Quantum computing is rapidly progressing from theoretical promise to practical implementation, offering significant computational advantages for tasks in optimization, simulation, cryptography, and machine learning. However, its integration into real-world software systems remains constrained by hardware fragility, platform heterogeneity, and the absence of robust software engineering practices. This article introduces Service-Oriented Quantum (SOQ), a novel paradigm that reimagines quantum software systems through the lens of classical service-oriented computing. Unlike prior approaches such as Quantum Service-Oriented Computing (QSOC), which treat quantum capabilities as auxiliary components within classical systems, SOQ positions quantum services as autonomous, composable, and interoperable entities. We define the foundational principles of SOQ, propose a layered technology stack to support its realization, a reference architecture for defining quantum services based on the good implementation of a classical service, and identify the key research and engineering challenges that must be addressed, including interoperability, hybridity, pricing models, service abstractions, and workforce development.
Publicaciones
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Jose Garcia-Alonso, Enrique Moguel, Jaime Alvarado-Valiente, …, , et al. . Rethinking Services in the Quantum Age: The SOQ Paradigm. ACM Transactions on Software Engineering and Methodology (TOSEM), vol. 35 revista
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Juan M. Murillo, Ignacio García Rodríguez de Guzmán, Enrique Moguel, …, , et al. . QuantumX: an experience for the consolidation of Quantum Computing and Quantum Software Engineering as an emerging discipline. arXiv preprint arXiv:2603.10621 preprint
Juan M. Murillo, Ignacio García Rodríguez de Guzmán, Enrique Moguel, Javier Romero-Álvarez, Jaime Alvarado-Valiente, Álvaro M. Aparicio-Morales, Jose Garcia-Alonso, Ana Díaz Muñoz, Eduardo Fernández-Medina, Francisco Chicano, Carlos Canal, José Daniel Viqueira, Sebastián Villarroya, Eduardo Gutiérrez, , Alfonso E. Márquez-Chamorro, Antonio Ruiz-Cortés, Cyrille YetuYetu Kesiku, Pedro Sánchez, Diego Alonso Cáceres, Lidia Sánchez-González, Fernando Plou
A report on the first QuantumX track, held at JISBD 2025, which brought together Spanish research groups exploring how principles of software quality, governance, testing, orchestration, and abstraction can be adapted to the quantum paradigm. Contributions covered quantum service engineering, hybrid architectures, quality models, circuit optimization, and quantum machine learning; the article synthesizes common themes and outlines future directions for Quantum Software Engineering.
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Alfonso E. Márquez-Chamorro, , Manuel Resinas, Antonio Ruiz-Cortés . Causally-Informed Predictive Process Monitoring. Service-Oriented Computing – ICSOC 2024 Workshops, LNCS 15833, pp. 96–108 workshop
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, Alfonso E. Márquez-Chamorro, Cristina Cabanillas . A Mashup-Based Approach for Predictive Compliance Monitoring. Selected Papers of HybridAIMS and CAI Workshops, co-located with CAiSE 2025, CEUR-WS vol. 3996 workshop
Predictive Compliance Monitoring (PCM) is an emerging field that integrates predictive techniques with compliance monitoring to ensure business processes adhere to regulatory and organizational standards. Existing research in this area has been limited, as current approaches mainly focus on monitoring Service Level Agreements (SLAs) or restrict predictions to remaining execution time. This paper introduces a framework for PCM that utilizes multiple predictive process monitoring (PPM) models on compliance mashups. The framework forecasts key process indicators, including next event predictions, remaining execution time, and process outcomes, while simultaneously evaluating compliance with predefined rules. This approach advances automated compliance monitoring and highlights key challenges and future research opportunities in the PCM field.
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. QuBind: A Multi-Metric Approach for Optimal and Dynamic QPU Selection. Master's thesis, MSc in Software Engineering: Cloud, Data and IT Management, Universidad de Sevilla tesis
A multi-metric framework for selecting quantum processing units (QPUs), built on a matcher and optimizer pattern, that picks the best available backend for a quantum workload dynamically.