In next part we will start build our "State Machine" in java
If you already aware of basics, go straight at : “Designing a State Machine in Java” section
First explore Graph Theory : A Foundation for State Machines
Understanding Graph Theory :
Graph theory is a branch of mathematics that deals with the study of graphs, which are mathematical structures used to model pairwise relationships between objects. A graph consists of vertices/nodes (circles) and edges/connections (lines joins nodes) that link pairs of vertices. These graphs can be directed or undirected, weighted or unweighted, and can represent a wide range of real-world phenomena.
Key Concepts in Graph Theory :
Vertices (Nodes): Represent entities or objects in a system.
Edges (Connections): Define relationships or connections between vertices.
Directed vs. Undirected Graphs: In directed graphs, edges have a specific direction, while in undirected graphs, edges have no direction.
Weighted vs. Unweighted Graphs: Edges in weighted graphs have associated weights or values, while edges in unweighted graphs do not.
How Graph Theory is used in real world :
Graph theory finds applications in various fields, including computer science, biology, social sciences, and network analysis. Some common applications include:
Network Routing Algorithms : Graphs are used to model computer networks, and graph algorithms help in finding optimal routes for data transmission.
Social Network Analysis : Graphs represent social networks, and graph algorithms help analyze connectivity, influence, and community structures within these networks.
Transportation Networks : Graphs model road networks, and algorithms optimize transportation routes, traffic flow, and logistics.
State Machines and Graph Theory :
State machines, also known as finite state machines (FSMs), are a practical application of graph theory. A state machine can be represented as a directed graph, where vertices represent states, and edges represent transitions between states triggered by inputs or events. The transition from one state to another is determined by the current state and the input received, similar to traversing edges in a graph based on certain conditions.
Let’s distinct Workflow from state machine, before we go deep into state machine
Workflow represents a predefined sequence of tasks aimed at achieving a specific goal, allowing for both sequential and parallel execution of tasks.
State Machine represents the dynamic behavior of a system by modeling its states, transitions, and actions, operating sequentially in response to specific events or inputs.
Workflow :
A workflow represents a predefined sequence of tasks or activities aimed at achieving a specific goal. It encapsulates the steps required to complete a process from start to finish. Workflows are typically linear in nature, with each task depending on the completion of the previous one. They are commonly used in business process management, project management, and task automation scenarios. Workflows can also accommodate parallel execution of tasks, allowing multiple activities to progress simultaneously towards the ultimate goal.
State Machine :
A state machine, on the other hand, represents the dynamic behavior of a system by modeling its states, transitions, and actions. It is particularly suited for systems with complex, event-driven behavior where the system can be in different states at any given time. State machines are used to model reactive systems, control logic, and finite automation scenarios. Unlike workflows, state machines operate sequentially, with each state transition triggered by specific events or inputs. State machines are deterministic and do not inherently support parallel execution of states.
Workflow : Planning and Taking a Road Trip
Imagine planning and taking a road trip (workflow). It involves several steps often performed in a specific order:
Choose a destination: Decide where you want to go.
Pack luggage: Gather clothes, toiletries, and other necessities.
Prepare the car: Check oil, tire pressure, fill the gas tank, etc.
Map out the route: Plan stops for breaks, food, and overnight stays.
Drive to your destination: Follow the route, making necessary stops.
While some preparation tasks could happen in parallel (packing luggage while checking the car), the actual trip itself is primarily sequential. You can’t reach your destination without driving those miles.
State Machine: Driving a Car
The act of driving your car (state machine) involves various states and transitions:
Parked: The car is not running.
Ignition: The engine is turned on.
In Gear (Drive, Reverse, etc.): The car is moving.
Braking: The car is slowing down.
Stopped: The car is at a standstill, perhaps at a traffic light.
The car transitions between these states based on the driver’s input (turning the key, shifting gears, pressing pedals). It reacts to events (a red light), and the state changes are not strictly linear, unlike the step-by-step progression of planning the entire road trip.
Ok, with that, lets do a generic design for state machine in java
State machines are powerful tools in software engineering, providing a structured approach to modeling dynamic behavior in systems. Let’s delve into understanding state machines, designing them in Java, and exploring their real-world applications.
Concept :
A state machine is a mathematical model that represents the behavior of a system as a finite number of states, transitions between those states, and actions triggered by those transitions.
Components :
States : Represent distinct conditions or stages of the system.
Transitions : Define the movement between states triggered by specific events or inputs.
Actions : Correspond to tasks or behaviors associated with state transitions.
Designing a State Machine in Java
Basic principle :
If we are in state S and the event E occurs, we should perform action(s) A and make a transition to the state S′
S → E A, S'
S: Represents the current state of the system.
E: Represents the event that occurs while in state S.
A: Denotes the action(s) that should be performed in response to event E.
S′: Represents the resulting state after performing action A in response to event E.
Identify the states and events:
Carefully examine our system and recognize the distinct State and Eventthat trigger transitions between them.
Define the states:
Within our Java code, utilize the State class to construct the states our system will embody. As an example:
State signedOut = new State("signedOut");
State signedIn = new State("signedIn");
Define the events:
Similar to states, establish the events that will trigger transitions between states. We will come up w/ some abstract class say BaseEvent and extend it to create our own events. For instance:
class SignInEvent extends AbstractEvent { }
class SignOutEvent extends AbstractEvent { }
Construct the transitions:
Utilize the TransitionBuilder class to define the transitions between states triggered by events. Each transition should specify the source state, event, event handler (action to execute), and target state. For example:
Transition signIn = new TransitionBuilder()
.name("signIn")
.sourceState(signedOut)
.eventType(SignInEvent.class)
.eventHandler(new SignInHandler())
.targetState(signedIn)
.build();
Build the state machine:
FiniteStateMachine authStateMachine = new FiniteStateMachineBuilder(states, signedOut)
.registerTransition(signIn)
.build();