Game System Reimagination (GSR) is an instructional approach designed to make commercial games viable in games engineering education, despite their complexity. GSR addresses the challenge of staying relevant in a rapidly advancing field with students who are often avid gamers. Modern games comprise a wide range of systems, from common ones like movement, combat, and inventory management to unique, game-specific variants. By engaging students with these systems, GSR aims to enhance their motivation, technical skills, and understanding of complex games while bridging the gap between academic learning and real-world game development. Grounded in constructivist learning theory, GSR leads students through hands-on projects, where they play commercial games, identify systems to investigate, and deconstruct them to understand the underlying mechanics and challenges. Instead of merely replicating game systems, students reimagine them by removing, adding, combining, or altering functionality. Using a predefined technical framework with a modern game engine, they develop prototypes that showcase their understanding and ability to create complex systems. GSR supports a wide range of student abilities and has been applied to numerous undergraduate projects and bachelor's theses, primarily using the Unity game engine. We validated its educational impact through a survey assessing technical skills, practical relevance, creative engagement, motivation, and selfconfidence. The results confirm that GSR fosters key competencies, with participants acknowledging its technical and practical benefits for games engineering.

The increased use and interconnection of electronic components in automobiles has made communication behavior in automotive networks drastically more complex. Both communication designs at application level and complex communication scenarios are often under-specified or out of scope of existing analysis techniques. We extend traditional protocol analyzers in order to capture communication at the level of abstraction that reflects application design and show that the same technique can be used to specify, monitor and test complex scenarios. We present CFR (Channel Filter Rule) models, a novel approach for the specification of analyzers and a domain-specific language that implements this approach. From CFR models, we can fully generate powerful analyzers that extract design intentions, abstract protocol layers and even complex scenarios from low level communication data. We show that three basic concepts (channels, filters and rules) are sufficient to build such powerful analyzers and identify possible areas of application.