Work

AI Assisted Domain Modeling Explainability and Traceability

Year: 2024

Type: conference-paper

Abstract: Domain Models are abstract representations of selected elements in a domain that is created in a collaborative process between domain and modeler experts. The participants share domain knowledge to conceptualize and reason about the elements that will create the domain models. Through this exchange, a comprehensive and accurate representation of the domain is achieved, ensuring that the model captures the relevant aspects and relationships in the domain. Research in Artificial Intelligence (AI) has explored various methods to assist in the creation of domain models from text using Natural Language Processing (NLP) and Machine Learning (ML). Recent advancements with Large Language Models (LLMs) have shown that it is possible to create domain models using prompting techniques; however, the generated domain models contain errors and remain constrained by the performance of the LLM used.

Source: ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS)

DOI: 10.1145/3652620.3688197

Author: Jonathan Silva Mercado

Institution: University of Luxembourg

Language: English

Topic: Model-Driven Software Engineering Techniques

Subfield: Software

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4403935771

FWCI: 1.165

Cites: 21

Cited by: 4

Related to: 10