This paper presents a tool that simplifies quantum software development by unifying circuit design, code generation, and execution within a single cross-platform environment that supports iterative development. Implemented as open source, the DEQSE Quantum IDE Extension has been developed to provide quantum functionalities within the Visual Studio Code environment, including project creator, code runner, code converter, and embedded quantum circuit simulator. Furthermore, the system provides capabilities that facilitate iterative development and support learning, distinguishing it from other available Visual Studio Code Extensions for quantum computing.
This paper presents a tool that simplifies quantum software development by unifying circuit design, code generation, and execution within a single cross-platform environment that supports iterative development. Implemented as open source, the DEQSE Quantum IDE Extension has been developed to provide quantum functionalities within the Visual Studio Code environment, including project creator, code runner, code converter, and embedded quantum circuit simulator. Furthermore, the system provides capabilities that facilitate iterative development and support learning, distinguishing it from other available Visual Studio Code Extensions for quantum computing.
The rapid growth of quantum computing calls for more accessible, interoperable, and collaborative development environments. While current quantum providers allow remote execution of quantum circuits, developers still face significant challenges due to fragmented programming models, lack of standardization, and limited support for collaboration. In response to these issues, this work introduces a web-based tool that integrates three key capabilities: visual circuit design, realtime collaborative editing, and deployment of quantum circuits as services. This feature enables multiple developers to codesign quantum circuits synchronously, in the spirit of cloudbased collaborative tools. This functionality facilitates teamwork, education, and reproducibility in quantum software engineering by allowing users to edit, share, and review quantum circuits simultaneously. In addition to collaborative editing, the tool also allows developers to automatically translate circuits into code compatible with both Qiskit and Amazon Braket, execute them on real quantum back-ends, and visualize execution results.
Abstract Quantum computing proposes a revolutionary paradigm that can radically transform numerous scientific and industrial application domains. To realize this promise, these new capabilities need software solutions that are able to effectively harness its power. However, developers may face significant challenges when developing and executing quantum software due to the limited availability of quantum computer hardware, high computational demands of simulating quantum computers on classical systems, and complicated technology stack to enable currently available accelerators into development environments. These limitations make it difficult for the developer to create an efficient workflow for quantum software development. In this paper, we investigate the potential of using remote computational capabilities in an efficient manner to improve the workflow of quantum software developers, by lowering the barrier of moving between local execution and computationally more efficient remote hardware and offering speedup in execution with simulator surroundings. The goal is to allow the development of more complex circuits and to support an iterative software development approach. In our experiment, with the solution presented in this paper, we have obtained up to 5 times faster circuit execution runtime, and enabled qubit ranges from 21 to 29 qubits with a simple plug-and-play kernel for the Jupyter notebook.
Quantum Software Engineering (QSE) is emerging as a critical discipline to make quantum computing accessible to a broader developer community; however, most quantum development environments still require developers to engage with low-level details across the software stack—including problem encoding, circuit construction, algorithm configuration, hardware selection, and result interpretation—making them difficult for classical software engineers to use. To bridge this gap, we present C2 ∣Q⟩ , a hardware-agnostic quantum software development framework that translates specific types of classical specifications into quantum-executable programs while preserving methodological rigor. The framework applies modular software engineering principles by classifying the workflow into three core modules: an encoder that classifies problems, produces Quantum-Compatible Formats (QCFs), and constructs quantum circuits, a deployment module that generates circuits and recommends hardware based on fidelity, runtime, and cost, and a decoder that interprets quantum outputs into classical solutions. This architecture supports systematic evaluation across simulators and Noisy Intermediate-Scale Quantum (NISQ) quantum devices, remaining scalable to new problem classes and algorithms. In evaluation, the encoder module achieved a 93.8% completion rate, the hardware recommendation module consistently selected the appropriate quantum devices for workloads scaling up to 56 qubits. End-to-end experiments on 434 Python programs and 100 JSON problem instances demonstrate that the full C2 ∣Q⟩ workflow executes reliably on simulators and can be deployed successfully on representative real quantum hardware, with empirical runs limited to small- and medium-sized instances consistent with current NISQ capabilities. A proxy-based usability analysis further indicates substantial reductions in handwritten lines of code and explicit configuration steps compared to conventional quantum SDK workflows. These results indicate that C2 ∣Q⟩ lowers the entry barrier to quantum software development by providing a reproducible, extensible toolchain that connects classical specifications to quantum execution. The open-source implementation of C2 ∣Q⟩ is available at https://github.com/C2-Q/C2Q and as a ready-to-use Python package at https://pypi.org/project/c2q-framework/ .
This paper introduces a vision for Quantum Software Development lifecycle, proposing a hybrid full-stack iterative model that integrates quantum and classical computing. Addressing the current challenges in Quantum Computing (QC) such as the need for integrating diverse programming languages and managing the complexities of quantum-classical systems, this model is rooted in the principles of DevOps and continuous software engineering. It presents a comprehensive lifecycle for quantum software development, encompassing quantum-agnostic coding, testing, deployment, cloud computing services, orchestration, translation, execution, and interpretation phases. Each phase is designed to accommodate the unique demands of QC, enabling traditional software developers to engage with QC environments without needing in-depth QC expertise. The paper presents a detailed implementation roadmap, utilizing a range of existing tools and frameworks, thereby making quantum software development more accessible and efficient. The proposed model not only addresses current challenges in quantum software development but also makes a substantial contribution to the field of Quantum Software Engineering (QSE). By proposing a structured and accessible model, it sets the stage for further advancements and research in QSE, enhancing its practicality and relevance in a wide range of applications.
Quantum computing promises significant advancements over classical computing by enabling exponential speedups for specific problems. Despite its potential, quantum software development remains challenging due to its complexity, cost, and susceptibility to errors. Aligned with the novel paradigm of Quantum Software Engineering (QSE), this paper introduces a tool designed to automate the generation of quantum software components from truth tables. The tool simplifies the development process by allowing users to specify expected output values for given inputs, which the tool then translates into the corresponding quantum code. This approach reduces the manual effort required and helps ensure accuracy in quantum program development. Our method not only streamlines quantum software generation but also optimizes the resulting quantum circuits by minimizing unnecessary computations. The paper provides a detailed overview of the algorithm, tool implementation, and potential applications, highlighting the tool's efficacy in facilitating more efficient quantum software development.
Abstract Quantum computing has experienced a breakthrough. Several companies are taking up the challenge of designing and manufacturing quantum computers, and the supply of tools for quantum software development is growing all the time. This article addresses quantum software development toolkits and introduces the ‘QuantumPath’ platform. In developing QuantumPath, our aim is to fulfil certain principles such as: agnosticism, extensibility, integration, independency, optimisation, scalability, security, usability and software engineering support. This article presents both the architecture itself as well as the main tools that compose QuantumPath, in order to illustrate the support which platform provides to the development and execution of quantum software.