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.

中文翻译：

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对状态和状态机的语义建模

系统的行为通常通过诸如描述系统应该如何行为的状态图之类的模型来指定。据研究人员称，对于要建模的系统，状态实际上代表什么尚不清楚。标准没有对状态的使用提供足够的定义或足够的指导。研究表明，这些不一致会导致规范不完善或不完整，进而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，系统建模者（例如需求工程师）的目标是理解关键概念和词汇，例如状态和状态机，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，其中事件驱动状态变化。这引发了关于这些与状态相关的符号的性质的问题。这些概念的语义基于一种称为事物机器的新建模方法，该方法应用于现有模型的许多示例。事物机器语义建立在五个基本动作上，这些动作将静态模型划分为定义事件的变化/状态。