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Auflistung nach Schlagwort "Domain Specific Language"

1 - 2 von 2
  • Konferenzbeitrag
    Athos: An Extensible DSL for Model Driven Traffic and Transport Simulation
    (Modellierung 2020, 2020) Hoffmann, Benjamin; Urquhart, Neil; Chalmers, Kevin; Guckert, Michael
    Multi-agent systems may be considered appropriate tools for simulating complex systems such as those based around traffic and transportation networks. Modelling traffic participants as agents can reveal relevant patterns of traffic flow. Upsurging traffic in urban areas increases the relevance of such simulations and the insight they provide into reducing congestion and pollution. Developing multi-agent traffic simulations is a challenging task even for professional software developers. In contrast, domain experts need tools that can be quickly adapted to new questions emerging in their research without potentially error-prone communication with software developers. There is a need for simulation tools that are intuitive to domain experts yet flexible and adaptable by software developers as required. A model driven approach with an extensible domain specific language delivers an answer for both of these opposing requirements. The modeller is relieved from implementing time consuming programming details and can focus on the application itself. We present the domain specific language Athos that allows to create simulations of traffic and transport related problems declaratively. The models are platform independent and executable code can be generated for appropriate multi-agent platforms. The language is flexible and can be easily extended by exploiting the structure of the problem domain itself. In this paper, we present Athos and focus on how it can be extended by arbitrary traffic and routing algorithms through an annotation-based extension mechanism.
  • Konferenzbeitrag
    Towards Detecting Algorithm Implementations in Code Bases
    (Softwaretechnik-Trends Band 42, Heft 2, 2022) Neumüller, Denis; Tichy, Matthias
    Developing an understanding of a software system is an integral part of a software-reengineering effort. Even though many approaches for supporting the process of software understanding exist, to the best of our knowledge, none focuses on leveraging information from the algorithms implemented in a system. We believe that detecting well known algorithms in the code base can be helpful to gain knowledge about, which concerns are present in the code base, how they are solved and which components are involved. Our envisioned solution consists of a Domain Specific Language (DSL) designed to describe key features of an algorithm, a search algorithm to find these features and a set of “ready to use” descriptions for common algorithms.