🤖 AI Summary
This study addresses the lack of effective metrics for analyzability in quantum-classical hybrid software, a key barrier to its maintainability and industrial adoption. Building upon the ISO/IEC 25010 standard, the authors propose a novel analyzability model for quantum software and empirically validate its ability to differentiate analyzability across diverse quantum algorithms through four controlled experiments involving multiple scenarios and participant groups. Complementing these experiments with user surveys on perceived complexity, the study demonstrates a strong alignment between the model’s outputs and human subjective judgments. The findings indicate that the proposed model not only provides an effective means to quantify analyzability in quantum software but also establishes a meaningful correspondence between objective measurement and human cognition, thereby offering a reliable tool for quantum software quality assessment.
📝 Abstract
The analyzability of hybrid software, which integrates both classical and quantum components, is a key factor in ensuring its maintainability and industrial adoption. This article presents the empirical validation, through a family of experiments, of the quantum component of a previously proposed hybrid software analyzability model based on the ISO/IEC 25010 standard. The experimental series consists of four studies involving participants with diverse profiles in both academic and professional settings. In these experiments, the model’s ability to effectively measure the analyzability of quantum algorithms is assessed, and the relationship between the analyzability levels computed by the model and the participant’s perceptions of the complexity of these algorithms is examined. The results indicate that the proposed model effectively distinguishes between quantum software components with varying levels of analyzability and aligns with human perception, reinforcing its validity in quantum computing.