Understanding State Machines, Statecharts, and Software Classification
State Machines and Statecharts
State machines and statechart diagrams capture the dynamic aspects of a software-intensive system. Events can be categorized as signals, calls, changes, or time-based. Except for call events, which are synchronous, all others are asynchronous.
Signal Events
Signal events are triggered by external events. Signals are similar to classes in that they have attributes, operations, instances, and participate in generalization relationships. The sender continues execution after sending a signal; control is not transferred.
Call Events
Call events can trigger a state transition in a state machine. An object (sender) calls an operation of another object (receiver), leading to the receiver taking control. After the receiver completes the operation, it transitions to a new state, and control returns to the sender.
Change Events
Change events represent the occurrence of an event when a Boolean expression becomes true due to a state change or the satisfaction of a condition. The keyword when signifies a change event.
Time Events
Time events represent the passage of time. They are denoted by the keyword after, followed by an expression, such as after(expression).
State Machines
A state machine comprises a set of states, a set of events, a sequence of state changes in response to received events (transitions), and responses due to received events (actions). A state machine emphasizes:
- The lifetime of an object
- Potential states and transitions from one state to another
- The flow of control from activity to activity (activity diagram)
A composite state can have either sequential states (a disjoint partitioning) or concurrent states (an orthogonal partitioning).
Software Classification
Classification is fundamental to creating knowledge taxonomies. It aims to identify common aspects of things (key abstractions and mechanisms), thus supporting smaller and simpler software. There are no general, automated methods for identifying the classification of objects and classes. Iterative and incremental classification emphasizes a dynamic process, constantly optimizing and adjusting the classification to ensure its adaptability and effectiveness.
Classical Categorization
Identify classes and objects according to the relevant properties for the problem domain of interest that form disjoint sets.
Conceptual Clustering
Identify collaborating objects using inexact (“best fit”) criteria. Conceptual clustering based on descriptions is related to probabilistic or fuzzy theories. Conceptual categories can serve as the basis for forming classical categories by grouping things with similar properties into different categories.
Prototype Theory
Identify objects by association with prototypical objects. Objects of a classification resemble, in some significant way, a prototypical object. Objects belonging to the classification must share some, but not all, properties with the prototypical object.
Classic Approaches
Classic approaches in database modeling abstract real-world elements into categories that can be represented in a database, such as people, places, and items. These categories help model the structure and function of the real world, providing a foundation for designing and analyzing database structures.
Behavioral and Domain Approaches
These approaches emphasize behavioral and domain analysis. Behavioral analysis focuses on understanding the behavior and responsibilities of objects, while domain analysis focuses on understanding the structure of objects and classes within a specific application domain. These methods help software engineers better understand and design software systems to meet the needs and characteristics of a particular domain.
Use Cases
- Use-case: A short verb phrase naming some behavior.
- Actor: A role name a user plays when interacting with the system.
- Association: Signifies communication between an actor and a use case.
- Generalization: A child use case inherits the behavior and meaning of the parent use case.
- Include: One use case (base use case) explicitly incorporates the behavior of another use case (supplier use case). The base use case pulls in behavior from the supplier use case.
- Extend: One use case (base use case) implicitly incorporates the behavior of another use case. The base use case may stand alone, but under certain conditions, it may be extended.
Classification Methods
- Classical Categorization: Classification based on properties.
- Conceptual Clustering: Classification based on concepts.
- Prototype Theory: Classification based on association with prototypes.