Empirical Investigation of Quantum Computing Toolchains and Algorithms : Mining Stack Overflow Repository

• URL: http://arxiv.org/abs/2604.15512v1
• Date: Thu, 16 Apr 2026 20:40:15 GMT
• Title: Empirical Investigation of Quantum Computing Toolchains and Algorithms : Mining Stack Overflow Repository
• Abstract summary: We analyze 1,404 Stack Overflow posts related to quantum computing topics.<n>We identify the main discussion topics, their popularity, and the tools, programming languages, and quantum algorithms referenced by practitioners.
• Score: 1.4760094700012518
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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