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

Abstract

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.

Positioning of the low-code movement within the field of model-driven engineering

“…It is more a synonym (or a subset) of the techniques we are already working on. In fact, we could take almost any of the open challenges in model-driven engineering [1] and just change "model-driven" by "low-code" to get, for free, a research roadmap for low-code development (e.g. we need better ways to integrate AI in low-code tools or we should strive as a community to build a shared repository of low-code examples for future research).…”

“…Low-code application platforms accelerate app delivery by dramatically reducing the amount of hand-coding required 1 This is clearly not the first time the software engineering community attempts to reduce manual coding by combining visual development techniques (what we would call "models") and code generation. In fact, as Grady Booch says, the entire history of software engineering is about raising the level of abstraction.…”

Papyrus for gamers, let's play modeling

“…A Level refers to one Game associated to a SourceDiagram from the SourceModel and linked to LevelRules defined in GDF. Teacher can define custom series of exercises by defining one or several levels following this approach: (i) choose a game among the available games in the system, (ii) create a source diagram in Papyrus according to the game requirements about source diagrams, (iii) create the reward rules about points and eventual bonuses in GDF, and (iv) write the high-level JSON 4 definition of the Level (as presented in Figure 4). Each level connects to the Gamification Engine rules thanks to a specific id (1) held by the series, references a game (2), a source diagram (3) from a source model (4), and features textual instructions (5).…”

“…While modeling is now validated as effective for solving complex problems or developing complex systems, its widespread and systematic application has not yet lived up to expectations. Several studies have been led to analyse the reasons of this situation and highlighted several issues, including the complexity of the modeling languages and tools [1][2][3] and the lack of required skills in abstraction [4].…”

Mining of DSLs and generator templates from reference applications

“…MDD is used in various software domains [4,12,22,23,37] and finds application in either new domains or newly discovered platforms within a known domain. The development of the IDE components is facilitated by a wealth of frameworks that make it possible to develop them on a higher abstraction level.…”