Abstract Until now, the quality problems of quantum software have been largely ignored. This chapter analyzes the applicability of models and metrics for quantum software and, to mitigate this lack of attention to quality issues, presents a set of metrics that have been proposed and empirically validated to characterize the complexity of quantum circuits in terms of their understandability. The validation experiment design, execution, and results are reported. In addition, the main functionalities of a prototype tool that has been created for the automatic computation of the metrics are briefly presented.
Abstract Until now, the quality problems of quantum software have been largely ignored. This chapter analyzes the applicability of models and metrics for quantum software and, to mitigate this lack of attention to quality issues, presents a set of metrics that have been proposed and empirically validated to characterize the complexity of quantum circuits in terms of their understandability. The validation experiment design, execution, and results are reported. In addition, the main functionalities of a prototype tool that has been created for the automatic computation of the metrics are briefly presented.
Quantum computing is the basis of a new revolution. Several quantum computers are already available and, with them, quantum programming languages, quantum software development kits and platforms, quantum error correction and optimization tools are proposed and presented continuously. In connection with this, disciplines such as the Quantum Software Engineering are appearing for applying the knowledge acquired through time in their corresponding classical relatives. Besides, measurement is well known as a key factor for assessing, and improving if needed, the quality of any model in terms of, for instance, its understandability. The easier to understand a model is, the easier to maintain, reuse, etc. In this work, we present the definition of a set of metrics for assessing the understandability of quantum circuits. Some examples of the calculation of the metrics are also presented. This is just the beginning of a more thorough process in which they will be empirically validated by the performance of empirical studies, especially experiments.
Quantum software is often described using circuit-level metrics, including the number of qubits, the number of gates, circuit depth, the number of two-qubit gates, and the number of measurement operations. These metrics are useful for estimating program size and execution cost, but they do not directly describe whether and to what extent qubits become structurally related through possible entanglement during program execution. This paper argues that entanglement dependence provides a basis for measuring a quantum-specific form of software complexity. The proposed metrics capture possible entanglement-related structural dependence, not physical entanglement observed in a particular execution. Based on this notion, we define a focused set of six metrics that characterize the amount, density, local connectivity, global scope, program span, and modular crossing of entanglement-related dependencies. We also analyze these metrics using Weyuker’s properties for evaluating software complexity measures. The paper presents the metrics as a measurement framework and research direction for empirical quantum software engineering. It discusses how future studies can validate the metrics and examine their usefulness for testing, debugging, maintenance, and program comprehension of quantum software.
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.
As quantum computing evolves, the demand for high-quality quantum software is increasing. Classical software quality models, such as McCall's model, provide a useful foundation, but they do not explicitly capture distinctive properties of quantum software, including probabilistic measurement outcomes, backend-dependent behavior, and hybrid quantum-classical workflows. This paper proposes a base quality model for quantum software using McCall's factor-criterion-metric structure as the organizing backbone. It broadens the set of quality factors by drawing on representative classical software quality models and standards and introduces quantum-specific extensions only where needed. We define the resulting factor set and quality criteria, provide a many-to-many mapping of core factor-to-criterion relationships, discuss representative candidate metrics together with the execution, reference, and interpretation conditions needed to use them, and illustrate how the resulting model can be applied across the quantum software lifecycle. The model is intended as a common starting point for structuring, assessing, and communicating quality concerns in quantum software while supporting context-specific adaptation. Further expert feedback, case studies, and empirical studies can be used to evaluate and refine the model and its application across different quantum software contexts.
Given the rapid evolution that has taken place in recent years in the software industry, and along with it the emergence of quantum software, there is a need to design an environment for measuring quality metrics for hybrid, classic-quantum software. In order to measure and evaluate the quality of classic software, there are models and standards, among which ISO/IEC 25000 stands out, which proposes a set of quality characteristics such as maintainability. However, there is currently no consensus for the measurement and evaluation of quantum software quality. In this paper we propose a series of adaptations to “classic” metrics, as well as a set of new measurements for hybrid maintainability. Finally, a first prototype of a measurement tool developed as a SonarQube plugin, capable of measuring these metrics in quantum developments, is also presented.
Quantum computing is the latest revolution in computing and will probably come to be seen as an advance as important as the steam engine or the information society. In the last few decades, our understanding of quantum computers has expanded and multiple efforts have been made to create languages, libraries, tools, and environments to facilitate their programming. Nonetheless, quantum computers are complex systems at the bottom of a stack of layers that programmers need to understand. Hence, efforts towards creating quantum programming languages and computing environments that can abstract low-level technology details have become crucial steps to achieve a useful quantum computing technology. However, most of these environments still lack many of the features that would be desirable, such as those outlined in The Talavera Manifesto for Quantum Software Engineering and Programming. For advancing quantum computing, we will need to develop quantum software engineering techniques and tools to ensure the feasibility of this new type of quantum software. To contribute to this goal, this paper provides a review of the main quantum software components and platforms. We also propose a set of quality requirements for the development of quantum software platforms and the conduct of their quality assessment.