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State pattern
State pattern
from Wikipedia

The state pattern is a behavioral software design pattern that allows an object to alter its behavior when its internal state changes. This pattern is close to the concept of finite-state machines. The state pattern can be interpreted as a strategy pattern, which is able to switch a strategy through invocations of methods defined in the pattern's interface.

The state pattern is used in computer programming to encapsulate varying behavior for the same object, based on its internal state. This can be a cleaner way for an object to change its behavior at runtime without resorting to conditional statements and thus improve maintainability.[1]: 395 

Overview

[edit]
A sample UML class and sequence diagram for the State design pattern.[2]

The state design pattern is one of twenty-three design patterns documented by the Gang of Four that describe how to solve recurring design problems. Such problems cover the design of flexible and reusable object-oriented software, such as objects that are easy to implement, change, test, and reuse.[3]

The state pattern is set to solve two main problems:[4]

  • An object should change its behavior when its internal state changes.
  • State-specific behavior should be defined independently. That is, adding new states should not affect the behavior of existing states.

Implementing state-specific behavior directly within a class is inflexible because it commits the class to a particular behavior and makes it impossible to add a new state or change the behavior of an existing state later, independently from the class, without changing the class. In this, the pattern describes two solutions:

  • Define separate (state) objects that encapsulate state-specific behavior for each state. That is, define an interface (state) for performing state-specific behavior, and define classes that implement the interface for each state.
  • A class delegates state-specific behavior to its current state object instead of implementing state-specific behavior directly.

This makes a class independent of how state-specific behavior is implemented. New states can be added by defining new state classes. A class can change its behavior at run-time by changing its current state object.

Structure

[edit]
State in UML[1]

In the accompanying Unified Modeling Language (UML) class diagram, the Context class doesn't implement state-specific behavior directly. Instead, Context refers to the State interface for performing state-specific behavior (state.handle()), which makes Context independent of how state-specific behavior is implemented. The ConcreteStateA and ConcreteStateB classes implement the State interface, that is, implement (encapsulate) the state-specific behavior for each state. The UML sequence diagram shows the run-time interactions:

The Context object delegates state-specific behavior to different State objects. First, Context calls handle(this) on its current (initial) state object (ConcreteStateA), which performs the operation and calls setState(ConcreteStateB) on Context to change context's current state to ConcreteStateB. The next time, Context again calls handle(this) on its current state object (ConcreteStateB), which performs the operation and changes context's current state to ConcreteStateA.

Example

[edit]

This is a C++ example demonstrating the state pattern.

import std;

using std::shared_ptr;

// Abstract State
class FanState {
public:
    virtual void handleButtonPress(class Fan& fan) const = 0;
    virtual ~FanState() = default;
};

// Context
class Fan {
private:
    shared_ptr<FanState> currentState;
public:
    explicit Fan(shared_ptr<FanState> state):
        currentState{state} {}

    void setState(shared_ptr<FanState> state) noexcept {
        currentState = state;
    }

    void pressButton() noexcept {
        currentState->handleButtonPress(*this);
    }
};

// Concrete States
class OffState : public FanState {
public:
    void handleButtonPress(Fan& fan) const override {
        std::println("Fan is OFF -> Switching to LOW speed.");
        fan.setState(std::make_shared<LowSpeedState>());
    }
};

class LowSpeedState : public FanState {
public:
    void handleButtonPress(Fan& fan) const override {
        std::println("Fan is on LOW speed -> Switching to HIGH speed.");
        fan.setState(make_shared<HighSpeedState>());
    }
};

class HighSpeedState : public FanState {
public:
    void handleButtonPress(Fan& fan) const override {
        std::println("Fan is on HIGH speed -> Turning OFF.");
        fan.setState(make_shared<OffState>());
    }
};

int main() {
    Fan fan(std::make_shared<OffState>());

    // Simulate pressing the button several times
    fan.pressButton(); // OFF -> LOW
    fan.pressButton(); // LOW -> HIGH
    fan.pressButton(); // HIGH -> OFF
    fan.pressButton(); // OFF -> LOW

    return 0;
}

See also

[edit]

References

[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
The State pattern is a behavioral design pattern in that enables an object to change its behavior when its internal state changes, making it appear as though the object has changed its class. It achieves this by encapsulating state-specific behavior into separate classes, which are delegated to by a context object, thereby avoiding complex conditional logic in the main class. Introduced as one of the 23 classic in the 1994 book Design Patterns: Elements of Reusable Object-Oriented Software by , Richard Helm, Ralph Johnson, and John Vlissides—commonly known as the (GoF)—the State pattern addresses the problem of managing objects with multiple possible states, such as a document progressing from draft to published or a handling coin insertions and selections. The pattern's core structure involves:
  • A Context class that maintains a reference to the current State object and delegates state-dependent operations to it.
  • An abstract State interface declaring methods for state-specific behaviors.
  • Concrete State classes implementing the interface, each handling one state and potentially transitioning to another state by updating the context's state reference.
This design promotes the Single Responsibility Principle by isolating each state's logic and adheres to the Open-Closed Principle by allowing new states to be added without modifying existing code. It is particularly applicable in scenarios with numerous states, frequent state transitions, or duplicated conditional statements, such as components, engines, or state machines. While beneficial for maintainability and flexibility, the pattern can introduce overhead if the number of states is small or stable, potentially leading to excessive classes. The State pattern relates closely to the Strategy pattern, extending it with state transitions rather than interchangeable algorithms, and shares similarities with the Bridge pattern in decoupling abstractions from implementations, though with a focus on behavioral variation over structural. Implementations are common across object-oriented languages like Java, C++, and Python, often using interfaces or abstract classes to define states.

Overview and Motivation

Definition and Purpose

The State pattern is one of the 23 behavioral design patterns cataloged by the in their influential 1994 book, Design Patterns: Elements of Reusable Object-Oriented Software. As a , it enables an object to appear to change its class by delegating state-specific behavior to separate state objects, allowing the object's behavior to vary dynamically as its internal state changes. This delegation mechanism ensures that the object maintains a consistent interface while adapting its responses based on the current state, effectively encapsulating variations in behavior that would otherwise require scattered conditional logic. The pattern's primary intent is to allow an object to alter its when its internal state changes, without relying on extensive conditional statements like if-else chains that proliferate in state-dependent code. By encapsulating each possible state in its own class, the State pattern promotes the Open-Closed Principle, whereby the core context class remains closed to modification but open to extension through the addition of new state classes. This approach localizes state-specific logic, reducing complexity and enhancing maintainability in systems where evolves with state transitions. At its core, the State pattern involves a context object that maintains a reference to the current State object, which defines a for all state-specific behaviors. Concrete state subclasses implement this interface to handle operations appropriate to their particular state, and they may trigger transitions to other states by updating the context's reference, thereby enabling seamless behavioral shifts.

Problem It Solves

In , objects frequently need to alter their behavior based on internal state changes, such as a progressing from draft to published. A naive implementation relies on extensive conditional statements—like long if-else chains or switch blocks—within a single class to route actions according to the current state, which causes significant as the number of states grows. This approach complicates maintenance, as modifications to state logic must propagate across multiple methods, and it violates the Single Responsibility Principle by forcing one class to manage diverse behavioral concerns. Consider a TCP connection object, which operates in distinct states including , Established, Syn Sent, and Closed; in the Established state, methods like send() transmit data, whereas in Closed, they might raise errors or do nothing. Implementing these variations through scattered conditionals fragments the logic throughout the class, making the codebase harder to read and reason about. Without addressing this, extending the system becomes problematic: introducing a new state demands updates to conditional blocks in numerous locations, heightening the chance of overlooked errors in state transitions. Additionally, the resulting tight binds state-handling logic inextricably to the class, rendering the design inflexible and prone to bugs during evolution.

Structure and Components

UML Class Diagram

The UML class diagram for the State pattern depicts the core structure of the design, illustrating how an object's behavior varies based on its internal state through and polymorphism. At the center is the class, which serves as the primary interface for clients and maintains a reference to the current State object, represented as a composition relationship—a filled diamond arrow pointing from Context to State with a multiplicity of 1 on both ends, indicating that each Context instance owns exactly one State instance at a time. The State is modeled as an abstract class or interface, featuring an abstract method such as handle() (or request() in some notations), which defines the interface for state-specific operations and often takes the as a to enable state transitions. ConcreteState subclasses, such as ConcreteStateA and ConcreteStateB, extend or implement State via relationships—open triangle s pointing from each ConcreteState to State—where they provide concrete implementations of the handle() method tailored to their respective states. Additionally, a dependency relationship, shown as a dashed from State to , highlights how state operations may rely on the for accessing shared data or initiating changes. This diagram emphasizes the pattern's encapsulation of state-dependent behavior, with the Context delegating requests to the current State without direct knowledge of concrete implementations, thereby promoting and extensibility for adding new states. Variations in the diagram may include optional methods in the State interface, such as changeState() or explicit transition operations, to model state shifts more directly, particularly when transitions are centralized rather than distributed across ConcreteStates.

Key Elements and Responsibilities

The State pattern comprises three primary elements: the class, the State interface, and one or more ConcreteState classes, each with distinct responsibilities that enable an object's to vary polymorphically based on its internal state. The class serves as the primary interface for clients, encapsulating the object's overall while maintaining a reference to the current ConcreteState instance. It delegates state-specific requests to this current state object and typically includes a method, such as setState() or changeState(), to allow transitions to a new state. This delegation ensures that the remains independent of concrete state details, promoting flexibility in . The State interface defines a common protocol for all state-specific behaviors, typically declaring abstract methods like () that represent operations varying by state. It may also include optional methods for initiating state changes, though transitions are often handled within concrete implementations. By providing this uniform interface, the State ensures that all concrete states can be used interchangeably by the . ConcreteState classes implement the State interface, each tailoring the behavior to a particular state of the —for instance, defining how a request is processed differently in "open" versus "closed" states. These classes state transitions by invoking the Context's setState() method with a new ConcreteState instance, and in complex scenarios, they may share a transition table to centralize logic for determining next states. ConcreteStates often maintain a reference back to the Context to access additional or trigger changes, though this should be minimized to avoid circular dependencies where possible. In terms of interactions, clients interact solely with the Context, which forwards requests to the current ConcreteState for execution, resulting in polymorphic behavior as different states alter the observed outcome. State transitions occur explicitly when a ConcreteState determines the need for change, replacing the Context's state reference and thereby shifting future behaviors without modifying the Context itself. This collaboration localizes state-dependent code and makes transitions transparent to clients. Key design invariants include adherence to a single State interface across all ConcreteStates to guarantee substitutability, and careful management of transitions to prevent invalid states, often through atomic operations or guarded methods. While ConcreteStates may reference the for transitions, designs should avoid unnecessary mutual references to mitigate potential cycles in object graphs.

Implementation

Pseudocode

The State pattern's pseudocode provides a outline of its core structure, emphasizing how the delegates behavior to the current State and enables transitions between concrete states. This representation highlights the encapsulation of state-specific logic and the avoidance of conditional branching in the . The maintains a to the current State and includes methods for updating the state and handling requests by delegating to the State.

pseudocode

class [Context](/page/Context) { State state; function setState(State newState) { state = newState; } function handleRequest() { state.[handle](/page/Handle)(this); } }

class [Context](/page/Context) { State state; function setState(State newState) { state = newState; } function handleRequest() { state.[handle](/page/Handle)(this); } }

The State defines an interface for handling requests, with the passed to allow states to trigger transitions.

pseudocode

interface State { function [handle](/page/Handle)([Context](/page/Context) context); }

interface State { function [handle](/page/Handle)([Context](/page/Context) context); }

Concrete states implement the handle method to execute state-specific logic and initiate transitions by calling the Context's setState method. For example:

pseudocode

class ConcreteStateA implements State { function handle(Context context) { // Perform actions specific to State A // ... context.setState(new ConcreteStateB()); } } class ConcreteStateB implements State { function handle(Context context) { // Perform actions specific to State B // ... } }

class ConcreteStateA implements State { function handle(Context context) { // Perform actions specific to State A // ... context.setState(new ConcreteStateB()); } } class ConcreteStateB implements State { function handle(Context context) { // Perform actions specific to State B // ... } }

For systems with numerous states, transition logic can be centralized using a state transition table, typically implemented as a map keyed by the current state and an event to determine the next state. This approach simplifies management of complex finite state machines by externalizing transition rules.

pseudocode

map< pair<State, Event>, State > transitionTable; // Example initialization transitionTable[(ConcreteStateA, EventX)] = ConcreteStateB; transitionTable[(ConcreteStateB, EventY)] = ConcreteStateA; // In handle method function handle(Context context, Event event) { State nextState = transitionTable[(this, event)]; if (nextState != null) { context.setState(nextState); } }

map< pair<State, Event>, State > transitionTable; // Example initialization transitionTable[(ConcreteStateA, EventX)] = ConcreteStateB; transitionTable[(ConcreteStateB, EventY)] = ConcreteStateA; // In handle method function handle(Context context, Event event) { State nextState = transitionTable[(this, event)]; if (nextState != null) { context.setState(nextState); } }

To ensure robustness, error handling in state transitions involves validating changes before applying them, preventing invalid states that could lead to undefined behavior.

pseudocode

function setState(State newState) { State currentState = this.state; if (!isValidTransition(currentState, newState)) { throw new InvalidStateTransitionError("Transition from " + currentState + " to " + newState + " is not allowed"); } this.state = newState; }

function setState(State newState) { State currentState = this.state; if (!isValidTransition(currentState, newState)) { throw new InvalidStateTransitionError("Transition from " + currentState + " to " + newState + " is not allowed"); } this.state = newState; }

Example in Object-Oriented Language

The State pattern can be implemented in using an interface for the state abstraction and classes for each state, allowing the context object to delegate dynamically. The example below demonstrates a simple media player context with three states: StopState (initial state where no playback occurs), PlayState (active playback), and PauseState (temporary halt during playback). The player starts in the StopState and transitions between states via methods like play(), stop(), and pause(), with each state defining appropriate responses and transitions.

java

// State interface interface State { void handlePlay(MediaPlayer context); void handleStop(MediaPlayer context); void handlePause(MediaPlayer context); } // Concrete state: StopState class StopState implements State { @Override public void handlePlay(MediaPlayer context) { System.out.println("Starting playback."); context.setState(new PlayState()); } @Override public void handleStop(MediaPlayer context) { System.out.println("Already stopped."); } @Override public void handlePause(MediaPlayer context) { System.out.println("Cannot pause; not playing."); } } // Concrete state: PlayState class PlayState implements State { @Override public void handlePlay(MediaPlayer context) { System.out.println("Already playing."); } @Override public void handleStop(MediaPlayer context) { System.out.println("Stopping playback."); context.setState(new StopState()); } @Override public void handlePause(MediaPlayer context) { System.out.println("Pausing playback."); context.setState(new PauseState()); } } // Concrete state: PauseState class PauseState implements State { public void handlePlay(MediaPlayer context) { System.out.println("Resuming playback."); context.setState(new PlayState()); } @Override public void handleStop(MediaPlayer context) { System.out.println("Stopping from paused."); context.setState(new StopState()); } @Override public void handlePause(MediaPlayer context) { System.out.println("Already paused."); } } // Context: MediaPlayer class MediaPlayer { private State state; public MediaPlayer() { this.state = new StopState(); // Initial state setup } public void setState(State state) { this.state = state; } public void play() { state.handlePlay(this); } public void stop() { state.handleStop(this); } public void pause() { state.handlePause(this); } } // Demo public class MediaPlayerDemo { public static void main(String[] args) { MediaPlayer player = new MediaPlayer(); player.play(); // Output: Starting playback. player.pause(); // Output: Pausing playback. player.stop(); // Output: Stopping from paused. player.play(); // Output: Starting playback. } }

// State interface interface State { void handlePlay(MediaPlayer context); void handleStop(MediaPlayer context); void handlePause(MediaPlayer context); } // Concrete state: StopState class StopState implements State { @Override public void handlePlay(MediaPlayer context) { System.out.println("Starting playback."); context.setState(new PlayState()); } @Override public void handleStop(MediaPlayer context) { System.out.println("Already stopped."); } @Override public void handlePause(MediaPlayer context) { System.out.println("Cannot pause; not playing."); } } // Concrete state: PlayState class PlayState implements State { @Override public void handlePlay(MediaPlayer context) { System.out.println("Already playing."); } @Override public void handleStop(MediaPlayer context) { System.out.println("Stopping playback."); context.setState(new StopState()); } @Override public void handlePause(MediaPlayer context) { System.out.println("Pausing playback."); context.setState(new PauseState()); } } // Concrete state: PauseState class PauseState implements State { public void handlePlay(MediaPlayer context) { System.out.println("Resuming playback."); context.setState(new PlayState()); } @Override public void handleStop(MediaPlayer context) { System.out.println("Stopping from paused."); context.setState(new StopState()); } @Override public void handlePause(MediaPlayer context) { System.out.println("Already paused."); } } // Context: MediaPlayer class MediaPlayer { private State state; public MediaPlayer() { this.state = new StopState(); // Initial state setup } public void setState(State state) { this.state = state; } public void play() { state.handlePlay(this); } public void stop() { state.handleStop(this); } public void pause() { state.handlePause(this); } } // Demo public class MediaPlayerDemo { public static void main(String[] args) { MediaPlayer player = new MediaPlayer(); player.play(); // Output: Starting playback. player.pause(); // Output: Pausing playback. player.stop(); // Output: Stopping from paused. player.play(); // Output: Starting playback. } }

This implementation follows the structure outlined in the Gang of Four design patterns book, where states encapsulate behavior and manage transitions internally. To trace execution, consider the demo sequence starting from the initial StopState: Invoking play() calls handlePlay on StopState, which prints "Starting playback." and sets the context to PlayState. Next, pause() delegates to PlayState's handlePause, printing "Pausing playback." and transitioning to PauseState. Then, stop() on PauseState prints "Stopping from paused." and sets StopState. Finally, another play() from StopState restarts the cycle, printing "Starting playback." and returning to PlayState. This demonstrates how state changes alter the object's behavior without modifying the context class itself. In , the State interface enables polymorphism, with concrete states extending the common ; the holds a reference to the interface type, avoiding null states by initializing in the constructor (e.g., to StopState). For C++, an abstract base class with pure virtual methods could replace the interface, using virtual for proper cleanup. The code compiles with standard (e.g., javac MediaPlayerDemo.java) requiring no external libraries, producing a MediaPlayerDemo.class executable via java MediaPlayerDemo. At runtime, polymorphism is resolved through : the JVM's (vtable) invokes the overridden method based on the actual object instance (e.g., PlayState's handlePlay), enabling seamless behavior variation as states change without conditional logic in the .

Applications and Evaluation

Common Use Cases

The State pattern finds frequent application in (UI) development, particularly in document editors where the behavior of the interface changes based on the document's state, such as editing, viewing, or locked modes. In tools like word processors, the editing state allows text modifications and cursor interactions, while the viewing state restricts changes to read-only display, and the locked state prevents any alterations to ensure during sharing or review. This approach encapsulates state-specific logic, making the UI more maintainable as new states, like collaborative editing, can be added without altering the core editor class. In networking protocols, the State pattern is commonly used to implement finite state machines for managing connection lifecycles, as exemplified by the Transmission Control Protocol (TCP). TCP connections transition through states such as SYN_SENT (initiating a connection), ESTABLISHED (data transfer active), and FIN_WAIT (closing the connection), where each state defines valid actions like sending acknowledgments or handling timeouts to avoid invalid operations. This pattern mirrors the design in seminal works on software patterns, enabling robust protocol implementations by delegating behavior to state objects. Video games often employ the State pattern for character controllers, where an entity's behavior varies by state, such as (no movement), running (continuous locomotion), or ( and collision handling). Input processing differs per state—for instance, a jump input in triggers a jump transition, while in running it combines with speed boosts—allowing developers to modularize , physics, and event responses without monolithic conditional logic. This is particularly effective in engines for handling complex AI or player mechanics. In embedded systems, the State pattern controls real-time devices like vending machines, managing states including idle (awaiting selection), selecting (processing item choice after payment), and dispensing (delivering product and returning change). Transitions are triggered by events like coin insertion or button presses, ensuring safe operations such as refunding in case of errors, which is critical for hardware-software integration. The pattern is best applied to objects exhibiting three or more distinct states with complex, event-driven transitions, as it eliminates sprawling conditional statements and promotes extensibility; in modern contexts, it integrates with frameworks by modeling stateful streams, akin to the State monad for handling asynchronous behaviors.

Benefits and Trade-offs

The State pattern offers several key benefits in , primarily by promoting cleaner and more maintainable code structures. By encapsulating state-specific behaviors into dedicated classes, it eliminates the need for large conditional statements within the context class, adhering to the Single Responsibility Principle and reducing complexity in the core logic. This separation allows each state class to handle its own transitions and actions independently, making the system easier to understand and modify without affecting unrelated parts. Another advantage is enhanced extensibility, as new states can be added by simply implementing the state interface or extending the abstract class, without altering existing code, in line with the Open-Closed Principle. This modularity also improves testability, since individual state classes can be unit-tested in isolation, focusing solely on their specific behaviors and transitions, which simplifies verification and debugging. Despite these strengths, the pattern introduces trade-offs, particularly in terms of increased complexity and resource usage. It results in a proliferation of classes—one for each state—which can lead to a larger and higher maintenance overhead if the number of states grows excessively, potentially causing "state explosion" in overly granular designs. Additionally, frequent state transitions may incur minor performance costs due to object creation, delegation through interfaces, and method invocations, compared to direct conditional checks, though this overhead is often negligible in non-real-time applications. The pattern is not ideal for all scenarios and should be avoided in cases with only a few transient states or infrequent changes, where simpler alternatives like enums suffice without the added layers. In resource-constrained environments, such as embedded systems, the extra objects could amplify memory usage, making it less suitable unless states are pooled or flyweight-optimized. Overall, while it excels in dynamic, state-heavy systems, judicious application is key to balancing gains against structural and runtime costs.

Comparison to Strategy Pattern

The State pattern and the are both behavioral design patterns that rely on composition to delegate to separate objects, allowing a context class to alter its functionality without subclassing. However, their intents differ fundamentally: the State pattern enables an object to change its behavior when its internal state changes, effectively making it appear as though the object has changed its class, whereas the defines a family of interchangeable algorithms and allows the context to select and switch between them at runtime to encapsulate varying behaviors independently of the context's state evolution. In terms of structure, both patterns feature a context that holds a reference to an abstract component (State or interface), with concrete implementations providing the varying behaviors. The key structural distinction lies in : in the State pattern, concrete states often include methods to trigger transitions to other states (e.g., via a setState() call on the context), creating a dynamic lifecycle where states can reference and modify the context's state; in contrast, the treats strategies as independent, self-contained algorithms with no inherent awareness of each other or the need to alter the context's state, and the client typically manages any strategy swaps externally. Regarding applicability, the State pattern is best suited for scenarios where an object's behavior evolves through a series of internal states, such as managing stages in a document (e.g., draft to published) or progressing phases in a game's enemy AI, where states handle transitions autonomously to model finite state machines. The , however, excels in cases requiring pluggable, algorithm-specific behaviors without ongoing state changes, like selecting different sorting methods (e.g., vs. mergesort) or search algorithms in a navigation system, where the focus is on runtime flexibility rather than lifecycle progression. While overlaps exist in reactive systems where both could delegate behaviors, the State pattern emphasizes state-driven evolution, whereas Strategy prioritizes algorithmic interchangeability.

Comparison to Flyweight Pattern

The State pattern and the both involve managing object state but serve distinct purposes in . The State pattern, a behavioral , encapsulates state-specific behavior into separate objects, enabling an object to alter its behavior dynamically by delegating to the appropriate state instance, often creating one ConcreteState object per active state type to handle unique behavioral logic. In contrast, the , a structural , optimizes memory by sharing immutable intrinsic state—such as fixed attributes like color or texture—across multiple similar objects, while extrinsic state, like position or context-specific data, is passed externally or stored separately to allow variations without duplication. Structurally, the State pattern features a Context class that holds a reference to the current State interface implementation, with ConcreteState subclasses providing the behavior and potentially triggering transitions between states. The , however, employs a interface for shared objects, a FlyweightFactory to manage a pool of reusable ConcreteFlyweight instances containing intrinsic state, and a client or that supplies extrinsic state during operations to customize behavior without altering the shared flyweights. The State pattern applies to scenarios where objects exhibit unique behavioral contexts that evolve over time, such as per-object states in a , whereas the Flyweight pattern suits cases involving numerous similar objects where memory efficiency is critical, for example, game characters sharing base stats like appearance while differing in positions or health. To optimize implementations, the State pattern may incorporate Flyweight techniques when state objects lack instance-specific data, allowing shared state instances across multiple contexts to reduce overhead, as state objects in such cases resemble stateless . For instance, in a application, the State pattern handles unique document states like "editing" or "saved," with each document delegating to its current state object for behavior. By comparison, the could optimize rendering of identical UI elements, such as multiple toolbar icons sharing intrinsic properties like shape and color, while using extrinsic state for their varying screen positions.

References

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