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Auflistung nach Schlagwort "domain modeling"

1 - 3 von 3
  • Konferenzbeitrag
    A Context Map as the Basis for a Microservice Architecture for the Connected Car Domain
    (INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft, 2019) Abeck, Sebastian; Schneider, Michael; Quirmbach, Jan-Philip; Klarl, Heiko; Urbaczek, Christof; Zogaj, Shkodran
    In the near future cars will have two properties: They will be electrically powered and they will be connected to the Internet. Such cars will provide a huge amount of sensor data which can be accessed via web APIs in order to develop innovative connected car applications, such as traffic control, hazard warning, assisted or even autonomous driving. However, current software solutions in this field are mainly monoliths solving single problems in an isolated way. Therefore, we propose a systematic approach by which each single connected car application becomes part of a microservice architecture. This approach requires a sound and well-elaborated domain model from which the microservices' APIs and implementation of the applications can be systematically derived. The main contribution of this paper is a context map for the connected car domain. We demonstrate a structured software development approach with the example of a mobile application, the Electric Car Charger, by showing how this application is integrated into the context map and, thus, into a connected car microservice architecture.
  • Konferenzbeitrag
    The QDAcity-RE Method for Structural Domain Modeling Using Qualitative Data Analysis
    (Software Engineering und Software Management 2018, 2018) Kaufmann, Andreas; Riehle, Dirk
    The creation of domain models from qualitative input relies heavily on experience. An uncodified ad-hoc modeling process is still common and leads to poor documentation of the analysis. In this article we present a new method for domain analysis based on qualitative data analysis (QDA). The method helps identify inconsistencies, ensures a high degree of completeness, and inherently provides traceability from analysis results back to stakeholder input. These traces do not have to be documented after the fact. We evaluate our approach using four exploratory studies.
  • Conference paper
    Term Extraction for Domain Modeling
    (Proceedings of DELFI 2024, 2024) Kruse, Theresa; Lohr, Dominic; Berges, Marc; Kohlhase, Michael; Moghbeli, Halimeh; Schütz, Marcel
    Adaptive learning systems need to use domain and learner models to provide meaningful support for learners. Building fine-grained domain models by hand is very time-consuming, so the demand for partial automation is high. This paper investigates how term extraction tools can support constructing a domain model. Therefore, we study if different automatic term extraction tools give comparable results to a human annotator. Our results show that the current extraction tools support the process, but their results are not directly usable and still need human adjustments.