Maryam Tavassoli Sabzevari

2papers

2 Papers

26.4SEApr 16Code
Empirical Investigation of Quantum Computing Toolchains and Algorithms : Mining Stack Overflow Repository

Maryam Tavassoli Sabzevari, Arif Ali Khan

Quantum computing (QC) is increasingly transitioning toward practical and industrial adoption, highlighting the need to understand how developers engage with quantum technologies. In this study, we analyze 1,404 Stack Overflow posts related to quantum computing topics, including quantum programming, tools, and algorithms, to investigate real-world developer discussions. Using topic modeling and quantitative analysis, we identify the main discussion topics, their popularity, and the tools, programming languages, and quantum algorithms referenced by practitioners. We further assess the difficulty of developer questions using two metrics: (i) the percentage of questions without accepted answers and (ii) the median time required to receive an accepted answer. Our findings reveal seven main topics, with hybrid quantum--classical computing and quantum circuit implementation emerging as the most prevalent. We observe that Qiskit and Q-sharp dominate developer discussions, while Grover's and Shor's algorithms are the most frequently referenced. Moreover, our analysis highlights differences in engagement and difficulty across topics, tools, and algorithms, indicating varying levels of maturity and community support. These findings provide actionable insights for researchers, tool developers, and educators, supporting improvements in usability, documentation, and learning resources in quantum software engineering. To support transparency and reproducibility, the open-source dataset used in this study is publicly available at Zenodo.

SEJun 10, 2024
$Classi|Q\rangle$ Towards a Translation Framework To Bridge The Classical-Quantum Programming Gap

Matteo Esposito, Maryam Tavassoli Sabzevari, Boshuai Ye et al.

Quantum computing, albeit readily available as hardware or emulated on the cloud, is still far from being available in general regarding complex programming paradigms and learning curves. This vision paper introduces $Classi|Q\rangle$, a translation framework idea to bridge Classical and Quantum Computing by translating high-level programming languages, e.g., Python or C++, into a low-level language, e.g., Quantum Assembly. Our idea paper serves as a blueprint for ongoing efforts in quantum software engineering, offering a roadmap for further $Classi|Q\rangle$ development to meet the diverse needs of researchers and practitioners. $Classi|Q\rangle$ is designed to empower researchers and practitioners with no prior quantum experience to harness the potential of hybrid quantum computation. We also discuss future enhancements to $Classi|Q\rangle$, including support for additional quantum languages, improved optimization strategies, and integration with emerging quantum computing platforms.