Software Engineering Modeling Applied to English Verb Classification (and Poetry)

TL;DR

This paper explores English verb classification to improve process modeling in software engineering, focusing on diagrammatic representations of core action verbs to enhance understanding of system processes.

Contribution

It introduces a novel approach to model English verbs diagrammatically for better process representation in software system modeling.

Findings

Identifies five fundamental verbs: create, process, receive, release, transfer.

Proposes a diagrammatic modeling method for these verbs.

Highlights potential benefits for linguistics and software engineering.

Abstract

In requirements specification, software engineers create a textual description of the envisioned system as well as develop conceptual models using such tools as Universal Modeling Language (UML) and System Modeling Language (SysML). One such tool, called FM, has recently been developed as an extension of the INPUT-PROCESS-OUTPUT (IPO) model. IPO has been used extensively in many interdisciplinary applications and is described as one of the most fundamental and important of all descriptive tools. This paper is an attempt to understanding the PROCESS in IPO. The fundamental way to describe PROCESS is in verbs. This use of language has an important implication for systems modeling since verbs express the vast range of actions and movements of all things. It is clear that modeling needs to examine verbs. Accordingly, this paper involves a study of English verbs as a bridge to learn about processes, not as linguistic analysis but rather to reveal the semantics of processes, particularly the five verbs that form the basis of FM states: create, process, receive, release, and transfer. The paper focuses on verb classification, and specifically on how to model the action of verbs diagrammatically. From the linguistics point of view, according to some researchers, further exploration of the notion of verb classes is needed for real-world tasks such as machine translation, language generation, and document classification. Accordingly, this non-linguistics study may benefit linguistics.