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Abstract-In practice, more and more software development projects are distributed, ranging from partly distributed teams to global projects with each stakeholder located differently. Teaching actual practice in software engineering at university needs a proper mixture of theory and practice. But setting up practical exercises for global software engineering is hard, because students have to cooperate across different locations and situations reflecting the teaching intentions have to be provoked explicitly.This paper presents the concepts behind our common teaching environment for global software engineering -the GloSELab. It describes the experiences on setting up a distributed course and reports our teaching intentions based on each universities main focus: project management, requirements engineering & quality assurance, architecture, and implementation. Furthermore, we discuss our setup -a stage-gate process, where each location takes care of a different phase -and report occurred problems and how they supported or interfered with our teaching intentions.

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A well-structured, modular software architecture is known to support comprehensibility, maintainability and extensibility of a software system. To achieve this goal the software system is divided into components in such a way that its component structure is optimized regarding cohesion and coupling. But with increasing size and complexity identifying and evaluating a component structure can be rarely accomplished by humans manually.To support this task, we developed an approach using Spectral Clustering from the field of neural computation. Based on the different dependencies between software elements, our approach automatically forms a component structure of the analyzed software system. In a case study we demonstrate this approach on a software system of manually manageable size and complexity. The results are compared to the component structure skilled software architects manually formed. In most cases both variants, manually as well as automated, provide similar component structures. For this reason, the presented approach seems to be suitable for systems which are not manageable by hand.

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