Models@run.time: a Guided Tour of the State-of-the-Art and Research Challenges

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Abstract

More than a decade ago, the research topic models@run.time was coined. Since then, the research area has received increasing attention. Given the prolific results during these years, the current outcomes need to be sorted and classified. Furthermore, many gaps need to be categorized in order to further develop the research topic by experts of the research area but also newcomers. Accordingly, the paper discusses the principles and requirements of models@run.time and the state of the art of the research line. To make the discussion more concrete, a taxonomy is defined and used to compare the main approaches and research outcomes in the area during the last decade and including ancestor research initiatives. We identified and classified 275 papers on models@run.time, which allowed us to identify the underlying research gaps and to elaborate on the corresponding research challenges. Finally, we also facilitate sustainability of the survey over time by offering tool support to add, correct and visualize data.

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  • Models@run.time: a Guided Tour of the State-of-the-Art and Research Challenges

    Rights statement: © Springer-Verlag GmbH Germany, part of Springer Nature 2019

    Accepted author manuscript, 2 MB, PDF-document

    Embargo ends: 9/01/20

Details

Original languageEnglish
Number of pages34
JournalSoftware and Systems Modeling
Early online date9 Jan 2019
DOIs
Publication statusE-pub ahead of print - 9 Jan 2019

Bibliographic note

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

    Keywords

  • Causal connection, Models@run.time, Self-reflection, Systematic literature review

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