Textual-Based vs. Thinging Machines Conceptual Modeling

TL;DR

This paper compares textual-based and Thinging Machine (TM) conceptual modeling approaches, demonstrating that TM modeling offers a more efficient and effective methodology for domain modeling than traditional diagrammatic schemes like UML.

Contribution

It introduces TM modeling as a novel approach, emphasizing its dynamic, action-based structure and potential for simplifying complex domain representations.

Findings

TM modeling provides a clearer conceptual foundation.

TM models are simpler and more dynamic than UML diagrams.

Contrasts show TM's advantages in developer efficiency.

Abstract

Software engineers typically interpret the domain description in natural language and translate it into a conceptual model. Three approaches are used in this domain modeling: textual languages, diagrammatic languages, and a mixed based of text and diagrams. According to some researchers, relying on a diagrammatic notation levies certain burdens for designing large models because visual languages are intended to depict everything diagrammatically during a development process but fail to do so for a lack of developer efficiency. It is claimed that textual formats enable easier manipulation in editors and tools and facilitate the integration of ontologies in software systems. In this paper, we explore the problem of the relationship between textual format and diagramming in conceptual modeling. The main focus is modeling based on the so-called thinging machine (TM). Several examples are developed in detail to contrast side-by-side targeted domains represented in textual description and TM modeling. A TM model is defined as a thimac (thing/machine) with a time feature that forms dynamic events over static thimacs utilizing five generic actions: create, process, release, transfer, and receive. This provides a conceptual foundation that can be simplified further by eliminating the actions of release, transfer, and receive. A multilevel reduction in the TM diagram s complexity can also be achieved by assuming diagrammatic notations represent the actions of creation and processing. We envision that special tools will help improve developer efficiency. The study s results of contrasting textual and mix-based descriptions vs. TM modeling justify our claim that TM modeling is a more appropriate methodology than other diagrammatic schemes (e.g., UML classes) examined in this paper.