juan M. Murillo, Jose Garcia-Alonso, Enrique Moguel +13

As quantum computers advance, the complexity of the software they can execute increases as well. To ensure this software is efficient, maintainable, reusable, and cost-effective -k…

cs.SE2024

GenCode: A Generic Data Augmentation Framework for Boosting Deep Learning-Based Code Understanding

Zeming Dong, Qiang Hu, Xiaofei Xie +4

Pre-trained code models lead the era of code intelligence, with multiple models designed with impressive performance. However, one important problem, data augmentation for code dat…

cs.SE2024

On Repairing Quantum Programs Using ChatGPT

Xiaoyu Guo, Jianjun Zhao, Pengzhan Zhao

Automated Program Repair (APR) is a vital area in software engineering aimed at generating automatic patches for vulnerable programs. While numerous techniques have been proposed f…