Some Narrow and Broad Challenges in MDD

Gogolla, Martin; Hilken, Frank; Kästner, Andreas

doi:10.1007/978-3-319-74730-9_15

Cited by 1 publication

(1 citation statement)

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“…A critical discussion on social challenges took up the argument that MDE should be the catalyst to enable non-technical people to build the tools they need in their domains (Modeling by the People, for the People [27]). While this is one of the main selling arguments for MDE, it is still tricky for some modeling aspects, like the definition of desired consistency properties [28]. Ideally, instead of starting from scratch, stakeholders could be assisted in exploring the design space of potential models to be built [29], where these potential models (and their relationships) should be informed by domain information, e.g., regulatory texts from which some initial models could be inferred.…”

Section: Social Aspectsmentioning

confidence: 99%

Grand challenges in model-driven engineering: an analysis of the state of the research

et al. 2020

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In 2017 and 2018, two events were held-in Marburg, Germany, and San Vigilio di Marebbe, Italy, respectively-focusing on an analysis of the state of research, state of practice, and state of the art in model-driven engineering (MDE). The events brought together experts from industry, academia, and the open-source community to assess what has changed in research in MDE over the last 10 years, what challenges remain, and what new challenges have arisen. This article reports on the results of those meetings, and presents a set of grand challenges that emerged from discussions and synthesis. These challenges could lead to research initiatives for the community going forward. Keywords Model-driven engineering • Grand challenge • Research roadmap 1 Introduction The field of model-driven engineering [1] (MDE) has evolved substantially from the earliest work on UML in the 1990s, through to seminal research on metamodeling, model transformation, and model management in the earlyto-mid-2000s. MDE has made incredible contributions to leverage abstraction and automation in almost every area of software and systems development and analysis. In many domains, including railway systems, automotive, business process engineering, and embedded systems, models are key to success in modern software engineering processes. How-Communicated by Bernhard Rumpe.

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Section: Social Aspectsmentioning

confidence: 99%