Refactoring Java Code A Guide To Enhancing Modularity With Design Patterns

by StackCamp Team 75 views

Hey guys! Let's dive into how we can refactor some Java code to make it super modular using design patterns. This is based on an assignment where we’re learning to apply these patterns correctly. The goal here is to take some code that's a bit messy and turn it into something clean, easy to maintain, and scalable. Let’s get started!

Issue Analysis

We've found some critical deficiencies in the structure and design of our source code. These issues really impact the readability, maintainability, and scalability of the program. Think of it like this: if your code is a house, right now it's got rooms in weird places, the foundation isn't great, and adding a new room would be a total nightmare. We're here to fix that!

Root Causes

Let's break down the main problems we’ve got:

  1. Multiple Classes in a Single File:

One of the first things we noticed is that we've got the main, ID, and fakeID classes all crammed into the same main.java file. This is a big no-no in the Java world. It's like trying to fit an entire apartment building into a single room! When you bundle multiple classes into a single file, it becomes a real headache to navigate and maintain your code. Imagine trying to find a specific piece of information in a giant, disorganized pile of papers—that's what working with multiple classes in one file feels like. Each class should have its own .java file to keep things tidy and organized. This not only makes it easier to find what you're looking for but also promotes code reuse. If each class is in its own file, it's simpler to use it in other parts of your application or even in different projects altogether.

Plus, having separate files aligns with standard Java conventions. It's the way things are supposed to be done, so following this practice makes your code more accessible to other developers. When someone new joins your project, they'll be able to jump in and understand the structure much more quickly if it follows these established norms.

So, breaking up those classes into their own files isn't just about aesthetics; it's about making your codebase more manageable, reusable, and developer-friendly. Think of it as giving each class its own home, where it can be easily found and maintained. This is a crucial step in ensuring that your code remains clean and efficient as your project grows and evolves.

  1. Tight Coupling in Object Creation:

Right now, our main method is directly creating instances of ID and FakeID using the new keyword. This is what we call tight coupling, and it's like having the walls of your house glued together—hard to make any changes without messing everything up. When the main method is in charge of creating these objects directly, it becomes heavily reliant on the specific details of those classes. This centralization of object creation logic might seem convenient at first, but it makes your code brittle and resistant to change. Every time you need to create an ID or FakeID, you're locked into the specific way the main method does it.

This tight coupling makes it harder to extend your system in the future. What if you want to add a new type of ID? You'd have to go into the main method and modify it directly, which can introduce bugs and make your code harder to test. This violates the Open/Closed Principle, which states that software entities (classes, modules, functions, etc.) should be open for extension but closed for modification. In other words, you should be able to add new functionality without altering existing code.

By decoupling the object creation process, we can make our code much more flexible and adaptable. We want to get to a point where we can easily add new types of identities or change the way existing ones are created without having to touch the main method. This is where design patterns like the Factory Method come into play, allowing us to delegate the responsibility of object creation to specialized classes, making our code more robust and easier to maintain.

  1. Rigid Centralization of Data Capture and Validation in main Method:

Currently, all the heavy lifting for data capture and validation—think name, age, gender, address, and so on—is happening right inside the main method. This is like having one giant room in your house where you cook, sleep, and work—it just doesn't make sense! This approach mixes user interaction logic (getting input from the user) with business logic (validating that input), which is a big no-no in software design. It violates the Single Responsibility Principle, which says that each class or method should have only one reason to change.

When you jam all this logic into one place, it becomes incredibly difficult to modify or extend the input flow without risking unintended consequences. Imagine you want to add a new field to the ID—you'd have to wade through all the existing code in the main method, which is a recipe for bugs. Or what if you want to change how a particular field is validated? Again, you're stuck modifying this central hub of logic.

This centralization makes the code harder to test, too. Because everything is intertwined, it's tough to isolate specific parts of the data capture and validation process to ensure they're working correctly. We need to decouple these concerns, breaking them up into smaller, more manageable pieces. This will not only make the code cleaner and easier to understand but also make it much more flexible and maintainable in the long run. We'll explore how patterns like the Chain of Responsibility can help us with this.

Proposed Solution

Okay, so we've identified the problems. Now, let's talk about how we can fix them! We’re going to refactor in two structural phases, with an extra improvement for the input flow. Think of it like renovating that messy house we talked about earlier, but instead of drywall and paint, we’re using design patterns and clean code!

1. Structural Refactoring (Immediate Action):

  • Separate each class (ID and FakeID) into its own .java file (ID.java and FakeID.java).

    *This is our first and most immediate step. It's like decluttering a room by putting everything in its proper place. By moving each class into its own file, we're aligning our project with Java best practices. This simple change immediately improves modularity—think of modularity as having well-defined rooms in your house, each with its own purpose. When each class has its own file, it's much easier to find, understand, and work with.

    This separation isn't just about cleanliness; it's also about making your code more reusable. If you ever need to use the ID or FakeID class in another part of your application, having them in their own files makes it a breeze. No more copy-pasting large chunks of code—just import the class and you're good to go.*

    Moreover, this refactoring makes your codebase more accessible to other developers. Standard Java projects have this structure for a reason: it's easy to navigate and understand. When someone new joins your project, they'll immediately know where to find the ID and FakeID classes, saving them time and frustration. So, this is a quick win that lays the groundwork for more advanced refactoring.

2. Implementation of the Factory Method Pattern:

  • To resolve the coupling issue, apply the Factory Method design pattern, which involves:
    • Defining a common interface Identity, implemented by both Id and FakeId classes.
    • Creating an abstract class IdentityFactory that declares a factory method such as createIdentity().
    • Implementing concrete factories (OriginalIdentityFactory, FakeIdentityFactory) that return the appropriate identity instances.
  • Once applied, the main method will delegate identity creation to these factories, eliminating direct dependency on specific classes.

Image

Let's break this down piece by piece:

  • The Problem of Tight Coupling:

    As we discussed earlier, our main method is currently responsible for creating instances of ID and FakeID directly using the new keyword. This creates a tight dependency, making it difficult to swap out or extend these classes without modifying the main method. Imagine if you wanted to add a SuperFakeID class—you'd have to go into main and change the object creation logic. That's not ideal.

  • Enter the Factory Method Pattern:

    The Factory Method pattern is like having a specialized workshop that knows exactly how to build the objects you need. Instead of the main method doing the construction itself, it delegates that responsibility to a factory. This pattern is all about decoupling—separating the responsibility of object creation from the code that uses those objects.

  • How It Works:

    1. Common Interface (Identity):

      First, we define an interface called Identity. This interface acts as a blueprint for all our identity classes, including Id and FakeId. It specifies the common methods that all identities must have, like getName(), getAge(), and so on. Think of it as the basic structure that all types of IDs must follow.

    2. Abstract Factory (IdentityFactory):

      Next, we create an abstract class called IdentityFactory. This is where the magic happens! It declares an abstract method, typically named createIdentity(), which is responsible for creating the actual Identity object. The key here is that it doesn't specify how the object is created—it just says that it will be created. This is like the foreman of the workshop, knowing the job needs to be done but not doing the work themselves.

    3. Concrete Factories (OriginalIdentityFactory, FakeIdentityFactory):

      Now, we get to the specific workshops. We create concrete factory classes, such as OriginalIdentityFactory and FakeIdentityFactory. Each of these classes extends IdentityFactory and implements the createIdentity() method to return a specific type of Identity. The OriginalIdentityFactory knows how to create an ID object, while the FakeIdentityFactory knows how to create a FakeID object. These are the skilled craftsmen in our workshop, each specializing in their own type of ID.

  • The Result: Decoupled and Flexible Code:

    With the Factory Method pattern in place, the main method no longer needs to know the details of how ID and FakeID objects are created. It simply asks the appropriate factory to create the object. This means we can add new types of identities, like our SuperFakeID, by creating a new factory class without ever touching the main method. We've achieved the Open/Closed Principle—we can extend the system without modifying existing code.

    This pattern also makes our code more testable. We can easily swap out different factories in our tests to simulate different scenarios, ensuring that our object creation logic is robust and reliable. So, the Factory Method pattern is a powerful tool for creating flexible, maintainable code. It's like having a well-organized workshop where each craftsman knows their job, making it easy to build whatever you need!

import java.time.LocalDate;

public interface Identity {
    public String getName();
    public int getAge();
    public char getSex();
    public double getHeight();
    public String getAddress();
    public LocalDate getBirthDate();
    public LocalDate getExpirationDate();
}

public abstract class IdentityFactory {
    public abstract Identity createIdentity();
}

import java.time.LocalDate;
import java.time.Period;
import java.util.InputMismatchException;
import java.util.Scanner;

public class OriginalIdentityFactory extends IdentityFactory{

    @Override
    public Identity createIdentity() {

        ID newID = new ID();
		Scanner scan = new Scanner(System.in);
		
		System.out.print("Name: ");
		newID.name = scan.nextLine();
		
		int bdaymonth = 0, bdayDay = 0, bdayYear = 0;
		LocalDate today = LocalDate.now();
		System.out.println("Birhtdate-----");
		
        //All the logic to create an ID with inputs

        return newID;
    }
    
}

public class FakeIdentityFactory extends IdentityFactory {
    private Identity originalData;

    public FakeIdentityFactory(Identity originalData){
        this.originalData = originalData;
    }

    @Override
    public Identity createIdentity() {
        return new FakeID(
                    originalData.getName(),
                    originalData.getAge(),
                    originalData.getSex(),
                    originalData.getBirthDate(),
                    originalData.getExpirationDate(),
                    originalData.getHeight(),
                    originalData.getAddress());
    }
    
}

public class main {
	
	public static void main(String[] args) {

		System.out.println("ENTER THE INFORMATION CURRENTLY ON YOUR ID\n");
		System.out.println("Fake ID Generator");
		
		IdentityFactory originalFactory = new OriginalIdentityFactory();
		Identity originalID = originalFactory.createIdentity();
		
		System.out.println("\n\nHere is your Original ID:\n");
        System.out.println(originalID);

		IdentityFactory fakeFactory = new FakeIdentityFactory(originalID);
		Identity fakeID = fakeFactory.createIdentity();

		System.out.println("\n\nHere is your fake ID:\n");
        System.out.println(fakeID);
		
	}	
}

3. Implementation of the Chain of Responsibility Pattern within OriginalIdentityFactory:

  • After moving the construction logic from main to OriginalIdentityFactory, it was identified that this class contains rigid and centralized logic for input data capture.
  • To address this, apply the Chain of Responsibility pattern:
    • Each step (name, age, gender, address, etc.) is handled by a specialized handler.
    • Each handler is responsible for:
      • Requesting a specific piece of data from the user.
      • Validating it if needed.
      • Assigning it to the Id object.
      • Passing control to the next handler in the chain.
  • OriginalIdentityFactory will only be responsible for initializing and triggering the chain, staying free from specific input logic.

Image

Let's dive deeper into how we can make our input process even more modular and flexible with the Chain of Responsibility pattern. This pattern is perfect for handling a series of tasks, each with its own logic, in a structured and organized way. It's like an assembly line where each station adds a specific part to the product.

  • The Problem of Centralized Input Logic:

    As you might recall, after using the Factory Method pattern, we moved the object creation logic from our main method to the OriginalIdentityFactory. While this was a great step, we noticed that OriginalIdentityFactory was now burdened with the rigid, centralized logic for capturing input data—things like name, age, gender, and so on. This means that OriginalIdentityFactory was handling too many responsibilities, making it harder to maintain and extend. It's like having one person on the assembly line doing every single step, which is inefficient and prone to errors.

  • The Chain of Responsibility to the Rescue:

    The Chain of Responsibility pattern helps us distribute the responsibility for handling different parts of a request to a chain of handlers. Each handler decides whether to handle the request or pass it on to the next handler in the chain. This pattern is ideal for situations where you have a series of steps or tasks that need to be performed in a specific order, but you want to avoid tightly coupling the steps together.

  • How It Works:

    1. Specialized Handlers:

      First, we break down the input process into individual steps, such as getting the name, birth date, gender, etc. For each step, we create a specialized handler class. So, we'll have a NameHandler, a BirthDateHandler, a GenderHandler, and so on. Each handler is responsible for one specific piece of data. Think of these as the specialized stations on our assembly line.

    2. The Handler Interface (IdentityHandler):

      We define an abstract class or interface, often called IdentityHandler, that all our handlers will implement. This interface typically includes a method to handle the request (like handle()) and a way to set the next handler in the chain (like setNext()). The handle() method is where the handler does its work—requesting the data, validating it if necessary, and assigning it to the Id object.

    3. Linking the Chain:

      In our OriginalIdentityFactory, we create instances of our handlers and link them together in the desired order. We use the setNext() method to create a chain, like this: nameHandler.setNext(birthDateHandler); birthDateHandler.setNext(genderHandler);, and so on. This chain defines the order in which the input data will be collected.

    4. Triggering the Chain:

      The OriginalIdentityFactory is now responsible for initializing the chain and triggering it. It simply calls the handle() method on the first handler in the chain, which starts the process. Each handler in the chain will then decide whether to handle the request or pass it on to the next handler.

  • The Benefits: Decoupling and Flexibility:

    With the Chain of Responsibility pattern, each handler has a single responsibility: handling one specific piece of input data. This makes the code cleaner and easier to understand. It also makes it easier to modify or extend the input process. If we need to add a new field to the ID, we simply create a new handler and add it to the chain—no need to modify the existing handlers.

    This pattern also promotes the Single Responsibility Principle, as each handler has a clear, focused purpose. And it makes our code more testable, as we can test each handler in isolation to ensure it's working correctly. Think of it like having a well-oiled assembly line where each station performs its task efficiently and reliably.

    In summary, the Chain of Responsibility pattern is a fantastic way to manage complex input processes, making our code more modular, maintainable, and flexible. It allows us to handle each step of the process with its own specialized logic, without creating a tangled mess of code.

import java.util.Scanner;

public abstract class IdentityHandler {
    protected IdentityHandler next;

    public void setNext(IdentityHandler next){
        this.next = next;
    }

    public void handle(ID id, Scanner scan){
        requestData(id, scan);
        if(next != null){
            next.handle(id, scan);
        }
    }

    protected abstract void requestData(ID id, Scanner scan);
}

import java.util.Scanner;

public class NameHandler extends IdentityHandler {

    @Override
    protected void requestData(ID id, Scanner scan) {
        System.out.print("Name: ");
		id.name = scan.nextLine();
    }

}

import java.time.LocalDate;
import java.util.InputMismatchException;
import java.util.Scanner;

public class BirthDateHandler extends IdentityHandler{

    @Override
    protected void requestData(ID id, Scanner scan) {
        int bdaymonth = 0, bdayDay = 0, bdayYear = 0;
		System.out.println("Birhtdate-----");
		
		while(true) {
			try {
				System.out.print("Month (01-12) : ");
				bdaymonth = scan.nextInt();
				
				if(bdaymonth > 12 || bdaymonth < 1) {
					throw new Exception("Invalid month entry");
				}
				break;
			}catch(InputMismatchException f) {
				System.out.println("Input Mismatch!");
			}catch(Exception e) {
				System.out.println(e);
			}
		}
		
		while(true) {
			try {
				System.out.print("Day (01-31): ");
				bdayDay = scan.nextInt();
				
				if(bdayDay > 31 || bdayDay < 1) {
					throw new Exception("Invalid day entry");
				}
				break;
			}catch(InputMismatchException f) {
				System.out.println("Input Mismatch!");
			}catch(Exception e) {
				System.out.println(e);
			}
		}

		while(true) {
			try {
				System.out.print("Year (####) : ");
				bdayYear = scan.nextInt();
				break;
			}catch(InputMismatchException f) {
					System.out.println("Input Mismatch!");
			}
		}
		
		id.birthdate = LocalDate.of(bdayYear, bdaymonth, bdayDay);
    }

}

import java.util.Scanner;

public class OriginalIdentityFactory extends IdentityFactory{

    @Override
    public Identity createIdentity() {

        ID newID = new ID();
		Scanner scan = new Scanner(System.in);
		
		IdentityHandler name = new NameHandler();
        IdentityHandler birth = new BirthDateHandler();
        IdentityHandler sex = new SexHandler();
        IdentityHandler height = new HeightHandler();
        IdentityHandler address = new AddressHandler();
        IdentityHandler exp = new ExpirationDateHandler();

        name.setNext(birth);
        birth.setNext(sex);
        sex.setNext(height);
        height.setNext(address);
        address.setNext(exp);
		
		name.handle(newID, scan);	
		
        return newID;
    }
    
}

Implementation Benefits

Alright, so we've put in the work, refactored our code, and applied some cool design patterns. Now, let's talk about the benefits! What do we get out of all this? Well, a lot, actually. Think of it as the difference between a messy, cramped room and a well-organized, spacious home. Here's a rundown of the perks:

  • Modularity and Readability

    First off, our code is now much more modular. This means it's broken down into smaller, more manageable pieces, like the classes and handlers we've created. This separation of classes and responsibilities makes the code way easier to read and navigate. It's like having well-labeled drawers and shelves instead of a giant pile of stuff. When your code is modular, it's also easier to understand, because each part has a clear, focused purpose. This makes it simpler to debug, modify, and extend. No more wading through a sea of tangled code!

  • Maintainability and Scalability

    This is a big one. By using both the Factory Method and Chain of Responsibility patterns, we've made our code much easier to maintain and scale. Maintainability means that it's easier to fix bugs and make small changes without breaking everything. Scalability means that we can add new features or handle more data without major headaches. These patterns allow for future system extensions, like adding new identity types or validations, without altering the client or the main flow. It's like having a house with a flexible design that can easily accommodate new rooms or a growing family.

  • Adherence to SOLID Principles

    Last but not least, our solution promotes high-quality code by complying with the SOLID principles. These are five key principles of object-oriented design that, when followed, make your code more robust, flexible, and maintainable. Let's see how our refactoring stacks up:

    1. Single Responsibility Principle:

      Each class or handler has a clear, focused purpose. The NameHandler handles names, the BirthDateHandler handles birth dates, and so on. This makes each component easier to understand and modify independently.

    2. Open/Closed Principle:

      New types or logic can be added without modifying existing classes. We can add a new type of ID or a new validation rule by creating a new factory or handler, without touching the existing code.

    3. Dependency Inversion Principle:

      The client (e.g., the main method) depends on abstractions (like the IdentityFactory interface), not concrete implementations (like the OriginalIdentityFactory class). This reduces coupling and makes the code more flexible. It's like depending on a contract rather than a specific vendor—you can switch vendors without breaking the contract.

By following the SOLID principles, we've created a codebase that's not only cleaner and easier to understand but also more adaptable to future changes. It's like having a solid foundation for our house, ensuring that it can withstand the test of time. So, there you have it! Refactoring with design patterns isn't just about making the code look pretty; it's about building a system that's robust, maintainable, and ready for whatever the future holds.