Quantum Software Analytics: Opportunities and Challenges
Thong Hoang, Hoa Khanh Dam, Tingting Bi, Qinghua Lu, Zhenchang Xing,, Liming Zhu, Lam Duc Nguyen, Shiping Chen

TL;DR
This paper explores the integration of software analytics into quantum software development, highlighting unique challenges and opportunities in the emerging field of quantum computing applications.
Contribution
It provides a comprehensive overview of how classical software analytics techniques can be adapted for quantum software development processes.
Findings
Identifies key challenges in quantum software lifecycle management
Proposes potential analytics techniques for quantum software development
Highlights opportunities for improving quantum software engineering practices
Abstract
Quantum computing systems depend on the principles of quantum mechanics to perform multiple challenging tasks more efficiently than their classical counterparts. In classical software engineering, the software life cycle is used to document and structure the processes of design, implementation, and maintenance of software applications. It helps stakeholders understand how to build an application. In this paper, we summarize a set of software analytics topics and techniques in the development life cycle that can be leveraged and integrated into quantum software application development. The results of this work can assist researchers and practitioners in better understanding the quantum-specific emerging development activities, challenges, and opportunities in the next generation of quantum software.
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Taxonomy
TopicsCloud Computing and Resource Management · Scientific Computing and Data Management · Quantum Computing Algorithms and Architecture
