30 years went by since we published our book „Pattern-Oriented Software Architecture - A System of Patterns“, one year after the legendary Design Pattern book by the Gang of Four ignited a lot of enthusiasm within our community. While most patterns are now known by probably all developers and architects world-wide, I still see a lot of errors when software engineers are applying these patterns. Reason enough for addressing this topic in more detail.
Introduction: Beyond the Pattern Cookbook
Software patterns have revolutionized how we think about designing and building systems. From the seminal "Gang of Four" design patterns to modern architectural patterns like microservices and event sourcing, patterns provide a shared vocabulary and proven solutions to recurring problems. However, the gap between understanding a pattern in theory and applying it effectively in practice remains surprisingly wide. Many developers treat patterns like ingredients in a recipe, mechanically implementing them without considering whether they truly fit the problem at hand. This article explores the nuanced art of pattern application, moving beyond simple implementation to genuine integration.
The fundamental misconception about patterns is that they are building blocks or ready-made implementations that you can drop into your codebase. This view misses the essence of what patterns actually are. Patterns are not code libraries or frameworks. They are conceptual templates that describe relationships, responsibilities, and collaborations between components. When you apply a pattern, you are not implementing something new from scratch in most cases. Instead, you are recognizing that existing entities in your architecture can assume specific roles described by the pattern, and you are organizing these entities according to the pattern's structure.
Consider a real-world analogy. When an architect designs a building using the pattern of a courtyard house, they are not constructing a separate "courtyard component" to bolt onto an existing structure. Rather, they are organizing the rooms, walls, and open spaces according to a proven arrangement that balances privacy, light, and communal space. The same principle applies to software patterns. The components you already have or need for your application's functionality take on the roles defined by the pattern.
Rule One: Implement Patterns One at a Time
The first and perhaps most important rule of pattern application is to introduce patterns incrementally, one at a time. This might seem obvious, but the temptation to apply multiple patterns simultaneously is strong, especially when you are excited about a new architectural approach or when you are refactoring a legacy system.
Why is this incremental approach so critical? When you introduce a pattern, you are making a significant change to your system's structure. You are redistributing responsibilities, creating new relationships between components, and potentially changing how data flows through your application. Each of these changes has consequences that ripple through the system. If you introduce multiple patterns at once, these ripples interact in complex ways that become nearly impossible to reason about.
Let's consider a concrete example. Imagine you are building an e-commerce system and you decide that you need both the Observer pattern to notify various subsystems when orders are placed and the Strategy pattern to handle different payment methods. Both are reasonable choices. However, if you try to implement both simultaneously, you face several challenges. First, you cannot easily determine which pattern is causing problems if bugs emerge. Second, you cannot measure the impact of each pattern independently. Third, your team must learn and adapt to two new structural changes at once, which increases cognitive load and the likelihood of mistakes.
The correct approach is to introduce the Observer pattern first, for instance. You would identify which existing components play the role of the Subject (probably your Order class) and which play the role of Observers (perhaps an InventoryManager, a NotificationService, and an AnalyticsTracker). You would implement the notification mechanism, test it thoroughly, and ensure that the team understands how it works. Only after this pattern is stable and well-understood would you move on to implementing the Strategy pattern for payment processing.
This sequential approach has another benefit that is often overlooked. As you implement the first pattern, you gain insights into your system's actual needs and constraints. These insights might change your perspective on whether the second pattern is even necessary or whether a different pattern would be more appropriate. Patterns do not exist in isolation, and the introduction of one pattern can change the context in which you evaluate others.
Rule Two: Patterns Are Not Building Blocks But Role Assignments
This rule deserves deep exploration because it represents a fundamental shift in how many developers think about patterns. When you read a pattern description in a book like "Design Patterns: Elements of Reusable Object-Oriented Software," you see class diagrams with boxes and arrows. It is easy to interpret these diagrams as blueprints for new classes you should create. This interpretation is usually wrong.
Patterns describe roles and relationships. When you apply a pattern, you are mapping these roles to entities that already exist in your system or that you need for your application's domain logic. The pattern does not prescribe what these entities should do in terms of business logic. It prescribes how they should collaborate and what responsibilities they should have in terms of the pattern's intent.
Let's examine this with the Command pattern. The pattern describes four roles: Command, ConcreteCommand, Invoker, and Receiver. A naive implementation might lead you to create four new classes with these exact names. But this misses the point entirely. In a text editor application, your existing MenuItem class might naturally assume the Invoker role. Your Document class might be the Receiver. The specific editing operations you already need (InsertText, DeleteText, FormatParagraph) become your ConcreteCommands. You are not adding the Command pattern on top of your existing design. You are recognizing that your existing design can be organized according to the Command pattern's structure, which brings benefits like undo/redo functionality.
Here is a small code example to illustrate this principle:
// Before pattern awareness - domain-focused design
class TextEditor {
private Document document;
public void insertText(String text, int position) {
document.insert(text, position);
}
public void deleteText(int start, int end) {
document.delete(start, end);
}
}
// After recognizing Command pattern roles in existing entities
interface EditCommand {
void execute();
void undo();
}
class InsertTextCommand implements EditCommand {
private Document document;
private String text;
private int position;
public InsertTextCommand(Document doc, String text, int pos) {
this.document = doc;
this.text = text;
this.position = pos;
}
public void execute() {
document.insert(text, position);
}
public void undo() {
document.delete(position, position + text.length());
}
}
class TextEditor {
private Document document;
private Stack<EditCommand> history;
public void executeCommand(EditCommand cmd) {
cmd.execute();
history.push(cmd);
}
public void undo() {
if (!history.isEmpty()) {
history.pop().undo();
}
}
}
Notice that the Document class did not change. The TextEditor class evolved to assume the Invoker role, but its core responsibility (managing the editing process) remained the same. The pattern provided a structure for organizing operations that we already needed.
However, the rule acknowledges that sometimes patterns do require additional infrastructural components. These are components that exist solely to support the pattern's structure rather than to implement domain logic. In the Command pattern example, the Stack that holds the command history is an infrastructural component. It does not represent a business concept. It exists to enable the undo mechanism that the pattern provides.
The key insight is that these infrastructural components should be minimal. If you find yourself creating many new classes that do not represent domain concepts and exist only to satisfy a pattern's structure, you should question whether you are applying the pattern correctly or whether the pattern is appropriate for your situation.
Another fascinating aspect of this rule is that the same component can assume different roles in different patterns simultaneously. Your Document class might be the Receiver in the Command pattern while also being the Subject in an Observer pattern that notifies views when the document changes. This is not a problem. It is a natural consequence of the fact that patterns describe different aspects of a system's structure. A single component can participate in multiple structural relationships.
Rule Three: Architecture Patterns Before Design Patterns
This rule addresses the order in which you should consider and apply patterns. Architecture patterns operate at a higher level of abstraction than design patterns. They make strategic decisions about the overall structure of your system, such as how it is divided into layers, how components communicate, and how data flows through the system. Design patterns, in contrast, make tactical decisions about how specific components are structured and how they collaborate to achieve particular goals.
The reason to apply architecture patterns first is straightforward but profound. The architectural structure of your system constrains and enables the design patterns you can effectively use. If you make design-level decisions before establishing the architectural foundation, you might find that these design decisions conflict with the architectural pattern you later want to adopt.
Consider a system where you start by implementing a complex Observer pattern to handle communication between various components. You invest significant effort in creating a sophisticated event notification system with filtering, prioritization, and asynchronous delivery. Then you decide that your system should follow a layered architecture pattern where each layer can only depend on the layer directly below it. Suddenly, your Observer implementation becomes problematic because it allows components in different layers to communicate directly, violating the layered architecture's constraints.
If you had started with the architectural decision to use a layered pattern, you would have approached inter-component communication differently from the beginning. You might have used a different design pattern, such as a Mediator within each layer, or you might have designed your Observer implementation to respect layer boundaries.
Let's explore this with a more detailed example. Suppose you are building a web application for managing customer relationships. At the architecture level, you might consider several patterns: a traditional three-tier architecture, a hexagonal architecture (also known as ports and adapters), or a microservices architecture. Each of these choices has profound implications.
If you choose a three-tier architecture, you establish that your system has a presentation layer, a business logic layer, and a data access layer. This decision immediately influences which design patterns make sense. The Data Access Object pattern becomes relevant for the data access layer. The Model-View-Controller pattern might structure your presentation layer. The Service Layer pattern could organize your business logic.
If instead you choose a hexagonal architecture, you are making a different strategic decision. You are saying that your core business logic should be independent of external concerns like databases, user interfaces, and external services. This architectural choice makes the Adapter pattern central to your design because you need adapters to connect your core logic to these external systems. The Repository pattern becomes important for abstracting data access. The Dependency Inversion principle becomes a key design guideline.
The microservices architecture makes yet another set of design patterns relevant. The API Gateway pattern addresses how clients interact with multiple services. The Circuit Breaker pattern handles failures in service-to-service communication. The Saga pattern manages distributed transactions.
Notice that the architectural choice does not just influence which design patterns you use. It fundamentally changes the problems you need to solve and therefore the patterns that are relevant. This is why architecture patterns must come first. They set the context within which design patterns operate.
Here is a small code example showing how an architectural decision influences design pattern application:
// Layered Architecture - design patterns respect layer boundaries
// Presentation Layer
class CustomerController {
private CustomerService service;
public void updateCustomer(CustomerDTO dto) {
service.updateCustomer(dto);
}
}
// Business Logic Layer
class CustomerService {
private CustomerRepository repository;
public void updateCustomer(CustomerDTO dto) {
Customer customer = repository.findById(dto.getId());
customer.updateDetails(dto);
repository.save(customer);
}
}
// Data Access Layer
class CustomerRepository {
private DatabaseConnection db;
public Customer findById(String id) {
// Database access logic
}
}
// Hexagonal Architecture - same functionality, different structure
// Core Domain (no dependencies on external systems)
class Customer {
public void updateDetails(CustomerDetails details) {
// Business logic
}
}
class CustomerService {
private CustomerPort customerPort;
public void updateCustomer(String id, CustomerDetails details) {
Customer customer = customerPort.findById(id);
customer.updateDetails(details);
customerPort.save(customer);
}
}
// Port (interface defined by core domain)
interface CustomerPort {
Customer findById(String id);
void save(Customer customer);
}
// Adapter (implements port, depends on external system)
class DatabaseCustomerAdapter implements CustomerPort {
private DatabaseConnection db;
public Customer findById(String id) {
// Adapter logic to convert database records to domain objects
}
public void save(Customer customer) {
// Adapter logic to persist domain objects
}
}
The same business requirement (updating customer information) is handled differently depending on the architectural pattern. In the layered architecture, the CustomerService depends directly on CustomerRepository. In the hexagonal architecture, CustomerService depends on an interface (CustomerPort) that is defined by the core domain, and the database adapter implements this interface. This inversion of dependencies is a consequence of the architectural choice, and it influences how you apply design patterns throughout the system.
Rule Four: Examine Context, Forces, and Consequences
Pattern descriptions in formal pattern languages follow a specific structure. This structure is not arbitrary. It is designed to help you determine whether a pattern is appropriate for your situation. The most important sections to examine are the Context, Forces, and Consequences.
The Context describes the situation in which the pattern applies. It tells you what conditions must be present for the pattern to be relevant. Many developers skip this section and jump straight to the Solution, but this is a mistake. If your situation does not match the pattern's context, the pattern is unlikely to help you, no matter how elegant its solution appears.
The Forces describe the competing concerns or tensions that the pattern addresses. Forces are the "why" behind the pattern. They explain what makes the problem difficult and what trade-offs are involved. Understanding the forces helps you determine whether the pattern's trade-offs align with your priorities.
The Consequences describe what happens when you apply the pattern, both positive and negative. Every pattern has drawbacks. There is no silver bullet. The Consequences section makes these trade-offs explicit so you can make an informed decision.
Let's examine this with the Strategy pattern. The Context for Strategy is that you have a family of algorithms or behaviors that are interchangeable, and you want to select which one to use at runtime. If your situation does not involve interchangeable algorithms, Strategy is not the right pattern. For example, if you have a single algorithm that you want to optimize, Strategy does not help. You might need a different pattern or no pattern at all.
The Forces in Strategy include the need to avoid conditional logic that selects between algorithms, the desire to make it easy to add new algorithms without modifying existing code, and the requirement to encapsulate the details of each algorithm. If these forces are not present in your situation, Strategy might be overkill. For instance, if you only have two algorithms and they are unlikely to change, a simple if-statement might be more appropriate than the overhead of creating a strategy hierarchy.
The Consequences of Strategy include increased flexibility and extensibility, but also increased number of classes and potential runtime overhead from polymorphic dispatch. If your system has strict performance requirements and the algorithm selection is on a critical path, this overhead might be unacceptable.
Here is an example that illustrates examining forces:
// Situation: Calculating shipping costs for an e-commerce system
// Force 1: Multiple shipping methods (standard, express, overnight)
// Force 2: Shipping methods change based on business deals with carriers
// Force 3: Need to add new shipping methods without changing existing code
// Force 4: Each shipping method has complex calculation logic
// These forces align well with Strategy pattern
interface ShippingStrategy {
double calculateCost(Order order, Address destination);
}
class StandardShipping implements ShippingStrategy {
public double calculateCost(Order order, Address destination) {
double weight = order.getTotalWeight();
int distance = calculateDistance(destination);
return weight * 0.5 + distance * 0.1;
}
}
class ExpressShipping implements ShippingStrategy {
public double calculateCost(Order order, Address destination) {
double weight = order.getTotalWeight();
int distance = calculateDistance(destination);
return weight * 1.2 + distance * 0.3 + 15.0; // Base fee
}
}
class ShippingCalculator {
private ShippingStrategy strategy;
public void setStrategy(ShippingStrategy strategy) {
this.strategy = strategy;
}
public double calculateShippingCost(Order order, Address destination) {
return strategy.calculateCost(order, destination);
}
}
Now contrast this with a situation where the forces are different:
// Situation: Validating user input in a form
// Force 1: Only two validation modes (strict for production, lenient for testing)
// Force 2: Validation mode is set at application startup and never changes
// Force 3: Validation logic is simple (just different thresholds)
// These forces do NOT align well with Strategy pattern
// A simple configuration parameter is more appropriate
class UserValidator {
private boolean strictMode;
public UserValidator(boolean strictMode) {
this.strictMode = strictMode;
}
public boolean validateAge(int age) {
int minimumAge = strictMode ? 18 : 13;
return age >= minimumAge;
}
public boolean validateEmail(String email) {
if (strictMode) {
return email.matches("[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}");
} else {
return email.contains("@");
}
}
}
In the second example, introducing the Strategy pattern would add unnecessary complexity. We would create multiple classes (StrictValidationStrategy, LenientValidationStrategy) for behavior that is simple enough to handle with conditional logic. The forces that make Strategy valuable (frequent addition of new algorithms, complex encapsulated logic, runtime selection) are not present.
The lesson here is that you must carefully analyze whether your situation matches the pattern's context and whether the forces the pattern addresses are actually present in your problem. Pattern application is not about using as many patterns as possible. It is about using the right patterns in the right situations.
Rule Five: Avoid or Modify Problematic Patterns
Not all patterns age well. Some patterns that were considered best practices when they were first documented have proven to have significant drawbacks in modern software development. The most notorious example is the Singleton pattern.
The Singleton pattern ensures that a class has only one instance and provides a global point of access to it. On the surface, this seems useful for resources that should only exist once, such as a database connection pool or a configuration manager. However, Singleton introduces global state into your application, and global state is one of the most problematic aspects of software design.
Global state makes testing difficult because tests cannot easily isolate the component under test. If a class depends on a Singleton, every test that uses that class also depends on the Singleton's state. This creates coupling between tests and makes it hard to run tests in parallel or in isolation. Global state also makes code harder to understand because the dependencies are hidden. When you see a method call, you cannot tell from the signature whether it depends on global state.
Moreover, Singleton violates the Single Responsibility Principle. A Singleton class has two responsibilities: its domain logic and the logic for ensuring single instantiation. This mixing of concerns makes the class harder to change and harder to test.
Modern dependency injection frameworks provide a better solution to the problem Singleton tries to solve. Instead of making a class responsible for ensuring it has only one instance, you configure the dependency injection container to create only one instance and inject it wherever needed. This gives you the same single-instance behavior without the drawbacks of global state.
// Problematic Singleton approach
class DatabaseConnectionPool {
private static DatabaseConnectionPool instance;
private List<Connection> connections;
private DatabaseConnectionPool() {
connections = new ArrayList<>();
// Initialize pool
}
public static DatabaseConnectionPool getInstance() {
if (instance == null) {
instance = new DatabaseConnectionPool();
}
return instance;
}
public Connection getConnection() {
// Return a connection from the pool
}
}
class UserRepository {
public User findById(String id) {
Connection conn = DatabaseConnectionPool.getInstance().getConnection();
// Use connection
}
}
// Better approach using dependency injection
class DatabaseConnectionPool {
private List<Connection> connections;
public DatabaseConnectionPool() {
connections = new ArrayList<>();
// Initialize pool
}
public Connection getConnection() {
// Return a connection from the pool
}
}
class UserRepository {
private DatabaseConnectionPool pool;
public UserRepository(DatabaseConnectionPool pool) {
this.pool = pool;
}
public User findById(String id) {
Connection conn = pool.getConnection();
// Use connection
}
}
// In your dependency injection configuration
// container.registerSingleton(DatabaseConnectionPool.class);
// container.register(UserRepository.class);
The second approach is better because the dependency on DatabaseConnectionPool is explicit in UserRepository's constructor. Tests can easily provide a mock or stub pool. The DatabaseConnectionPool class has a single responsibility. And there is no global state.
Another example of a pattern that should be modified is the Factory pattern. The classic Factory pattern provides a create method that encapsulates the complexity of object creation. This is valuable, but it is incomplete. If creating an object is complex, destroying it is often equally complex. Objects might need to release resources, close connections, or perform cleanup operations. However, the Factory pattern as traditionally described does not include a destroy or release method.
In modern applications, especially those dealing with limited resources like file handles, network connections, or memory in resource-constrained environments, proper cleanup is as important as proper initialization. Therefore, when you apply the Factory pattern, you should extend it to include lifecycle management.
// Traditional Factory - incomplete
interface ShapeFactory {
Shape createShape(String type);
}
class ConcreteShapeFactory implements ShapeFactory {
public Shape createShape(String type) {
if (type.equals("circle")) {
return new Circle();
} else if (type.equals("rectangle")) {
return new Rectangle();
}
return null;
}
}
// Extended Factory with lifecycle management
interface ResourceFactory<T> {
T create(String type);
void destroy(T resource);
}
class DatabaseConnectionFactory implements ResourceFactory<DatabaseConnection> {
private Map<DatabaseConnection, ConnectionMetadata> activeConnections;
public DatabaseConnection create(String type) {
DatabaseConnection conn;
if (type.equals("mysql")) {
conn = new MySQLConnection();
} else if (type.equals("postgres")) {
conn = new PostgreSQLConnection();
} else {
return null;
}
conn.open();
activeConnections.put(conn, new ConnectionMetadata());
return conn;
}
public void destroy(DatabaseConnection conn) {
if (activeConnections.containsKey(conn)) {
conn.close();
conn.releaseResources();
activeConnections.remove(conn);
}
}
}
This extended version of the Factory pattern provides symmetric lifecycle management. The factory is responsible for both creating and destroying objects, which ensures that cleanup is as reliable and well-encapsulated as creation.
The broader lesson is that patterns are not sacred. They were created by developers who observed recurring solutions in their work. As our understanding of software design evolves and as new technologies and paradigms emerge, patterns must evolve too. You should feel empowered to modify patterns to fit your needs, as long as you preserve the core intent and clearly document your modifications.
Rule Six: Follow the Pattern's Microprocess
Many pattern descriptions include a section on implementation or a recommended process for applying the pattern. This microprocess is often overlooked, but it represents valuable guidance from the pattern's authors based on their experience.
The microprocess typically describes the steps you should follow to introduce the pattern into your system. It might specify which components to create first, how to migrate existing code to use the pattern, or what testing strategy to employ. Following this microprocess can help you avoid common pitfalls and ensure that you apply the pattern correctly.
For example, the Composite pattern's microprocess might recommend starting by defining the component interface, then implementing the leaf classes, and finally implementing the composite class. This order ensures that you have a clear understanding of the common interface before you tackle the more complex composite implementation.
The Visitor pattern has a particularly important microprocess because it is one of the more complex patterns. The microprocess typically recommends defining the visitor interface first, with visit methods for each concrete element type. Then you implement the element hierarchy with accept methods. Finally, you implement concrete visitors. This order helps you avoid the circular dependency issues that can arise if you try to implement elements and visitors simultaneously.
// Visitor pattern microprocess example
// Step 1: Define the visitor interface
interface ShapeVisitor {
void visitCircle(Circle circle);
void visitRectangle(Rectangle rectangle);
void visitTriangle(Triangle triangle);
}
// Step 2: Define the element interface with accept method
interface Shape {
void accept(ShapeVisitor visitor);
}
// Step 3: Implement concrete elements
class Circle implements Shape {
private double radius;
public void accept(ShapeVisitor visitor) {
visitor.visitCircle(this);
}
public double getRadius() {
return radius;
}
}
class Rectangle implements Shape {
private double width;
private double height;
public void accept(ShapeVisitor visitor) {
visitor.visitRectangle(this);
}
public double getWidth() {
return width;
}
public double getHeight() {
return height;
}
}
// Step 4: Implement concrete visitors
class AreaCalculator implements ShapeVisitor {
private double totalArea;
public void visitCircle(Circle circle) {
totalArea += Math.PI * circle.getRadius() * circle.getRadius();
}
public void visitRectangle(Rectangle rectangle) {
totalArea += rectangle.getWidth() * rectangle.getHeight();
}
public void visitTriangle(Triangle triangle) {
// Calculate triangle area
}
public double getTotalArea() {
return totalArea;
}
}
Following this microprocess ensures that at each step, you have a compilable, testable system. If you tried to implement elements and visitors simultaneously, you would have a period where neither compiles because they reference each other but neither is complete.
Some patterns have implicit microprocesses that are not explicitly documented but can be inferred from the pattern's structure. For instance, when applying the Decorator pattern, it is generally wise to start with the component interface and a concrete component, then add decorators one at a time. This incremental approach allows you to test each decorator independently before combining them.
The microprocess is particularly important when refactoring existing code to use a pattern. In this case, the microprocess should include steps to ensure that the system remains functional throughout the refactoring. You might introduce the pattern's structure alongside the existing implementation, gradually migrate functionality to the pattern-based design, and finally remove the old implementation. This approach minimizes risk and allows you to validate each step.
Rule Seven: Implementation Variations Are Valid
Pattern books typically show one or two implementations of each pattern. These implementations are examples, not prescriptions. There are often multiple valid ways to implement a pattern, and the best implementation depends on your specific context, programming language, and requirements.
The State pattern is an excellent example of this principle. The classic implementation represents each state as a separate class. The context object holds a reference to the current state object and delegates state-specific behavior to it. This is a clean, object-oriented implementation that makes it easy to add new states and ensures that state-specific logic is encapsulated.
// Classic State pattern implementation
interface State {
void handleRequest(Context context);
}
class ConcreteStateA implements State {
public void handleRequest(Context context) {
// Handle request in state A
// Possibly transition to another state
context.setState(new ConcreteStateB());
}
}
class ConcreteStateB implements State {
public void handleRequest(Context context) {
// Handle request in state B
context.setState(new ConcreteStateA());
}
}
class Context {
private State state;
public Context() {
state = new ConcreteStateA();
}
public void setState(State state) {
this.state = state;
}
public void request() {
state.handleRequest(this);
}
}
However, this is not the only way to implement the State pattern. An alternative implementation uses a state transition table. This approach represents states as enumerations or constants and stores the transition logic in a data structure rather than in code.
// Table-driven State pattern implementation
enum State {
STATE_A, STATE_B, STATE_C
}
enum Event {
EVENT_1, EVENT_2, EVENT_3
}
class StateTransition {
State nextState;
Runnable action;
StateTransition(State nextState, Runnable action) {
this.nextState = nextState;
this.action = action;
}
}
class StateMachine {
private State currentState;
private Map<State, Map<Event, StateTransition>> transitionTable;
public StateMachine() {
currentState = State.STATE_A;
initializeTransitionTable();
}
private void initializeTransitionTable() {
transitionTable = new HashMap<>();
Map<Event, StateTransition> stateATransitions = new HashMap<>();
stateATransitions.put(Event.EVENT_1,
new StateTransition(State.STATE_B, () -> System.out.println("A->B")));
stateATransitions.put(Event.EVENT_2,
new StateTransition(State.STATE_A, () -> System.out.println("A->A")));
transitionTable.put(State.STATE_A, stateATransitions);
Map<Event, StateTransition> stateBTransitions = new HashMap<>();
stateBTransitions.put(Event.EVENT_1,
new StateTransition(State.STATE_C, () -> System.out.println("B->C")));
transitionTable.put(State.STATE_B, stateBTransitions);
// More transitions...
}
public void handleEvent(Event event) {
Map<Event, StateTransition> transitions = transitionTable.get(currentState);
if (transitions != null && transitions.containsKey(event)) {
StateTransition transition = transitions.get(event);
transition.action.run();
currentState = transition.nextState;
}
}
}
The table-driven implementation has several advantages in certain contexts. It makes the state machine's structure explicit and visible in one place, which can be easier to understand and maintain when there are many states and transitions. It also makes it possible to load the state machine's structure from a configuration file or database, enabling runtime reconfiguration. In systems where state machines are defined by non-programmers (such as workflow designers), the table-driven approach is often more appropriate.
However, the table-driven implementation also has disadvantages. It is less type-safe because states and events are typically represented as enumerations rather than classes. It can be harder to implement complex state-specific behavior because the logic must fit into the action callbacks. And it may have slightly worse performance due to the hash table lookups.
The point is that both implementations are valid applications of the State pattern. They both achieve the pattern's intent: allowing an object to alter its behavior when its internal state changes. The choice between them depends on your specific requirements, such as the number of states, the complexity of state-specific behavior, the need for runtime reconfiguration, and performance constraints.
This principle applies to many patterns. The Observer pattern can be implemented with push or pull notification models. The Factory pattern can use reflection, configuration files, or hard-coded logic to determine which class to instantiate. The Adapter pattern can use inheritance or composition. None of these variations is inherently better than the others. The best choice depends on your context.
Rule Eight: Leverage Pattern Repositories and Domain-Specific Patterns
The Gang of Four design patterns and the classic architectural patterns are well-known, but they represent only a small fraction of the patterns that have been documented. There are patterns for specific domains like enterprise application architecture, concurrent programming, distributed systems, user interface design, and many others.
One of the most valuable resources for finding patterns is the Hillside Group's website at hillside.net, which hosts the Pattern Languages of Programs (PLoP) conference proceedings. These proceedings contain hundreds of patterns that address problems in specific domains. For example, if you are building a financial trading system, you might find patterns specific to that domain that are more relevant than general-purpose design patterns.
Domain-specific patterns are valuable because they encode solutions to problems that are unique to a particular field. The patterns for distributed systems, for instance, include Circuit Breaker, Bulkhead, and Saga patterns that address challenges like network failures, resource isolation, and distributed transactions. These patterns would not make sense in a single-process desktop application, but they are essential in a microservices architecture.
Similarly, patterns for user interface design address concerns like managing complex forms, handling asynchronous user input, and maintaining consistency between multiple views of the same data. The Model-View-ViewModel pattern, for example, is specifically designed for user interfaces with rich data binding requirements.
Modern AI-powered search tools can also help you discover patterns. If you describe your problem to an AI assistant, it might suggest relevant patterns that you were not aware of. However, you should always verify these suggestions by consulting authoritative sources. AI tools can sometimes conflate similar patterns or suggest patterns that do not actually exist in the literature.
When you find a pattern that seems relevant, take the time to read the complete pattern description, not just a summary. The full description includes the context, forces, and consequences that help you determine whether the pattern truly fits your situation. Many patterns have similar solutions but address different forces, and understanding these nuances is crucial for effective pattern application.
For example, the Proxy pattern and the Decorator pattern have similar structures (both involve wrapping an object), but they have different intents. Proxy controls access to an object, while Decorator adds responsibilities to an object. If you only look at the structure, you might use the wrong pattern. But if you examine the forces and consequences, you will understand which pattern addresses your actual problem.
Rule Nine: Document Pattern Decisions as Architecture Decision Records
When you introduce a pattern into your system, you are making an architecture decision. Like all architecture decisions, this should be documented in an Architecture Decision Record (ADR). An ADR captures the context of the decision, the decision itself, the alternatives you considered, and the consequences of the decision.
Documenting pattern decisions serves several purposes. First, it helps future developers (including your future self) understand why the pattern was chosen. Without this context, someone might look at the code and wonder why a particular structure was used, or they might try to simplify the code by removing the pattern, not realizing that it was introduced to address specific forces.
Second, documenting the decision helps you think through whether the pattern is truly appropriate. The act of writing down the context, forces, and alternatives forces you to articulate your reasoning, which often reveals gaps or assumptions you had not fully considered.
Third, ADRs provide a historical record of the system's evolution. When you need to make future decisions, you can review past ADRs to understand what was tried before and why. This prevents you from repeating mistakes or revisiting decisions that have already been thoroughly analyzed.
An ADR for a pattern decision might look like this:
ADR 015: Use Command Pattern for Undo/Redo in Document Editor
Context:
Our document editor needs to support undo and redo functionality for all editing
operations. Users expect to be able to undo at least the last 50 operations. The
editor supports various types of operations including text insertion, deletion,
formatting changes, and image insertion.
Decision:
We will use the Command pattern to implement undo/redo functionality. Each editing
operation will be encapsulated in a Command object that implements execute() and
undo() methods. The editor will maintain a history stack of executed commands.
Alternatives Considered:
1. Memento pattern: Store complete document snapshots for each operation. Rejected
because it would consume too much memory for large documents.
2. Event sourcing: Store all editing events and replay them to reconstruct document
state. Rejected because it would be too slow for large documents with long edit
histories.
3. Custom undo system: Implement operation-specific undo logic without a pattern.
Rejected because it would lead to scattered undo logic and make it hard to add
new operations.
Consequences:
Positive:
- Clean separation between operation execution and undo logic
- Easy to add new operations without modifying existing code
- Undo/redo logic is centralized and consistent
- Can implement additional features like operation history, macros, etc.
Negative:
- Increased number of classes (one per operation type)
- Some memory overhead for storing command history
- All operations must be designed to be reversible
Status: Accepted
Date: 2024-01-15
This ADR provides all the information someone needs to understand the decision. It explains what problem was being solved, why the Command pattern was chosen over alternatives, and what trade-offs were accepted. If someone later questions why the system uses the Command pattern, they can read this ADR and understand the reasoning.
ADRs should be stored in version control alongside the code. They should be written in a simple format like Markdown so they are easy to create and read. There are tools that can help manage ADRs, but a simple directory of numbered Markdown files is often sufficient.
Rule Ten: Refactor Homegrown Solutions to Patterns
It is common to encounter code where a developer has created a custom solution to a problem that would be better addressed by a well-known pattern. This often happens when developers are not familiar with the pattern catalog or when they implement a solution quickly without considering whether a pattern applies.
When you recognize that a homegrown solution is essentially a poor implementation of a known pattern, you should consider refactoring to use the pattern properly. This refactoring brings several benefits. First, it makes the code more understandable to other developers who are familiar with the pattern. Instead of having to reverse-engineer the custom solution, they can recognize the pattern and immediately understand the structure and intent.
Second, proper pattern implementation often handles edge cases and subtleties that the homegrown solution might miss. Patterns have been refined through repeated use and have accumulated wisdom about how to handle various scenarios.
Third, using a recognized pattern makes it easier to communicate about the code. You can say "this uses the Observer pattern" rather than having to explain a custom notification system.
Here is an example of a homegrown solution that should be refactored to a pattern:
// Homegrown solution - custom notification system
class OrderProcessor {
private InventorySystem inventory;
private EmailService emailService;
private AnalyticsTracker analytics;
public void processOrder(Order order) {
// Process the order
order.setStatus(OrderStatus.CONFIRMED);
// Manually notify all interested parties
inventory.updateStock(order.getItems());
emailService.sendConfirmation(order.getCustomer());
analytics.recordOrderPlaced(order);
}
}
// Refactored to use Observer pattern
interface OrderObserver {
void onOrderProcessed(Order order);
}
class InventorySystem implements OrderObserver {
public void onOrderProcessed(Order order) {
updateStock(order.getItems());
}
}
class EmailService implements OrderObserver {
public void onOrderProcessed(Order order) {
sendConfirmation(order.getCustomer());
}
}
class AnalyticsTracker implements OrderObserver {
public void onOrderProcessed(Order order) {
recordOrderPlaced(order);
}
}
class OrderProcessor {
private List<OrderObserver> observers = new ArrayList<>();
public void addObserver(OrderObserver observer) {
observers.add(observer);
}
public void processOrder(Order order) {
order.setStatus(OrderStatus.CONFIRMED);
notifyObservers(order);
}
private void notifyObservers(Order order) {
for (OrderObserver observer : observers) {
observer.onOrderProcessed(order);
}
}
}
The refactored version is better because OrderProcessor no longer needs to know about all the systems that care about order processing. New observers can be added without modifying OrderProcessor. The code is more modular and testable.
However, refactoring to a pattern should be done carefully. You should ensure that the pattern truly fits the problem and that the refactoring does not introduce unnecessary complexity. Sometimes a simple solution is better than a pattern-based solution, especially for small, stable systems.
Rule Eleven: Respect Domain Constraints
Some patterns are inappropriate in certain domains due to fundamental constraints. The most important constraint to consider is whether the pattern's characteristics align with your system's requirements, particularly around performance, determinism, safety, and resource usage.
Real-time embedded systems are a prime example where certain patterns must be avoided or heavily modified. The Observer pattern, as typically implemented, introduces non-determinism in the order and timing of notifications. In a real-time system where timing guarantees are critical, this non-determinism is unacceptable.
Consider an automotive control system where multiple components need to react to sensor readings. If you implement this with the Observer pattern, you cannot guarantee the order in which observers are notified or how long the notification process will take. If one observer's processing takes longer than expected, it delays all subsequent observers. This could cause the system to miss real-time deadlines, potentially leading to safety issues.
In such systems, a better approach is to hard-wire the connections between components with explicit, deterministic ordering. You might use a static scheduling approach where each component's execution time and order are known at compile time.
// Observer pattern - non-deterministic, unsuitable for hard real-time
class SensorReading {
private List<SensorObserver> observers = new ArrayList<>();
private double value;
public void addObserver(SensorObserver observer) {
observers.add(observer);
}
public void setValue(double newValue) {
value = newValue;
// Order and timing of notifications is not guaranteed
for (SensorObserver observer : observers) {
observer.onSensorUpdate(value);
}
}
}
// Hard-wired approach - deterministic, suitable for hard real-time
class SensorReading {
private double value;
private BrakeController brakeController;
private StabilityController stabilityController;
private DashboardDisplay dashboardDisplay;
public void setValue(double newValue) {
value = newValue;
// Explicit, deterministic order with known timing
// Critical safety components first
brakeController.updateSensorValue(value);
stabilityController.updateSensorValue(value);
// Non-critical components last
dashboardDisplay.updateSensorValue(value);
}
}
The hard-wired approach sacrifices flexibility for determinism and predictability. You cannot easily add new observers at runtime, but you gain the ability to reason about and guarantee the system's timing behavior.
Similarly, in systems with strict memory constraints, patterns that create many objects or use dynamic allocation might be inappropriate. The Flyweight pattern, which is designed to reduce memory usage by sharing common state, becomes more important in such systems. Conversely, patterns that create many small objects (like some implementations of the Interpreter pattern) might be unsuitable.
In safety-critical systems, patterns that hide control flow or make the system's behavior harder to analyze might be problematic. The Visitor pattern, for instance, uses double dispatch which can make it harder to trace execution flow. In a system that must be certified for safety, this added complexity might make verification more difficult.
The lesson is that patterns exist in a context, and that context includes the domain's constraints. You must always evaluate whether a pattern's characteristics align with your domain's requirements. When they do not, you should either avoid the pattern, modify it to meet the constraints, or use a domain-specific pattern that was designed with those constraints in mind.
Rule Twelve: Apply Patterns Orthogonally Across Similar Contexts
When you apply a pattern to solve a specific problem in one part of your system, you should consider applying the same pattern to similar problems elsewhere in the system. This principle of orthogonality ensures consistency and makes your system easier to understand and maintain.
Orthogonality in pattern application means that if a particular context and set of forces appear in multiple places in your system, you should use the same pattern to address them. This creates a consistent architectural vocabulary throughout your codebase. Developers who understand how one part of the system works can apply that understanding to other parts.
For example, suppose you are building a system that processes different types of financial transactions. You identify that payment processing involves selecting from multiple payment methods (credit card, bank transfer, digital wallet), and you decide to use the Strategy pattern to handle this variation. Later, you discover that refund processing also involves selecting from multiple refund methods (original payment method, store credit, check). The context and forces are similar to those in payment processing, so you should apply the Strategy pattern here as well.
// Payment processing using Strategy pattern
interface PaymentStrategy {
boolean processPayment(double amount, PaymentDetails details);
}
class CreditCardPayment implements PaymentStrategy {
public boolean processPayment(double amount, PaymentDetails details) {
// Process credit card payment
}
}
class BankTransferPayment implements PaymentStrategy {
public boolean processPayment(double amount, PaymentDetails details) {
// Process bank transfer
}
}
class PaymentProcessor {
private PaymentStrategy strategy;
public void setStrategy(PaymentStrategy strategy) {
this.strategy = strategy;
}
public boolean processPayment(double amount, PaymentDetails details) {
return strategy.processPayment(amount, details);
}
}
// Refund processing using the same Strategy pattern for consistency
interface RefundStrategy {
boolean processRefund(double amount, RefundDetails details);
}
class OriginalMethodRefund implements RefundStrategy {
public boolean processRefund(double amount, RefundDetails details) {
// Refund to original payment method
}
}
class StoreCreditRefund implements RefundStrategy {
public boolean processRefund(double amount, RefundDetails details) {
// Issue store credit
}
}
class RefundProcessor {
private RefundStrategy strategy;
public void setStrategy(RefundStrategy strategy) {
this.strategy = strategy;
}
public boolean processRefund(double amount, RefundDetails details) {
return strategy.processRefund(amount, details);
}
}
By using the Strategy pattern in both places, you create consistency. A developer who understands how payment processing works will immediately understand how refund processing works. The code follows a predictable structure, which reduces cognitive load and makes maintenance easier.
However, orthogonality does not mean blindly applying the same pattern everywhere. You must verify that the context and forces are truly similar. If the forces are different, using the same pattern might be inappropriate. For instance, if refund processing only had two methods and they were unlikely to change, using Strategy might be overkill, and a simple conditional might be more appropriate despite the similarity to payment processing.
The key is to look for genuine similarity in context and forces. When you find it, applying the same pattern creates valuable consistency. When the similarity is superficial, forcing the same pattern can create unnecessary complexity.
Orthogonality also applies across different types of patterns. If you use the Observer pattern to notify components when user data changes, you should consider using the same pattern when notifying components about order data changes, product data changes, or any other domain entity changes where the forces are similar. This creates a consistent event notification architecture throughout your system.
Rule Thirteen: Never Apply Patterns Without Purpose
Perhaps the most important rule of all is that applying patterns is not a goal in itself. Patterns are tools that help you solve specific problems. Using a pattern without a clear purpose is not just wasteful, it actively harms your codebase by adding unnecessary complexity.
This rule addresses a common anti-pattern in software development: pattern-driven design. Some developers, especially those who have recently learned about patterns, become enthusiastic about using them and start looking for opportunities to apply patterns everywhere. They might introduce the Factory pattern even when object creation is simple, use the Strategy pattern when there is only one algorithm, or apply the Decorator pattern when there is nothing to decorate. This enthusiasm, while well-intentioned, leads to over-engineered systems that are harder to understand and maintain than simpler alternatives.
The principle here is simple but profound: every design decision, including the decision to use a pattern, must be justified by a specific need or problem. Before you apply a pattern, you should be able to clearly articulate what problem the pattern solves, why simpler alternatives are insufficient, and what benefits the pattern provides that outweigh its costs.
Consider a simple example. You are building a configuration manager for your application. You have read about the Singleton pattern and think it might be appropriate because you only need one configuration manager. However, if you examine the actual requirements, you might find that there is no real problem to solve. Your dependency injection framework can easily ensure that only one instance is created. There is no need for the configuration manager to control its own instantiation. Applying Singleton here adds complexity (global state, harder testing) without solving any actual problem.
// Unnecessary Singleton - no real problem being solved
class ConfigurationManager {
private static ConfigurationManager instance;
private Properties config;
private ConfigurationManager() {
config = loadConfiguration();
}
public static ConfigurationManager getInstance() {
if (instance == null) {
instance = new ConfigurationManager();
}
return instance;
}
public String getProperty(String key) {
return config.getProperty(key);
}
}
// Simple alternative - let dependency injection handle lifecycle
class ConfigurationManager {
private Properties config;
public ConfigurationManager() {
config = loadConfiguration();
}
public String getProperty(String key) {
return config.getProperty(key);
}
}
The second version is simpler and more testable. It does not use a pattern, but it does not need to. The pattern would not solve any actual problem in this context.
This principle extends beyond patterns to all technologies and techniques. You should never use a technology just because it is new or popular. You should never adopt a technique just because someone recommended it. Every decision must be driven by actual requirements and constraints. If you cannot articulate a clear reason for a decision, you should not make it.
The challenge is that this requires discipline and humility. It is tempting to use sophisticated patterns and technologies because they make you feel like a skilled developer. It is hard to choose the simple solution when a more complex one seems more impressive. But the mark of a truly skilled developer is knowing when simplicity is better than sophistication.
A good practice is to start with the simplest solution that could possibly work. Only when you encounter a specific problem or limitation should you consider introducing a pattern. This approach, sometimes called YAGNI (You Aren't Gonna Need It), prevents over-engineering and ensures that every piece of complexity in your system is justified.
For example, you might start with a simple class that handles user authentication. As requirements evolve, you might discover that you need to support multiple authentication methods (password, OAuth, biometric). At that point, the Strategy pattern becomes justified because you have a real problem (multiple interchangeable algorithms) that the pattern solves. But if you had introduced Strategy from the beginning when you only had password authentication, you would have added unnecessary complexity.
// Start simple - single authentication method
class AuthenticationService {
public boolean authenticate(String username, String password) {
// Verify password
}
}
// Evolve to pattern when requirements justify it
interface AuthenticationStrategy {
boolean authenticate(Credentials credentials);
}
class PasswordAuthentication implements AuthenticationStrategy {
public boolean authenticate(Credentials credentials) {
// Verify password
}
}
class OAuthAuthentication implements AuthenticationStrategy {
public boolean authenticate(Credentials credentials) {
// Verify OAuth token
}
}
class AuthenticationService {
private AuthenticationStrategy strategy;
public void setStrategy(AuthenticationStrategy strategy) {
this.strategy = strategy;
}
public boolean authenticate(Credentials credentials) {
return strategy.authenticate(credentials);
}
}
The evolution from simple to pattern-based design is driven by actual requirements, not by a desire to use patterns for their own sake.
Additional Rules and Considerations
Beyond the thirteen rules discussed above, there are several additional principles that guide effective pattern application.
Rule Fourteen: Understand Pattern Relationships and Combinations
Patterns do not exist in isolation. Many patterns work together or can be combined to solve more complex problems. Understanding these relationships helps you apply patterns more effectively.
Some patterns are alternatives to each other. They solve similar problems but make different trade-offs. For example, Strategy and State both use composition to change behavior, but Strategy focuses on interchangeable algorithms while State focuses on state-dependent behavior. Knowing when to use which pattern requires understanding these subtle differences.
Other patterns are complementary and are often used together. The Composite pattern is frequently combined with the Visitor pattern. Composite creates a tree structure of objects, and Visitor provides a way to perform operations on all elements of the tree without adding those operations to the element classes themselves. The Abstract Factory pattern is often combined with the Singleton pattern, though as we discussed earlier, Singleton should generally be avoided in favor of dependency injection.
Some patterns are refinements of other patterns. The Proxy pattern is a specialized form of the Decorator pattern. Both wrap an object, but Proxy controls access while Decorator adds functionality. Understanding this relationship helps you choose the right pattern and implement it correctly.
// Composite and Visitor working together
interface FileSystemElement {
void accept(FileSystemVisitor visitor);
}
class File implements FileSystemElement {
private String name;
private long size;
public void accept(FileSystemVisitor visitor) {
visitor.visitFile(this);
}
public long getSize() {
return size;
}
}
class Directory implements FileSystemElement {
private String name;
private List<FileSystemElement> children = new ArrayList<>();
public void accept(FileSystemVisitor visitor) {
visitor.visitDirectory(this);
for (FileSystemElement child : children) {
child.accept(visitor);
}
}
public void addChild(FileSystemElement element) {
children.add(element);
}
}
interface FileSystemVisitor {
void visitFile(File file);
void visitDirectory(Directory directory);
}
class SizeCalculator implements FileSystemVisitor {
private long totalSize = 0;
public void visitFile(File file) {
totalSize += file.getSize();
}
public void visitDirectory(Directory directory) {
// Directory size is sum of its children
}
public long getTotalSize() {
return totalSize;
}
}
In this example, Composite provides the tree structure, and Visitor provides a way to calculate the total size without adding a calculateSize method to every FileSystemElement class. The two patterns work together seamlessly.
Rule Fifteen: Consider Language and Platform Features
Different programming languages and platforms provide different features that can affect how you implement patterns or whether you need them at all. A pattern that is essential in one language might be unnecessary in another.
For example, the Iterator pattern is fundamental in languages like C++ and Java that do not have built-in iteration constructs. However, in Python, the language has built-in support for iteration through the iterator protocol and the for-in syntax. You still use the Iterator pattern conceptually, but you do not need to implement it manually because the language provides it.
Similarly, the Strategy pattern is often implemented using function pointers or lambda expressions in languages that support first-class functions. This can be simpler than creating a class hierarchy.
// Strategy pattern in Java - requires class hierarchy
interface SortStrategy {
void sort(int[] array);
}
class QuickSort implements SortStrategy {
public void sort(int[] array) {
// QuickSort implementation
}
}
class MergeSort implements SortStrategy {
public void sort(int[] array) {
// MergeSort implementation
}
}
class Sorter {
private SortStrategy strategy;
public void setStrategy(SortStrategy strategy) {
this.strategy = strategy;
}
public void sort(int[] array) {
strategy.sort(array);
}
}
In a language with first-class functions, this can be simpler. The Python version achieves the same goal with less code because the language supports passing functions as arguments. The pattern is still there conceptually, but the implementation is simpler.
Modern languages also provide features like generics, reflection, and metaprogramming that can affect pattern implementation. The Template Method pattern, for instance, can sometimes be replaced with higher-order functions or generics. The Factory pattern can use reflection to instantiate classes dynamically.
The point is that you should consider your language's features when applying patterns. Do not blindly follow implementations from pattern books that were written for different languages. Adapt the pattern to take advantage of your language's strengths.
Rule Sixteen: Test Pattern Implementations Thoroughly
When you introduce a pattern into your system, you are adding complexity. This complexity must be justified by the benefits the pattern provides, and you must ensure that the pattern is implemented correctly. Thorough testing is essential.
Testing pattern implementations requires testing both the individual components and their interactions. For the Observer pattern, you need to test that observers are notified correctly, that they can be added and removed, and that the notification order is correct if order matters. You also need to test edge cases like what happens if an observer throws an exception during notification.
For the State pattern, you need to test all state transitions, including invalid transitions. You need to verify that state-specific behavior is correct in each state. You need to test what happens if a state transition occurs during the handling of an event.
Some patterns introduce concurrency concerns that require careful testing. If your Observer pattern allows observers to be added or removed during notification, you need to test for race conditions. If your Singleton pattern is used in a multi-threaded environment, you need to test that only one instance is created even under concurrent access.
Testing also helps you verify that the pattern is providing the benefits you expected. If you introduced the Strategy pattern to make it easy to add new algorithms, write a test that adds a new algorithm and verify that it works without modifying existing code. If you introduced the Command pattern to support undo/redo, write tests that exercise various undo/redo scenarios.
Rule Seventeen: Monitor Pattern Usage Over Time
After you introduce a pattern, you should monitor how it is used over time. Patterns can become obsolete as requirements change. A pattern that was appropriate when it was introduced might no longer be the best solution as the system evolves.
For example, you might have introduced the Strategy pattern to handle three different algorithms. Over time, two of the algorithms might become obsolete, leaving only one. At that point, the Strategy pattern is adding complexity without providing benefit, and you should consider simplifying the design.
Conversely, you might find that a pattern you introduced is being used in ways you did not anticipate. This could indicate that the pattern is more valuable than you thought, or it could indicate that the pattern is being misused. Either way, monitoring usage helps you make informed decisions about whether to keep, modify, or remove the pattern.
Code reviews and architecture reviews are good opportunities to monitor pattern usage. When reviewing code, look for places where patterns are being applied and ask whether they are still appropriate. When conducting architecture reviews, examine whether the patterns you have introduced are achieving their intended goals.
Conclusion: The Wisdom of Pattern Application
Applying software patterns effectively is both an art and a science. It requires deep understanding of the patterns themselves, careful analysis of your specific context, and the wisdom to know when to apply a pattern, when to modify it, and when to avoid it altogether.
The rules we have explored provide a framework for making these decisions. Implement patterns one at a time to manage complexity. Recognize that patterns describe roles and relationships, not building blocks. Apply architecture patterns before design patterns to establish the strategic foundation. Examine the context, forces, and consequences to determine whether a pattern fits. Avoid or modify patterns that have known problems. Follow the pattern's microprocess for implementation. Understand that there are multiple valid implementations of most patterns. Leverage pattern repositories to find domain-specific solutions. Document pattern decisions in ADRs. Refactor homegrown solutions to use patterns when appropriate. Respect domain constraints that might make certain patterns unsuitable. Apply patterns orthogonally across similar contexts to create consistency. Never apply a pattern without a clear purpose that justifies its complexity.
Beyond these core rules, remember that patterns exist in a web of relationships. They combine, refine, and complement each other. Your programming language and platform affect how you implement patterns. Testing ensures correctness. Monitoring ensures continued relevance.
Most importantly, remember that patterns are tools, not goals. The goal is to build software that meets its requirements, is maintainable, and can evolve over time. Patterns help achieve this goal when applied thoughtfully. But a system with no patterns that meets its requirements is better than a system full of patterns that does not.
The journey to mastering pattern application is ongoing. Each system you build teaches you something new about when patterns help and when they hinder. Each pattern you apply deepens your understanding of software design. Over time, you develop an intuition for pattern application that goes beyond rules and guidelines. You begin to see patterns not as separate entities but as facets of good design that emerge naturally when you focus on creating clean, modular, maintainable systems.
This is the ultimate goal: not to apply patterns mechanically, but to internalize the principles they represent so that good design becomes second nature. When you reach this point, you will find that you are using patterns without consciously thinking about them, and you will know instinctively when a pattern helps and when it does not. This is the wisdom of pattern application, and it is the mark of a mature software architect.
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