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Lauri Malmi

Publications and source records attributed to Lauri Malmi.

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C2|Q>: A Robust Framework for Bridging Classical and Quantum Software Development -- RCR Report

This is the Replicated Computational Results (RCR) Report for the paper C2|Q>: A Robust Framework for Bridging Classical and Quantum Software Development. The paper introduces a modular, hardware-agnostic framework that translates classical problem specifications-Python code or structured JSON-into executable quantum programs across ten problem families and multiple hardware backends. We release the framework source code on GitHub at https://github.com/C2-Q/C2Q, a pretrained parser model on Zenodo at https://zenodo.org/records/19061125, evaluation data in a separate Zenodo record at https://zenodo.org/records/17071667, and a PyPI package at https://pypi.org/project/c2q-framework/ for lightweight CLI and API use. Experiment 1 is supported through a released pretrained model and training notebook, while Experiments 2 and 3 are directly executable via documented make targets. This report describes the artifact structure, setup instructions, and the mapping from each execution route to the corresponding experiment.

cs.SE

C2|Q>: A Robust Framework for Bridging Classical and Quantum Software Development

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 SE principles by classifying the workflow into three core modules: an encoder that classifies problems, produces Quantum-Compatible Formats, 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. 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 show 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. 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 Python package at https://pypi.org/project/c2q-framework/.

cs.SE

Computing-specific pedagogies and theoretical models: common uses and relationships

Computing education widely applies general learning theories and pedagogical practices. However, computing also includes specific disciplinary knowledge and skills, e.g., programming and software development methods, for which there has been a long history of development and application of specific pedagogical practices. In recent years, there has also been substantial interest in developing computing-specific theoretical models, which seek to describe and explain the complex interactions within teaching and learning computing in various contexts. In this paper, we explore connections between computing-specific pedagogies and theoretical models as reported in the literature. Our goal is to enrich computing education research and practice by illustrating how explicit use of field-specific theories and pedagogies can further the whole field. We have collected a list of computing-specific pedagogical practices and theoretical models from a literature search, identifying source papers where they have been first introduced or well described. We then searched for papers in the ACM digital library that cite source papers from each list, and analyzed the type of interaction between the model and pedagogy in each paper. We developed a categorization of how theoretical models and pedagogies have supported or discounted each other, have been used together in empirical studies or used to build new artefacts. Our results showed that pair programming and parsons problems have had the most interactions with theoretical models in the explored papers, and we present findings of the analysis of these interactions.

cs.CY