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Auflistung nach Autor:in "Gilani, Wasif"

1 - 3 von 3
  • Konferenzbeitrag
    Dynamic aspect weaver family for family-based adaptable systems
    (NODe 2005 – GSEM 2005, 2005) Gilani, Wasif; Spinczyk, Olaf
  • Konferenzbeitrag
    Model transformation chains in model-driven performance engineering: experiences and future research needs
    (Modellierung 2010, 2010) Fritzsche, Mathias; Gilani, Wasif; Lämmel, Ralf; Jouault, Frédéric
    We gained experiences in implementing rule based model transformations within an industrial case study called Model-Driven Performance Engineering (MDPE). Similar to other MDE scenarios, these transformations have been implemented via multiple transformation steps interconnected in an automated model transformation chain. In this short paper, we use the MDPE case study to demonstrate reasons for decomposing model transformations and discuss disadvantages in terms of execution costs. Based on these experiences, we propose, as an input for future research, an architecture to optimize decomposed model transformation chains.
  • Konferenzbeitrag
    A scalable approach to annotate arbitrary modelling languages
    (Modellierung 2010, 2010) Fritzsche, Mathias; Gilani, Wasif; Thiele, Michael; Spence, Ivor; Brown, T. John; Kilpatrick, Peter
    Refinement via annotations is a common practice in Model-Driven Engineering (MDE). For instance, in the case of our Model-Driven Performance Engineering (MDPE) architecture, we are required to annotate different types of process models with performance objectives, constraints and other information. This is used to enable domain experts, such as business analysts, to benefit from an automated performance prediction based decision support. Currently, the process models are annotated manually, element by element. This approach is not scalable, for instance, in the case where numerous model elements in large model repositories need to be annotated with the same information. Thus, a scalable annotation mechanism is needed which can be used for arbitrary modelling languages. In this paper we propose an architecture which uses a specialized modelling language to express annotations in an efficient way. This language is transformed to model transformation scripts in order to generate annotation models, which separate the annotated information from the target models and, therefore, supports scalable model annotations for modelling languages of choice.