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Springer eBooks

Quantum Software Modernization

Luis Jiménez-Navajas, Ricardo Pérez‐Castillo, Mario G. Piattini

Published Jan 1, 2022• 1 citation
Publisher
DOI
10.1007/978-3-031-05324-5_11

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Abstract Quantum computing is getting closer and closer to bringing all its potential applications to our lives. This means that in a few years the current IT will evolve into hybrid software systems where quantum and classical computing paradigms should be designed, developed, and operated together. This is a big challenge that will require software modernization processes for transforming and migrating legacy software systems (which may include adding new existing quantum software) toward such hybrid software systems. This chapter discusses the challenges of hybrid software and how software modernization (based on architecture-driven modernization) can be used as a reengineering solution for an effective evolution of classical and quantum software.

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Quantum computing has gained a lot of interest in recent years, thanks to its ability to solve certain problems that classical computing cannot address. These applications will only be achieved through the development of quantum software. Thus, many organizations are starting projects to integrate this new software into their existing systems. Software modernization (as based on Model-Driven Engineering) can be used to migrate from/to the so-called hybrid software systems, which integrate classical and quantum software. In that process, reverse engineering and restructuring phases have already been addressed, but the forward engineering phase for hybrid software has not yet been addressed. This paper presents a preliminary code generation technique from extended UML design models. It proposes an EGL transformation to generate Python and Qiskit code by integrating classical and quantum code. The transformation has been preliminarily validated with an example of application with the design model of a hybrid system for a financial web application. The implication of this work is that the software modernization process for hybrid software systems is completed, which facilitates the adoption of this new paradigm in the industry.

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Code generation for classical-quantum software systems modeled in UML

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Abstract Quantum computing is gaining an increasing interest since it can solve certain problems exponentially faster than classical computing. Thus, many organizations are researching and launching investments for integrating quantum software into their existing systems. Software modernization (as based on Model-Driven Engineering) has been proposed to migrate from/to the so-called hybrid software systems, which integrate classical and quantum software. In that process, both, reverse engineering and restructuring phases, have already been investigated. However, forward engineering phase for generating hybrid source code from high-level design models has not yet been addressed. Thus, this research proposes a quantum code generation technique from extended UML design models. It consists of a set of Model-to-Text transformations (defined through Epsilon Generation Language) to generate both Python and Qiskit code, which, respectively, integrate classical and quantum code. The transformation has been validated through a multi-case study with 7 hybrid software systems modeled in UML, which demonstrated that the transformation is effective and efficient. The implication of this work is that the software modernization process for hybrid software systems can be completed by tackling forward engineering phase, and that Model-Driven Engineering can therefore globally facilitate industry adoption of quantum software.

Software & Systems Modeling•Jan 16, 2025•4 citations
Abstract Quantum computing is getting closer and closer to bringing all its potential applications to our lives. This means that in a few years the current IT will evolve into hybrid software systems where quantum and classical computing paradigms should be designed, developed, and operated together. This is a big challenge that will require software modernization processes for transforming and migrating legacy software systems (which may include adding new existing quantum software) toward such hybrid software systems. This chapter discusses the challenges of hybrid software and how software modernization (based on architecture-driven modernization) can be used as a reengineering solution for an effective evolution of classical and quantum software.
Quantum computing has gained a lot of interest in recent years, thanks to its ability to solve certain problems that classical computing cannot address. These applications will only be achieved through the development of quantum software. Thus, many organizations are starting projects to integrate this new software into their existing systems. Software modernization (as based on Model-Driven Engineering) can be used to migrate from/to the so-called hybrid software systems, which integrate classical and quantum software. In that process, reverse engineering and restructuring phases have already been addressed, but the forward engineering phase for hybrid software has not yet been addressed. This paper presents a preliminary code generation technique from extended UML design models. It proposes an EGL transformation to generate Python and Qiskit code by integrating classical and quantum code. The transformation has been preliminarily validated with an example of application with the design model of a hybrid system for a financial web application. The implication of this work is that the software modernization process for hybrid software systems is completed, which facilitates the adoption of this new paradigm in the industry.
Abstract Quantum computing is gaining an increasing interest since it can solve certain problems exponentially faster than classical computing. Thus, many organizations are researching and launching investments for integrating quantum software into their existing systems. Software modernization (as based on Model-Driven Engineering) has been proposed to migrate from/to the so-called hybrid software systems, which integrate classical and quantum software. In that process, both, reverse engineering and restructuring phases, have already been investigated. However, forward engineering phase for generating hybrid source code from high-level design models has not yet been addressed. Thus, this research proposes a quantum code generation technique from extended UML design models. It consists of a set of Model-to-Text transformations (defined through Epsilon Generation Language) to generate both Python and Qiskit code, which, respectively, integrate classical and quantum code. The transformation has been validated through a multi-case study with 7 hybrid software systems modeled in UML, which demonstrated that the transformation is effective and efficient. The implication of this work is that the software modernization process for hybrid software systems can be completed by tackling forward engineering phase, and that Model-Driven Engineering can therefore globally facilitate industry adoption of quantum software.