Empirical Investigation of Quantum Computing Toolchains and Algorithms : Mining Stack Overflow Repository
Maryam Tavassoli Sabzevari, Arif Ali Khan
TLDR
This paper analyzes Stack Overflow data to understand developer engagement with quantum computing tools and algorithms, revealing key trends and challenges.
Key contributions
- Analyzed 1,404 Stack Overflow posts on quantum computing topics using topic modeling.
- Identified 7 main discussion topics, with hybrid quantum-classical computing most prevalent.
- Found Qiskit and Q-sharp are dominant tools; Grover's and Shor's are the most referenced algorithms.
- Assessed question difficulty, revealing varying maturity and community support across topics and tools.
Why it matters
This study provides crucial insights into the real-world challenges and interests of quantum computing developers. Its findings can guide researchers, tool developers, and educators in improving quantum software engineering, documentation, and learning resources, accelerating practical adoption.
Original 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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