状态和状态机的语义建模
Modeling the Semantics of States and State Machines
摘要：
一个系统的行为通常是通过模型来指定的，比如描述系统应该如何行为的状态图。根据研究人员的说法，目前还不清楚一个状态实际上代表了要建模的系统。标准没有提供关于状态使用的适当定义或充分指导。研究表明，这些不一致可能导致质量不佳或不完整的规格，这反过来可能导致项目延迟或增加系统设计成本。本文旨在建立状态和状态机概念的精确定义，这是系统建模者（例如，需求工程师）需要理解诸如状态和状态机之类的关键概念和词汇，它们是主要的行为建模工具（例如，在UML中）。状态是状态机的主要概念，其中事件驱动状态更改。这引起了关于这些状态相关符号的性质的问题。这些概念的语义是基于一种新的建模方法，称为thinging机应用到现有模型的一些例子。事物机器语义建立在将静态模型划分为定义事件的变化/状态的五个基本动作之上。
英文摘要：
A system s behavior is typically specified through models such as state diagrams that describe how the system should behave. According to researchers, it is not clear what a state actually represents regarding the system to be modeled. Standards do not provide adequate definitions of or sufficient guidance on the use of states. Studies show these inconsistencies can lead to poor or incomplete specifications, which in turn could result in project delays or increase the cost of the system design. This paper aims to establish a precise definition of the notion of states and state machines, a goal motivated by system modelers (e.g., requirement engineers) need to understand key concepts and vocabulary such as states and state machine, which are major behavioral modeling tools (e.g., in UML). State is the main notion of a state machine in which events drive state changes. This raises questions about the nature of these state-related notations. The semantics of these concepts is based on a new modeling methodology called the thinging machine applied to a number of examples of existing models. The thinging machine semantics is founded on five elementary actions that divide the static model into changes/states upon which events are defined.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
