Agile methodology for software development and IT projects has developed into more complex, hybrid project management frameworks – notably the Scaled Agile Framework (SAFe). This allows the agile management of complex IT portfolios or development programmes which require methodology which goes beyond the single-project-single-team scope of e.g. the basic Scrum approach. The SAFe methodology claims to be the right approach for lean enterprises. But this still assumes that it is implemented in a single organization with stable organizational setups and team structures and with professional staff. In contrast, we apply SAFe in a typical distributed and loose environment of an Open Source development project. Instead of a dedicated team, the involved staff is organized in an informal, open community of practice (OpenCoP) where participants join and leave and where staff contributes only certain amounts of time with a limited commitment. In addition, we deal with a university led IT programme which involves students as developers with limited experience and competence in professional project work. This paper presents the case study of the development of a Digital Education Ecosystem (DEE) for a Virtual Master School. The members of this Master School (including the students) are the co-developers and the users of the DEE. They form an OpenCoP which develops a customized IT system for their own needs. Applying SAFe in such an environment is new and challenging. This paper describes first experiences in this field.

Currently, practitioners follow a top-down approach in automotive development projects. However, recent studies have shown that this top-down approach is not suitable for the implementation and testing of modern automotive systems. Specifically, practitioners increasingly fail to specify requirements and tests for systems with complex component interactions (e.g., e-mobility systems). In this paper, we address this research gap and propose an integrated and iterative scenario-based technique for the specification of requirements and test scenarios. Our idea is to combine both a top-down and a bottom-up integration strategy. For the top-down approach, we use a behavior-driven development (BDD) technique to drive the modeling of high-level system interactions from the user's perspective. For the bottom-up approach, we discovered that natural language processing (NLP) techniques are suited to make textual specifications of existing components accessible to our technique. To integrate both directions, we support the joint execution and automated analysis of system-level interactions and component-level behavior. We demonstrate the feasibility of our approach by conducting a case study at Kostal (Tierl supplier). The case study corroborates, among other things, that our approach supports practitioners in improving requirements and test specifications for integrated system behavior.

For the development and maintenance of distributed systems, it is useful to analyze the system condition and utilization for each hardware component. With pulseAT, a tool has been developed which collects that system utilization systematically with lightweight pulseAT Agents. The hierarchical structure of pulseAT allows having all system utilization data at one place on a pulseAT Manager to show an overall current health condition of the system. A cloud-based pulseAT Analyzer stores the data into a time-based database to support long-term analyses and to process analyzing algorithms, e.g., to forecast future health conditions. This paper describes the structure of pulseAT, main concepts, e.g., how the response time for each component is calculated. Some technical details of the implementation are shown. Finally, it describes how pulseAT has been tested on a mobile robot, the DAEbot.