Opportunities in intelligent modeling assistance
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EXPERT VOICE
Opportunities in intelligent modeling assistance Gunter Mussbacher1 · Benoit Combemale2 · Jörg Kienzle1 · Silvia Abrahão3 · Hyacinth Ali1 · Nelly Bencomo4 · Márton Búr1 · Loli Burgueño5,6 · Gregor Engels7 · Pierre Jeanjean8 · Jean-Marc Jézéquel8 · Thomas Kühn9 · Sébastien Mosser10 · Houari Sahraoui11 · Eugene Syriani11 · Dániel Varró1 · Martin Weyssow11 Received: 3 June 2020 / Accepted: 5 June 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Modeling is requiring increasingly larger efforts while becoming indispensable given the complexity of the problems we are solving. Modelers face high cognitive load to understand a multitude of complex abstractions and their relationships. There is an urgent need to better support tool builders to ultimately provide modelers with intelligent modeling assistance that learns from previous modeling experiences, automatically derives modeling knowledge, and provides context-aware assistance. However, current intelligent modeling assistants (IMAs) lack adaptability and flexibility for tool builders, and do not facilitate understanding the differences and commonalities of IMAs for modelers. Such a patchwork of limited IMAs is a lost opportunity to provide modelers with better support for the creative and rigorous aspects of software engineering. In this expert voice, we present a conceptual reference framework (RF-IMA) and its properties to identify the foundations for intelligent modeling assistance. For tool builders, RF-IMA aims to help build IMAs more systematically. For modelers, RF-IMA aims to facilitate comprehension, comparison, and integration of IMAs, and ultimately to provide more intelligent support. We envision a momentum in the modeling community that leads to the implementation of RF-IMA and consequently future IMAs. We identify open challenges that need to be addressed to realize the opportunities provided by intelligent modeling assistance. Keywords Model-based software engineering · Intelligent modeling assistance · Integrated development environment · Artificial intelligence · Development data · Feedback
1 Introduction Over the last decades, modeling activities have been applied across the whole life-cycle of complex software-intensive
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Benoit Combemale [email protected]
1
McGill University, Montreal, Canada
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Université de Toulouse and Inria, Toulouse, France
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Universitat Politècnica de València, Valencia, Spain
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Aston University, Birmingham, UK
5
Universitat Oberta de Catalunya, Barcelona, Spain
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CEA LIST, Palaiseau, France
7
Paderborn University, Paderborn, Germany
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Inria, CNRS, IRISA, Université de Rennes, Rennes, France
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Karlsruher Institut für Technologie, Karlsruhe, Germany
10
Université du Québec à Montréal, Montreal, Canada
11
Université de Montréal, Montreal, Canada
systems to support all stakeholders involved in software development, mostly thanks to the use of abstractions— provided by general-purpose and domain-specific modeling languages—and separation of concerns. Model
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