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Models@run.time: a guided tour of the state of the art and research challenges

机译:Models@run.time:关于最新技术和研究挑战的导览

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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.
机译:十多年前,创造了研究主题“ models@run.time”。从那以后,研究领域受到越来越多的关注。考虑到这些年来的丰硕成果,需要对当前成果进行分类。此外,为了进一步发展研究领域的专家和新来者的研究主题,需要对许多差距进行分类。因此,本文讨论了@ run.time模型的原理和要求以及研究线的最新水平。为了使讨论更加具体,定义了分类法并将其用于比较过去十年中该地区的主要方法和研究成果,包括祖先的研究计划。我们在models@run.time上对275篇论文进行了识别和分类,这使我们能够发现潜在的研究差距并详细阐述相应的研究挑战。最后,我们还通过提供工具支持来添加,更正和可视化数据,从而促进调查的可持续发展。

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