Opportunities in intelligent modeling assistance

Gunter Mussbacher, Benoit Combemale*, Jörg Kienzle, Silvia Abrahão, Hyacinth Ali, Nelly Bencomo, Márton Búr, Loli Burgueño, Gregor Engels, Pierre Jeanjean, Jean Marc Jézéquel, Thomas Kühn, Sébastien Mosser, Houari Sahraoui, Eugene Syriani, Dániel Varró, Martin Weyssow

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)1045-1053
Number of pages9
JournalSoftware and Systems Modeling
Volume19
Issue number5
Early online date17 Jul 2020
DOIs
Publication statusPublished - 1 Sep 2020

Keywords

  • Artificial intelligence
  • Development data
  • Feedback
  • Integrated development environment
  • Intelligent modeling assistance
  • Model-based software engineering

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