论文标题
建模国家和州机器的语义
Modeling the Semantics of States and State Machines
论文作者
论文摘要
系统的行为通常是通过模型来指定的，例如描述系统应如何行为的状态图。根据研究人员的说法，目前尚不清楚国家对要建模的系统的实际代表。标准不提供有关国家使用的足够定义或足够的指导。研究表明，这些不一致可能导致规格差或不完整，这反过来可能导致项目延迟或增加系统设计的成本。本文旨在建立对国家和州机器的概念的精确定义，这是由系统建模者（例如需求工程师）促进的目标，需要了解关键概念和词汇，例如状态和状态机器，这是主要的行为建模工具（例如，在UML中）。状态是事件驱动状态变化的状态机器的主要概念。这引发了有关这些与国家相关的符号的性质的疑问。这些概念的语义基于一种新的建模方法，称为“物品机器”，该方法应用于现有模型的许多示例。 Thinging Machine语义是建立在五个基本动作上的，该动作将静态模型分为定义事件的变化/状态。
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.
