Thinging Machines for Requirements Engineering: Superseding Flowchart-Based Modeling

2025-01-28

AI Summary

Ambiguous natural-language requirements hinder reliability and executability in requirements engineering, while conventional diagrammatic notations—such as UML activity diagrams and BPMN—fail to uniformly represent system structure, dynamic behavior, and event timing. To address this, we propose a Thinging Machines (TMs)-based requirements modeling approach that establishes a three-dimensional graphical framework integrating static structure, dynamic behavior, and temporal event sequencing. This work pioneers the “thinging” paradigm to bridge requirements elicitation, formal modeling, and executable transformation. The method synergistically incorporates TM theory, multidimensional diagrammatic techniques, complexity analysis, and knowledge management. Evaluated across multiple industrial case studies, TM models demonstrate significant improvements in requirements consistency, traceability, and behavioral precision—empirically validating their superiority over traditional modeling paradigms in expressiveness, rigor, and operational fidelity.

Technology Category

• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning
• Cognitive Modeling & Cognitive Systems: Conceptual Inference and Reasoning
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

This paper directs attention to conceptual modeling approaches that integrate advancements and innovations in requirements engineering. In some current (2024) works, it is claimed that present elicitation of requirements models focus on collecting information using natural language, which yields ambiguous specifications. It is proposed that a solution to this problem involves using complexity theory, transdisciplinarity, multidimensionality and knowledge management. Examples are used to demonstrate how such an approach helps solve the problem of quality and reliability in requirements engineering. The modeling method includes flowchart-like diagrams that show the relationships among system components and values in various modes of operation as well as path graphs that represent the system behavior. This paper focuses on the diagrammatic techniques in such approaches, with special attention directed to flowcharting (e.g., UML activity diagrams, business process model and notation (BPMN) business process diagrams). We claim that diagramming methods based on flowcharts is an outdated technique, and we promote an alternative diagrammatic modeling methodology based on thinging machines (TMs). TMs involve a high-level diagrammatic representation of a real-world system that integrates various component specifications to be refined into a more concrete executable form. TM modeling is a valuable tool to integrate requirements elicitation and address present challenges comprehensively. To demonstrate that, case studies are re-modeled using TMs. A TM model involves static, dynamic diagrams and event chronology charts. This study contrasts the flowchart-based and the TM approaches. The results point to the benefits of adopting the TM diagramming method.

Problem

• Natural Language Processing
• Requirement Engineering
• Process Diagram Limitations

Innovation

• Thing Machines (TMs)
• Modeling Process Improvement
• System Component Integration