Quantum Software Analytics: Opportunities and Challenges

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.