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A Machine Learning Based Approach to Application Landscape Documentation

Abstract : In the era of digitalization, IT landscapes keep growing along with complexity and dependencies. This amplifies the need to determine the current elements of an IT landscape for the management and planning of IT landscapes as well as for failure analysis. The field of enterprise architecture documentation sought for more than a decade for solutions to minimize the manual effort to build enterprise architecture models or automation. We summarize the approaches presented in the last decade in a literature survey. Moreover, we present a novel, machine-learning based approach to detect and to identify applications in an IT landscape.
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Jörg Landthaler, Ömer Uludağ, Gloria Bondel, Ahmed Elnaggar, Saasha Nair, et al.. A Machine Learning Based Approach to Application Landscape Documentation. 11th IFIP Working Conference on The Practice of Enterprise Modeling (PoEM), Oct 2018, Vienna, Austria. pp.71-85, ⟨10.1007/978-3-030-02302-7_5⟩. ⟨hal-02156459⟩

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