Teaching software architecture is hard. The topic is abstract and is best understood by experiencing it, which requires proper scale to fully grasp its complexity. Furthermore, students need to practice both technical and social skills to become good software architects. To overcome these teaching challenges, we developed the Collaborative Software Architecture Course. In this course, participants work together to study and document a large, open source software system of their own choice. In the process, all communication is transparent in order to foster an open learning environment, and the end-result is published as an online book to benefit the larger open source community.
We have taught this course during the past four years to classes of 50-100 students each. Our experience suggests that: (1) open source systems can be successfully used to let students gain experience with key software architecture concepts, (2) students are capable of making code contributions to the open source projects, (3) integrators (architects) from open source systems are willing to interact with students about their contributions, (4) working together on a joint book helps teams to look beyond their own work, and study the architectural descriptions produced by the other teams.@en

In the past two decades both the industry and the research community have proposed hundreds of metrics to track software projects, evaluate quality or estimate effort. Unfortunately, it is not always clear which metric works best in a particular context. Even worse, for some metrics there is little evidence whether the metric measures the attribute it was designed to measure. In this paper we propose a catalog format for software metrics as a first step towards a consolidated overview of available software metrics. This format is designed to provide an overview of the status of a metric in a glance, while providing enough information to make an informed decision about the use of the metric. We envision this format to be implemented in a (semantic) wiki to ensure that relationships between metrics can be followed with ease.

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