Skip to Main content Skip to Navigation
Journal articles

Opportunities in Intelligent Modeling Assistance

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 chal
Document type :
Journal articles
Complete list of metadatas

Cited literature [46 references]  Display  Hide  Download

https://hal.inria.fr/hal-02876536
Contributor : Benoit Combemale <>
Submitted on : Saturday, June 20, 2020 - 11:38:54 PM
Last modification on : Wednesday, June 24, 2020 - 4:19:51 PM

File

ima-sosym-expert-voice.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02876536, version 1

Citation

Gunter Mussbacher, Benoit Combemale, Jörg Kienzle, Silvia Abrahão, Hyacinth Ali, et al.. Opportunities in Intelligent Modeling Assistance. Software and Systems Modeling, Springer Verlag, 2020. ⟨hal-02876536⟩

Share

Metrics

Record views

47

Files downloads

174