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Quantum computing is a relatively new paradigm that has raised considerable interest in physics and computer science in general but has so far received little attention in software engineering and architecture. Hybrid applications that consist of both quantum and classical components require the development of appropriate quantum software architectures. However, given that quantum software engineering (QSE) in general is a new research area, quantum software architecture–a subresearch area in QSE is also understudied. The goal of this chapter is to provide a list of research challenges and opportunities for such architectures. In addition, to make the content understandable to a broader computer science audience, we provide a brief overview of quantum computing and explain the essential technical foundations.
Software development projects leave a large amount of data in repositories of Application Lifecycle Management (ALM) tools. These data contain detailed histories of their respective projects, their results and decisions made along the way. Analysis of such data helps uncover various interesting facts about projects, e.g. their socio-technical structures and the actual (vs. purported) roles of team members. Based on experiences with tools supporting our research we are convinced that it is feasible to consolidate data from different ALM tools, tapping into the situation common in real-life projects. In this paper we report on our work towards a shared common data model and tool integration aimed at improved project analysis. We discuss how this can help in the identification of architects in the project organizational structures, their activity patterns and collaboration with other team roles.