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.
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 software engineering (QSE) requires understanding application requirements, quantum programs and algorithms, quantum computation paradigms, executions, and deployment. However, relevant quantum computing (QC) concepts are often defined across physical, mathematical, and paradigm-specific levels of abstraction, making it difficult for the QSE community and hence proposed methods to refer to them consistently. To this end, we present QSoftCore, a conceptual model that reorganizes established QC concepts from a software engineering perspective and connects quantum applications, computational problems, algorithms, configurations, programs, and paradigm-specific computation specifications with state evolution, execution results, and backends. Our assessment against QSE literature across key software engineering activities indicates that QSoftCore provides shared QC referents for quantum computations, executions, deployment configurations, backends, and measurement evidence across the QSE lifecycle.
Quantum software plays a critical role in exploiting the full potential of quantum computing systems. As a result, it is drawing increasing attention recently. As research in quantum programming reaches maturity with a number of active research and practical products, software metric researchers need to focus on this new paradigm to evaluate it rigorously and quantitatively. As the first step, this paper proposes some basic metrics for quantum software, which mainly focus on measuring the size and structure of quantum software. These metrics are defined at different abstraction levels to represent various size and structure attributes in quantum software explicitly. The proposed metrics can be used to evaluate quantum software from various viewpoints.
In the context of quantum-classical hybrid computing, evaluating analysability, which is the ease of understanding and modifying software, presents significant challenges due to the complexity and novelty of quantum algorithms. Although advances have been made in quantum software development, standard software quality evaluation methods do not fully address the specifics of quantum components, resulting in a gap in the ability to ensure and maintain the quality of hybrid software products. In this registered report proposal, we intend to validate a quality model focused on the analysability of hybrid software through an international collab orative approach involving academic institutions from Italy and Spain through a controlled experiment. This approach allows for a more detailed analysis and validation methodology and establishes a framework for future research and developments in software quality assessment in quantum computing.
This doctoral dissertation, presented in the form of a compendium of publications, focuses on the design, implementation, and validation of an innovative model for evaluating analyz- ability—understood as a key subcharacteristic of maintainability—in the context of quantum software and, more broadly, hybrid software systems (those integrating classical and quantum components). In a landscape where quantum computing is rapidly advancing and beginning to consolidate in industrial applications, a pressing need arises to adapt and extend traditional software quality models, such as those established in the ISO/IEC 25000 family, to address the specific characteristics of quantum code. The lack of dedicated metrics hinders the rigorous evaluation of critical attributes like analyzability, negatively affecting hybrid systems’ maintainability, evolvability, and reliability in highly complex technical environments. The main objective of this dissertation is the design, implementation, and validation of an evaluation model focused on analyzability, which combines adapted classical metrics with newly defined indicators tailored explicitly for the quantum component. While the model targets hybrid systems, the validation has been exclusively focused on the quantum component, which constitutes the core contribution of this research. The classical part relies on well-established metrics validated and certified by bodies such as ILAC and ENAC and has therefore not been experimentally evaluated in this work. Additionally, an automated technological environment has been developed as a key element of the compendium, facilitating the practical application of the model in real-world projects. This environment enables integrated and real-time measurement of both classical and quantum metrics. However, like the model, its validation has been limited to the novel quantum indicators defined in this thesis. This approach strengthens the proposed methodology and lays the groundwork for future validation of the fully integrated hybrid model. The adopted methodology is grounded in an exhaustive review of the state of the art, the formal and informal definition of metrics, the development of the automated environment, and empirical validation through a family of experiments. The compendium of publications includes, among others, the following articles: Towards a set of metrics for hybrid (quan- tum/classical) systems maintainability, Implementing an environment for hybrid software evaluation, and Environment for the Evaluation of Hybrid (Classical-Quantum) Systems Analyzability. As part of the validation process, a preliminary study has been accepted at the international conference IQSOFT 2025, and an extended version has been submitted to the journal Empirical Software Engineering (EmSE), and is currently under review. The results demonstrate that the proposed model enables precise quantification of quantum software analyzability and that its application in hybrid systems is feasible conceptually and technically. The developed technological environment supports reproducible and systematic evaluation, laying a foundation for future applications in hybrid software engineering. The em- pirical validation conducted thus far has been deliberately limited to the quantum component, given that classical metrics are already widely established and certified. In conclusion, this dissertation represents a significant advance in the evaluation of hybrid software quality. It proposes a validated model that contributes to strengthening maintain- ability and supporting the evolution of complex systems in an ever-changing technological landscape.
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.