Trends and Insights into the Use of Model-Driven Engineering: A Survey

Hessa Alfraihi, Kevin Lano

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

5 Citations (Scopus)

Abstract

Model-Driven Engineering (MDE) has gained popularity as a software engineering approach that promises to improve productivity and software quality. However, its adoption in practice remains limited, and challenges with MDE tools, notations, and methods have been reported. In this study, we conducted a survey to investigate the current usage and challenges of MDE in academia and industry. A total of 119 participants completed the survey, representing a diverse group of organizations and roles. Our findings indicate that while MDE is used in various domains, its adoption is still not widespread, with many participants reporting lack of knowledge and skills as a barrier. We also found that difficulties with MDE concern mainly tools and notations, while methods are less problematic. Our results suggest that the adoption of MDE could be facilitated by improving the appropriateness and flexibility of MDE tools and providing training and education to increase MDE knowledge and skills.

Original languageEnglish
Title of host publicationProceedings - 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages286-295
Number of pages10
ISBN (Electronic)9798350324983
DOIs
Publication statusPublished - 2023
Event2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2023 - Vasteras, Sweden
Duration: 1 Oct 20236 Oct 2023

Publication series

NameProceedings - 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2023

Conference

Conference2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2023
Country/TerritorySweden
CityVasteras
Period1/10/20236/10/2023

Keywords

  • model-driven engineering
  • survey
  • usability

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