Quantum computing promises to offer significant computational advantages over classical computing, leveraging principles such as superposition and entanglement. This necessitates effective metrics and measurement techniques for evaluating quantum systems, aiding in their development and performance optimization. However, due to fundamental differences in computing paradigms, and current immaturity of quantum software abstractions, classical software and hardware metrics may not directly apply to quantum computing, where the distinction between software and hardware can still be somewhat indiscernible compared to classical computing. This paper provides a comprehensive review of existing quantum software and hardware metrics in the scientific literature, highlighting key challenges in the field. Additionally, it investigates the application of Functional Size Measurement (FSM) based on COSMIC ISO 19761 to measure quantum software. Three FSM approaches are analyzed by applying them to Shor’s and Grover’s algorithms, with measurement results compared to assess their effectiveness. A comparative analysis highlights the strengths and limitations of each approach, emphasizing the need for further refinement. The insights from this study contribute to the advancement of quantum metrics, especially software metrics and measurement, paving the way for the development of a unified and standardized approach to quantum software measurement and assessment.
Quantum computing promises to offer significant computational advantages over classical computing, leveraging principles such as superposition and entanglement. This necessitates effective metrics and measurement techniques for evaluating quantum systems, aiding in their development and performance optimization. However, due to fundamental differences in computing paradigms, and current immaturity of quantum software abstractions, classical software and hardware metrics may not directly apply to quantum computing, where the distinction between software and hardware can still be somewhat indiscernible compared to classical computing. This paper provides a comprehensive review of existing quantum software and hardware metrics in the scientific literature, highlighting key challenges in the field. Additionally, it investigates the application of Functional Size Measurement (FSM) based on COSMIC ISO 19761 to measure quantum software. Three FSM approaches are analyzed by applying them to Shor’s and Grover’s algorithms, with measurement results compared to assess their effectiveness. A comparative analysis highlights the strengths and limitations of each approach, emphasizing the need for further refinement. The insights from this study contribute to the advancement of quantum metrics, especially software metrics and measurement, paving the way for the development of a unified and standardized approach to quantum software measurement and assessment.
As quantum computing evolves, the need for quantum software measurement techniques has increased. Functional Size Measurement (FSM) has been adopted to measure quantum Software in three different approaches based on COSMIC ISO 19761. We examine the proposed approaches by analyzing the measurement results of their application on Shor’s and Grover’s algorithms. A comparative analysis reveals the strengths and limitations of each approach, emphasizing the need for continued refinement. The insights gained from this study are critical for developing a more unified approach for quantum software and pave the way to a standardized approach.
Rapid growth in quantum computing has created an urgent need to adapt traditional software engineering methodologies. Among these methodological challenges, software size measurement plays a central role in project estimation, quality assurance, and software engineering management. However, there is no consolidated understanding of how it should be applied to quantum software systems. This paper presents the first systematic literature review on quantum software size measurement, synthesizing existing approaches, and identifying key research gaps. An analysis of 16 studies shows that size measures span multiple abstraction levels, with most research focusing on adapting classical metrics, such as Lines of Code (LOC) and functional size, to quantum software systems. LOC continues to be used for sizing quantum code, while COSMIC Function Points (ISO 19761) have been extended to capture data movements in quantum components, enabling their application at the requirement, code, and circuit levels. At the specification and architectural design levels, the proposed measures include counts of quantum classes and methods as well as lines of architectural specifications. At the circuit level, quantum-specific constructs, such as qubits, gates, and measurements, are also incorporated. Additionally, software structure metrics, including cyclomatic complexity and Halstead metrics, are used to measure quantum software at both the code and design levels. Research output has grown since 2024, and is driven by academic groups, with minimal industrial participation. However, most metrics remain conceptual, lack empirical validation, and are not integrated into development life cycles, highlighting the immaturity and fragmentation of current proposals and the need for standardized frameworks.
The rapid evolution of quantum computing has led to growing interest in the development of systematic approaches to assess and manage quantum software. Among these, functional size measurement (FSM) offers a promising pathway for establishing metrics that can support project estimation, benchmarking, and quality assessment. This paper provides an overview of emerging efforts in quantum software functional size measurement with a focus on key concepts, challenges, and motivations. First, we examine the foundational principles of quantum computing in relation to the existing FSM methods, identifying both compatibilities and unique constraints. Building on this, we discuss the challenges that arise when applying FSM to quantum software, including the hardware-coupled nature of functionality, evolving semantics of data and measurement abstractions, gaps in tooling and standardization, and evolving role of FSM across the Noisy Intermediate-Scale Quantum (NISQ) and future faulttolerant eras. We then outline community-driven initiatives, such as the COSMIC Quantum Software Taskforce and the Fall 2024 Workshop, which highlight the increasing demand for structured measurement practices. By articulating these issues, this paper aims to present initial research efforts for quantum software functional size measurement and stimulate further exploration of measurement approaches that are both theoretically grounded and practically applicable in quantum software engineering.
Quantum computing, built on the principles of quantum mechanics, has emerged as a transformative paradigm with the potential to revolutionize computational capabilities, enabling solutions to problems that are currently intractable for classical systems. Quantum computing integrates hardware, architectures, and software for improved applications while utilizing superposition, entanglement, and interference to promote materials science, cryptography, optimization, and artificial intelligence. Sections introduce and describe the model components needed in order to create quantum processors, including qubits, quantum gates and control electronics, as well as a review of new developments in quantum software frameworks and programming tools. Notable examples, such as Shor’s algorithm for cryptographic caveat, Grover’s algorithm for inefficient search processes, and quantum-enhanced optimization, illuminate the position of quantum computing as a means of tackling tough problems that span disciplines, such as pharmaceuticals, predictors of climate, and finance modeling. However, the field continues to face significant challenges, like limited scalability, quantum gate error rates, qubit coherence times, and difficulties integrating with classical systems. Future efforts will focus on developing hybrid quantum-classical systems, scalable architectures, and industry- specific applications to transition quantum computing from exploration to practical deployment. This review provides a comprehensive analysis of quantum computing, covering its potential, trends, and challenges, while exploring hardware-software integration, classicalquantum comparisons, and insights to guide research and industry in unlocking its revolutionary possibility.
Quantum computers have the potential to provide an advantage over classical computers in a number of areas. Numerous metrics to benchmark the performance of quantum computers, ranging from their individual hardware components to entire applications, have been proposed over the years. Objective comparisons are further hampered in practice as different variations of the same metric are used, and the data disclosed together with a reported metric value is often not sufficient to reproduce the measurements. In this poster, we present our recent article, where we address these challenges by providing a review of metrics and benchmarks for quantum computers [1], including 1) a comprehensive collection of benchmarks allowing holistic comparisons of quantum computers, 2) a consistent format of the definitions across all metrics including a transparent description of the methodology and of the main assumptions and limitations, and 3) a reproducible approach by linking the metrics to open-source software used to evaluate them . We identify five areas where international standardization working groups could be established, namely: i) the identification and agreement on the categories of metrics that comprehensively benchmark device performance; ii) the identification and agreement on a set of well-established metrics that together comprehensively benchmark performance; iii) the identification of metrics specific to hardware platforms, including non-gate-based quantum computers; iv) inter-laboratory comparison studies to develop best practice guides for measurement methodology; and v) agreement on what data and software should be reported together with a metric value to ensure trust, transparency and reproducibility. We provide potential routes to advancing these areas. We expect that this work will accelerate the progress of quantum computing hardware towards quantum advantage. [1] D. Lall et al., A Review and Collection of Metrics and Benchmarks for Quantum Computers: Definitions, Methodologies and Software, arXiv:2502.06717.
Abstract The technological development of increasingly larger quantum processors on different quantum platforms raises the problem of how to fairly compare their performance, known as quantum benchmarking of quantum processors. This is a challenge that computer scientists have already faced when comparing classical processors, leading to the development of various mathematical tools to address it, but also to the identification of the limits of this problem. In this work, we briefly review the most important aspects of both classical processor benchmarks and the metrics comprising them, providing precise definitions and analyzing the quality attributes that they should exhibit. Subsequently, we analyze the intrinsic properties that characterize the paradigm of quantum computing and hinder the naive transfer of strategies from classical benchmarking. However, we can still leverage some of the lessons learned such as the quality attributes of a good benchmark such as relevance, reproducibility, fairness, verifiability and usability. Additionally, we review some of the most important metrics and benchmarks for quantum processors proposed in the literature, assessing what quality attributes they fulfill. Finally, we propose general guidelines for quantum benchmarking. These guidelines aim to pave the way for establishing a roadmap towards standardizing the performance evaluation of quantum devices, ultimately leading to the creation of an organization akin to the Standard Performance Evaluation Corporation (SPEC).