Modeling the Semantics of States and State Machines
This addresses a foundational problem for system modelers like requirement engineers, but it is incremental as it builds on existing modeling tools like UML.
The paper tackles the lack of clear definitions for states and state machines in system modeling, which can lead to poor specifications and increased costs, by establishing precise semantics using a new methodology called the thinging machine applied to examples.
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.