What is the dependency inversion principle and why is it important?
What Is It?
The books Agile Software Development, Principles, Patterns, and Practices and Agile Principles, Patterns, and Practices in C# are the best resources for fully understanding the original goals and motivations behind the Dependency Inversion Principle. The article "The Dependency Inversion Principle" is also a good resource, but due to the fact that it is a condensed version of a draft which eventually made its way into the previously mentioned books, it leaves out some important discussion on the concept of a package and interface ownership which are key to distinguishing this principle from the more general advise to "program to an interface, not an implementation" found within the book Design Patterns (Gamma, et. al).
To provide a summary, the Dependency Inversion Principle is primarily about reversing the conventional direction of dependencies from "higher level" components to "lower level" components such that "lower level" components are dependent upon the interfaces owned by the "higher level" components. (Note: "higher level" component here refers to the component requiring external dependencies/services, not necessarily its conceptual position within a layered architecture.) In doing so, coupling isn't reduced so much as it is shifted from components that are theoretically less valuable to components which are theoretically more valuable.
This is achieved by designing components whose external dependencies are expressed in terms of an interface for which an implementation must be provided by the consumer of the component. In other words, the defined interfaces express what is needed by the component, not how you use the component (e.g. "INeedSomething", not "IDoSomething").
What the Dependency Inversion Principle does not refer to is the simple practice of abstracting dependencies through the use of interfaces (e.g. MyService → [ILogger ⇐ Logger]). While this decouples a component from the specific implementation detail of the dependency, it does not invert the relationship between the consumer and dependency (e.g. [MyService → IMyServiceLogger] ⇐ Logger.
Why Is It Important?
The importance of the Dependency Inversion Principle can be distilled down to a singular goal of being able to reuse software components which rely upon external dependencies for a portion of their functionality (logging, validation, etc.)
Within this general goal of reuse, we can delineate two sub-types of reuse:
Using a software component within multiple applications with sub-dependency implementations (e.g. You've developed a DI container and want to provide logging, but don't want to couple your container to a specific logger such that everyone that uses your container has to also use your chosen logging library).
Using software components within an evolving context (e.g. You've developed business-logic components which remain the same across multiple versions of an application where the implementation details are evolving).
With the first case of reusing components across multiple applications, such as with an infrastructure library, the goal is to provide a core infrastructure need to your consumers without coupling your consumers to sub-dependencies of your own library since coupling to such dependencies requires your consumers to require the same dependencies as well. This can be problematic when consumers of your library choose to use a different library for the same infrastructure needs (e.g. NLog vs. log4net), or if they choose to use a later version of the required library which isn't backward compatible with the version required by your library.
With the second case of reusing business-logic components (i.e. "higher-level components"), the goal is to isolate the core domain implementation of your application from the changing needs of your implementation details (i.e. changing/upgrading persistence libraries, messaging libraries, encryption strategies, etc.). Ideally, changing the implementation details of an application shouldn't break the components encapsulating the application's business logic.
Note: Some may object to describing this second case as actual reuse, reasoning that components such as business-logic components used within a single evolving application represents only a single use. The idea here, however, is that each change to the application's implementation details renders a new context and therefore a different use case, though the ultimate goals could be distinguished as isolation vs. portability.
While following the Dependency Inversion Principle in this second case can offer some benefit, it should be noted that its value as applied to modern languages such as Java and C# is much reduced, perhaps to the point of being irrelevant. As discussed earlier, the DIP involves separating implementation details into separate packages completely. In the case of an evolving application, however, simply utilizing interfaces defined in terms of the business domain will guard against needing to modify higher-level components due to changing needs of implementation detail components, even if the implementation details ultimately reside within the same package. This portion of the principle reflects aspects that were pertinent to the language in view when the principle was codified (i.e. C++) which aren't relevant to newer languages. That said, the importance of the Dependency Inversion Principle primarily lies with the development of reusable software components/libraries.
A longer discussion of this principle as it relates to the simple use of interfaces, Dependency Injection, and the Separated Interface pattern can be found here. Additionally, a discussion of how the principle relates to dynamically-typed languages such as JavaScript can be found here.
Check this document out: The Dependency Inversion Principle.
It basically says:
High level modules should not depend upon low-level modules. Both should depend upon abstractions.
Abstractions should never depend upon details. Details should depend upon abstractions.
As to why it is important, in short: changes are risky, and by depending on a concept instead of on an implementation, you reduce the need for change at call sites.
Effectively, the DIP reduces coupling between different pieces of code. The idea is that although there are many ways of implementing, say, a logging facility, the way you would use it should be relatively stable in time. If you can extract an interface that represents the concept of logging, this interface should be much more stable in time than its implementation, and call sites should be much less affected by changes you could make while maintaining or extending that logging mechanism.
By also making the implementation depend on an interface, you get the possibility to choose at run-time which implementation is better suited for your particular environment. Depending on the cases, this may be interesting too.
When we design software applications we can consider the low level classes the classes which implement basic and primary operations (disk access, network protocols,...) and high level classes the classes which encapsulate complex logic (business flows, ...).
The last ones rely on the low level classes. A natural way of implementing such structures would be to write low level classes and once we have them to write the complex high level classes. Since high level classes are defined in terms of others this seems the logical way to do it. But this is not a flexible design. What happens if we need to replace a low level class?
The Dependency Inversion Principle states that:
High level modules should not depend upon low level modules. Both should depend upon abstractions.
Abstractions should not depend upon details. Details should depend upon abstractions.
This principle seeks to "invert" the conventional notion that high level modules in software should depend upon the lower level modules. Here high level modules own the abstraction (for example, deciding the methods of the interface) which are implemented by lower level modules. Thus making lower level modules dependent on higher level modules.
Dependency inversion well applied gives flexibility and stability at the level of the entire architecture of your application. It will allow your application to evolve more securely and stable.
Traditional layered architecture
Traditionally a layered architecture UI depended on the business layer and this in turn depended on the data access layer.
You have to understand layer, package, or library. Let's see how the code would be.
We would have a library or package for the data access layer.
// DataAccessLayer.dll
public class ProductDAO {
}
And another library or package layer business logic that depends on the data access layer.
// BusinessLogicLayer.dll
using DataAccessLayer;
public class ProductBO {
private ProductDAO productDAO;
}
Layered architecture with dependency inversion
The dependency inversion indicates the following:
High-level modules should not depend on low-level modules. Both should depend on abstractions.
Abstractions should not depend on details. Details should depend on abstractions.
What are the high-level modules and low level? Thinking modules such as libraries or packages, high-level module would be those that traditionally have dependencies and low level on which they depend.
In other words, module high level would be where the action is invoked and low level where the action is performed.
A reasonable conclusion to draw from this principle is that there should be no dependence between concretions, but there must be a dependence on an abstraction. But according to the approach we take we can be misapplying investment depend dependency, but an abstraction.
Imagine that we adapt our code as follows:
We would have a library or package for the data access layer which define the abstraction.
// DataAccessLayer.dll
public interface IProductDAO
public class ProductDAO : IProductDAO{
}
And another library or package layer business logic that depends on the data access layer.
// BusinessLogicLayer.dll
using DataAccessLayer;
public class ProductBO {
private IProductDAO productDAO;
}
Although we are depending on an abstraction dependency between business and data access remains the same.
To get dependency inversion, the persistence interface must be defined in the module or package where this high level logic or domain is and not in the low-level module.
First define what the domain layer is and the abstraction of its communication is defined persistence.
// Domain.dll
public interface IProductRepository;
using DataAccessLayer;
public class ProductBO {
private IProductRepository productRepository;
}
After the persistence layer depends on the domain, getting to invert now if a dependency is defined.
// Persistence.dll
public class ProductDAO : IProductRepository{
}
(source: xurxodev.com)
Deepening the principle
It is important to assimilate the concept well, deepening the purpose and benefits. If we stay in mechanically and learn the typical case repository, we will not be able to identify where we can apply the principle of dependence.
But why do we invert a dependency? What is the main objective beyond specific examples?
Such commonly allows the most stable things, that are not dependent on less stable things, to change more frequently.
It is easier for the persistence type to be changed, either the database or technology to access the same database than the domain logic or actions designed to communicate with persistence. Because of this, the dependence is reversed because as it is easier to change the persistence if this change occurs. In this way we will not have to change the domain. The domain layer is the most stable of all, which is why it should not depend on anything.
But there is not just this repository example. There are many scenarios where this principle applies and there are architectures based on this principle.
Architectures
There are architectures where dependency inversion is key to its definition. In all the domains it is the most important and it is abstractions that will indicate the communication protocol between the domain and the rest of the packages or libraries are defined.
Clean Architecture
In Clean architecture the domain is located in the center and if you look in the direction of the arrows indicating dependency, it is clear what are the most important and stable layers. The outer layers are considered unstable tools so avoid depending on them.
(source: 8thlight.com)
Hexagonal Architecture
It happens the same way with the hexagonal architecture, where the domain is also located in the central part and ports are abstractions of communication from the domino outward. Here again it is evident that the domain is the most stable and traditional dependence is inverted.
(source: pragprog.com)
Basically it says:
Class should depend on abstractions (e.g interface, abstract classes), not specific details (implementations).
To me, the Dependency Inversion Principle, as described in the official article, is really a misguided attempt to increase the reusability of modules that are inherently less reusable, as well as a way to workaround an issue in the C++ language.
The issue in C++ is that header files typically contain declarations of private fields and methods. Therefore, if a high-level C++ module includes the header file for a low-level module, it will depend on actual implementation details of that module. And that, obviously, is not a good thing. But this is not an issue in the more modern languages commonly used today.
High-level modules are inherently less reusable than low-level modules because the former are normally more application/context specific than the latter. For example, a component that implements an UI screen is of the highest-level and also very (completely?) specific to the application. Trying to reuse such a component in a different application is counter-productive, and can only lead to over-engineering.
So, the creation of a separate abstraction at the same level of a component A that depends on a component B (which does not depend on A) can be done only if component A will really be useful for reuse in different applications or contexts. If that's not the case, then applying DIP would be bad design.
A much clearer way to state the Dependency Inversion Principle is:
Your modules which encapsulate complex business logic should not depend directly on other modules which encapsulate business logic. Instead, they should depend only on interfaces to simple data.
I.e., instead of implementing your class Logic as people usually do:
class Dependency { ... }
class Logic {
private Dependency dep;
int doSomething() {
// Business logic using dep here
}
}
you should do something like:
class Dependency { ... }
interface Data { ... }
class DataFromDependency implements Data {
private Dependency dep;
...
}
class Logic {
int doSomething(Data data) {
// compute something with data
}
}
Data and DataFromDependency should live in the same module as Logic, not with Dependency.
Why do this?
The two business logic modules are now decoupled. When Dependency changes, you don't need to change Logic.
Understanding what Logic does is a much simpler task: it operates only on what looks like an ADT.
Logic can now be more easily tested. You can now directly instantiate Data with fake data and pass it in. No need for mocks or complex test scaffolding.
Good answers and good examples are already given by others here.
The reason DIP is important is because it ensures the OO-principle "loosely coupled design".
The objects in your software should NOT get into a hierarchy where some objects are the top-level ones, dependent on low-level objects. Changes in low-level objects will then ripple-through to your top-level objects which makes the software very fragile for change.
You want your 'top-level' objects to be very stable and not fragile for change, therefore you need to invert the dependencies.
Inversion of control (IoC) is a design pattern where an object gets handed its dependency by an outside framework, rather than asking a framework for its dependency.
Pseudocode example using traditional lookup:
class Service {
Database database;
init() {
database = FrameworkSingleton.getService("database");
}
}
Similar code using IoC:
class Service {
Database database;
init(database) {
this.database = database;
}
}
The benefits of IoC are:
You have no dependency on a central
framework, so this can be changed if
desired.
Since objects are created
by injection, preferably using
interfaces, it's easy to create unit
tests that replace dependencies with
mock versions.
Decoupling off code.
Dependency Inversion Principle(DIP)
It is a part of SOLID[About] which is a part of OOD and was introduced by Uncle Bob. It is about loose coupling between classes(layers...). Class should not be depended on concrete realization, class should be depended on abstraction/interface
Problem:
//A -> B
class A {
B b
func foo() {
b = B();
}
}
Solution:
//A -> IB <|- B
//client[A -> IB] <|- B is the Inversion
class A {
IB ib // An abstraction between High level module A and low level module B
func foo() {
ib = B()
}
}
Now A is not depended on B(one to one), now A is depended on interface IB which is implemented by B, it means that A depends on multiple realization of IB(one to many)
[DIP vs DI vs IoC]
The point of dependency inversion is to make reusable software.
The idea is that instead of two pieces of code relying on each other, they rely on some abstracted interface. Then you can reuse either piece without the other.
The way this is most commonly achieved is through an inversion of control (IoC) container like Spring in Java. In this model, properties of objects are set up through an XML configuration instead of the objects going out and finding their dependency.
Imagine this pseudocode...
public class MyClass
{
public Service myService = ServiceLocator.service;
}
MyClass directly depends on both the Service class and the ServiceLocator class. It needs both of those if you want to use it in another application. Now imagine this...
public class MyClass
{
public IService myService;
}
Now, MyClass relies on a single interface, the IService interface. We'd let the IoC container actually set the value of that variable.
So now, MyClass can easily be reused in other projects, without bringing the dependency of those other two classes along with it.
Even better, you don't have to drag the dependencies of MyService, and the dependencies of those dependencies, and the... well, you get the idea.
If we can take it as a given that a "high level" employee at a corporation is paid for the execution of their plans, and that these plans are delivered by the aggregate execution of many "low level" employee's plans, then we could say it is generally a terrible plan if the high level employee's plan description in any way is coupled to the specific plan of any lower level employee.
If a high level executive has a plan to "improve delivery time", and indicates that an employee in the shipping line must have coffee and do stretches each morning, then that plan is highly coupled and has low cohesion. But if the plan makes no mention of any specific employee, and in fact simply requires "an entity that can perform work is prepared to work", then the plan is loosely coupled and more cohesive: the plans do not overlap and can easily be substituted. Contractors, or robots, can easily replace the employees and the high level's plan remains unchanged.
"High level" in the dependency inversion principle means "more important".
I can see good explanation has been given in above answers. However i wants to provide some easy explanation with simple example.
Dependency Inversion Principle allows the programmer to remove the hardcoded dependencies so that the application becomes loosely coupled and extendable.
How to achieve this : through abstraction
Without dependency inversion:
class Student {
private Address address;
public Student() {
this.address = new Address();
}
}
class Address{
private String perminentAddress;
private String currentAdrress;
public Address() {
}
}
In above code snippet, address object is hard-coded. Instead if we can use dependency inversion and inject the address object by passing through constructor or setter method. Let's see.
With dependency inversion:
class Student{
private Address address;
public Student(Address address) {
this.address = address;
}
//or
public void setAddress(Address address) {
this.address = address;
}
}
Dependency Inversion Principle (DIP) says that
i) High level modules should not depend upon low-level modules. Both should depend upon abstractions.
ii) Abstractions should never depend upon details. Details should depend upon abstractions.
Example:
public interface ICustomer
{
string GetCustomerNameById(int id);
}
public class Customer : ICustomer
{
//ctor
public Customer(){}
public string GetCustomerNameById(int id)
{
return "Dummy Customer Name";
}
}
public class CustomerFactory
{
public static ICustomer GetCustomerData()
{
return new Customer();
}
}
public class CustomerBLL
{
ICustomer _customer;
public CustomerBLL()
{
_customer = CustomerFactory.GetCustomerData();
}
public string GetCustomerNameById(int id)
{
return _customer.GetCustomerNameById(id);
}
}
public class Program
{
static void Main()
{
CustomerBLL customerBLL = new CustomerBLL();
int customerId = 25;
string customerName = customerBLL.GetCustomerNameById(customerId);
Console.WriteLine(customerName);
Console.ReadKey();
}
}
Note: Class should depend on abstractions like interface or abstract classes, not specific details (implementation of interface).
Dependency inversion: Depend on abstractions, not on concretions.
Inversion of control: Main vs Abstraction, and how the Main is the glue of the systems.
These are some good posts talking about this:
https://coderstower.com/2019/03/26/dependency-inversion-why-you-shouldnt-avoid-it/
https://coderstower.com/2019/04/02/main-and-abstraction-the-decoupled-peers/
https://coderstower.com/2019/04/09/inversion-of-control-putting-all-together/
Adding to the flurry of generally good answers, I'd like to add a tiny sample of my own to demonstrate good vs. bad practice. And yes, I'm not one to throw stones!
Say, you want a little program to convert a string into base64 format via console I/O. Here's the naive approach:
class Program
{
static void Main(string[] args)
{
/*
* BadEncoder: High-level class *contains* low-level I/O functionality.
* Hence, you'll have to fiddle with BadEncoder whenever you want to change
* the I/O mode or details. Not good. A good encoder should be I/O-agnostic --
* problems with I/O shouldn't break the encoder!
*/
BadEncoder.Run();
}
}
public static class BadEncoder
{
public static void Run()
{
Console.WriteLine(Convert.ToBase64String(Encoding.UTF8.GetBytes(Console.ReadLine())));
}
}
The DIP basically says that high-level components shouldn't be dependent on low-level implementation, where "level" is the distance from I/O according to Robert C. Martin ("Clean Architecture"). But how do you get out of this predicament? Simply by making the central Encoder dependent only on interfaces without bothering how those are implemented:
class Program
{
static void Main(string[] args)
{
/* Demo of the Dependency Inversion Principle (= "High-level functionality
* should not depend upon low-level implementations"):
* You can easily implement new I/O methods like
* ConsoleReader, ConsoleWriter without ever touching the high-level
* Encoder class!!!
*/
GoodEncoder.Run(new ConsoleReader(), new ConsoleWriter()); }
}
public static class GoodEncoder
{
public static void Run(IReadable input, IWriteable output)
{
output.WriteOutput(Convert.ToBase64String(Encoding.ASCII.GetBytes(input.ReadInput())));
}
}
public interface IReadable
{
string ReadInput();
}
public interface IWriteable
{
void WriteOutput(string txt);
}
public class ConsoleReader : IReadable
{
public string ReadInput()
{
return Console.ReadLine();
}
}
public class ConsoleWriter : IWriteable
{
public void WriteOutput(string txt)
{
Console.WriteLine(txt);
}
}
Note that you don't need to touch GoodEncoder in order to change the I/O mode — that class is happy with the I/O interfaces it knows; any low-level implementation of IReadable and IWriteable won't ever bother it.
Related
In book 'Patterns of Enterprise Application Architecture', following is stated:
When thinking of a system in terms of layers, you imagine the principal subsystems
in the software arranged in some form of layer cake, where each layer
rests on a lower layer. In this scheme the higher layer uses various services
defined by the lower layer, but the lower layer is unaware of the higher layer.
On other hand, in book 'Agile Principles, Patterns, and Practices', following is stated on Dependency-Inversion Principle:
High-level modules should not depend on low-level modules. Both should depend
on abstractions.
This sort of confuses me. Am I mixing two different things here?
I suppose that it could speak to some the same principles, but at different levels of granularity. I would still view Dependency Inversion as something that stands on its own, however.
In the first instance, consider this example - in a simple layered architecture, you might have a presentation layer built in JavaScript, a business logic layer built in Java, and a data layer in SQL Server. These layers could be developed by different teams of people. The presentation layer knows how to make API calls to the business logic layer, but not the other way around. The business logic layer knows how to read/write to and from the database layer, but not the other way around. The distinction here happens at a high-level - you might even call it conceptual.
In the second instance, you want to prevent scenarios where supposedly generic code depends on specific implementations - and at this point, I see it as a relatively low-level concern that falls within the scope of a particular application (i.e. in code, not conceptually as in the previous example). If you have code that writes to a database, but you want to support different implementations - e.g. MySQL and SQL Server, where each of those might have some specific intricacies, don't make the calling code explicitly depend on either of those - abstract away the complexity through an interface. This is what the Dependency Inversion Principle addresses (see below).
public class UserService {
public UserRepository repository;
public void setUserRepository(UserRepository repository) {
this.repository = repository; //Is this a MySqlRepository or a SqlServerRepository? We don't care - the dependency is managed outside and we can change it without changing this class.
}
public void persistUser() {
this.repository.persist(user); //We just care about the abstraction - the interface.
}
}
Am I mixing two different things here?
Yes.
The first case is about dependencies at run-time while the second case is about dependencies at compile-time.
For example, at run-time, business layer can call the functions/methods implemented in database layer. But at compile-time, business layer code does not mention any code in database layer. This is usually achieved with Polymorphism.
I was recently having a debate about the Dependency Inversion Principle, Inversion of Control and Dependency Injection. In relation to this topic we were debating whether these principles violate one of the pillars of OOP, namely Encapsulation.
My understanding of these things is:
The Dependency Inversion Principle implies that objects should depend upon abstractions, not concretions - this is the fundamental principle upon which the Inversion of Control pattern and Dependency Injection are implemented.
Inversion of Control is a pattern implementation of the Dependency Inversion Principle, where abstract dependencies replace concrete dependencies, allowing concretions of the dependency to be specified outside of the object.
Dependency Injection is a design pattern that implements Inversion of Control and provides dependency resolution. Injection occurs when a dependency is passed to a dependent component. In essence, the Dependency Injection pattern provides a mechanism for coupling dependency abstractions with concrete implementations.
Encapsulation is the process whereby data and functionality that is required by a higher level object is insulated away and inaccessible, thus, the programmer is unaware of how an object is implemented.
The debate got to a sticking point with the following statement:
IoC isn't OOP because it breaks Encapsulation
Personally, I think that the Dependency Inversion Principle and the Inversion of Control pattern should be observed religiously by all OOP developers - and I live by the following quote:
If there is (potentially) more than one way to skin a cat, then do not
behave like there is only one.
Example 1:
class Program {
void Main() {
SkinCatWithKnife skinner = new SkinCatWithKnife ();
skinner.SkinTheCat();
}
}
Here we see an example of encapsulation. The programmer only has to call Main() and the cat will be skinned, but what if he wanted to skin the cat with, say a set of razor sharp teeth?
Example 2:
class Program {
// Encapsulation
ICatSkinner skinner;
public Program(ICatSkinner skinner) {
// Inversion of control
this.skinner = skinner;
}
void Main() {
this.skinner.SkinTheCat();
}
}
... new Program(new SkinCatWithTeeth());
// Dependency Injection
Here we observe the Dependency Inversion Principle and Inversion of Control since an abstract (ICatSkinner) is provided in order to allow concrete dependencies to be passed in by the programmer. At last, there is more than one way to skin a cat!
The quarrel here is; does this break encapsulation? technically one could argue that .SkinTheCat(); is still encapsulated away within the Main() method call, so the programmer is unaware of the behavior of this method, so I do not think this breaks encapsulation.
Delving a little deeper, I think that IoC containers break OOP because they use reflection, but I am not convinced that IoC breaks OOP, nor am I convinced that IoC breaks encapsulation. In fact I'd go as far as to say that:
Encapsulation and Inversion of Control coincide with each other
happily, allowing programmers to pass in only the concretions of a
dependency, whilst hiding away the overall implementation via
encapsulation.
Questions:
Is IoC a direct implementation of the Dependency Inversion Principle?
Does IoC always break encapsulation, and therefore OOP?
Should IoC be used sparingly, religiously or appropriately?
What is the difference between IoC and an IoC container?
Does IoC always break encapsulation, and therefore OOP?
No, these are hierarchically related concerns. Encapsulation is one of the most misunderstood concepts in OOP, but I think the relationship is best described via Abstract Data Types (ADTs). Essentially, an ADT is a general description of data and associated behaviour. This description is abstract; it omits implementation details. Instead, it describes an ADT in terms of pre- and post-conditions.
This is what Bertrand Meyer calls design by contract. You can read more about this seminal description of OOD in Object-Oriented Software Construction.
Objects are often described as data with behaviour. This means that an object without data isn't really an object. Thus, you have to get data into the object in some way.
You could, for example, pass data into an object via its constructor:
public class Foo
{
private readonly int bar;
public Foo(int bar)
{
this.bar = bar;
}
// Other members may use this.bar in various ways.
}
Another option is to use a setter function or property. I hope we can agree that so far, encapsulation is not violated.
What happens if we change bar from an integer to another concrete class?
public class Foo
{
private readonly Bar bar;
public Foo(Bar bar)
{
this.bar = bar;
}
// Other members may use this.bar in various ways.
}
The only difference compared to before is that bar is now an object, instead of a primitive. However, that's a false distinction, because in object-oriented design, an integer is also an object. It's only because of performance optimisations in various programming languages (Java, C#, etc.) that there's an actual difference between primitives (strings, integers, bools, etc.) and 'real' objects. From an OOD perspective, they're all alike. Strings have behaviours as well: you can turn them into all-upper-case, reverse them, etc.
Is encapsulation violated if Bar is a sealed/final, concrete class with only non-virtual members?
bar is only data with behaviour, just like an integer, but apart from that, there's no difference. So far, encapsulation isn't violated.
What happens if we allow Bar to have a single virtual member?
Is encapsulation broken by that?
Can we still express pre- and post-conditions about Foo, given that Bar has a single virtual member?
If Bar adheres to the Liskov Substitution Principle (LSP), it wouldn't make a difference. The LSP explicitly states that changing the behaviour mustn't change the correctness of the system. As long as that contract is fulfilled, encapsulation is still intact.
Thus, the LSP (one of the SOLID principles, of which the Dependency Inversion Principle is another) doesn't violate encapsulation; it describes a principle for maintaining encapsulation in the presence of polymorphism.
Does the conclusion change if Bar is an abstract base class? An interface?
No, it doesn't: those are just different degrees of polymorphism. Thus we could rename Bar to IBar (in order to suggest that it's an interface) and pass it into Foo as its data:
public class Foo
{
private readonly IBar bar;
public Foo(IBar bar)
{
this.bar = bar;
}
// Other members may use this.bar in various ways.
}
bar is just another polymorphic object, and as long as the LSP holds, encapsulation holds.
TL; DR
There's a reason SOLID is also known as the Principles of OOD. Encapsulation (i.e. design-by-contract) defines the ground rules. SOLID describes guidelines for following those rules.
Is IoC a direct implementation of the Dependency Inversion Principle?
The two are related in a way that they talk about abstractions, but that's about it. Inversion of Control is:
a design in which custom-written portions of a computer program
receive the flow of control from a generic, reusable library (source)
Inversion of control is allowing us to hook our custom code into the pipeline of a reusable library. In other words, Inversion control is about frameworks. A reusable library that does not apply Inversion of Control is merely a library. A framework is a reusable library that does apply Inversion of Control.
Do note that we as developers can only apply Inversion of Control if we are writing a framework ourselves; you can't apply inversion of control as an application developer. We can (and should) however apply Dependency Inversion Principle and the Dependency Injection pattern.
Does IoC always break encapsulation, and therefore OOP?
Since IoC is just about hooking into the pipeline of a framework, there is nothing that's leaking here. So the real question is: does Dependency Injection break encapsulation.
The answer to that question is: no, it does not. It doesn't break encapsulation because of two reasons:
Since the Dependency Inversion Principles states that we should program against an abstraction, a consumer will not be able to access the internals of the used implementation and that implementation will therefore not be breaking encapsulation to the client. The implementation might not even be known or accessible at compile time (because it lives in an unreferenced assembly) and the implementation can in that case not leak implementation details and break encapsulation.
Although the implementation accepts the dependencies it requires throughout its constructor, those dependencies will typically be stored in private fields and can't be accessed by anyone (even if a consumer depends directly on the concrete type) and it will therefore not break encapsulation.
Should IoC be used sparingly, religiously or appropriately?
Again, the question is "Should DIP and DI be used sparingly". In my opinion, the answer is: NO, you should actually use it throughout the application. Obviously, you should never apply things religiously. You should apply SOLID principles and the DIP is a crucial part of those principles. They will make your application more flexible and more maintainable and in most scenarios it is very appropriate to apply the SOLID principles.
What is the difference between IoC and an IoC container?
Dependency Injection is a pattern that can be applied either with or without a IoC container. An IoC container is merely a tool that can help building your object graph in a more convenient way, in case you have an application that applies the SOLID principles correctly. If you have an application that doesn't apply the SOLID principles, you will have a hard time using a IoC container. You will have a hard time applying Dependency Injection. Or let me put it more broadly, you will have a hard time maintaining your application anyway. But in no way an IoC container is a required tool. I'm developing and maintaining an IoC container for .NET, but I don't always use a container for all my applications. For the big BLOBAs (boring line of business applications) I often use a container, but for smaller apps (or windows services) I don't always use a container. But I do almost always use Dependency Injection as a pattern, because this is the most effective way to adhere to DIP.
Note: Since an IoC container helps us in applying the Dependency Injection pattern, "IoC container" is a terrible name for such library.
But despite of anything I said above, please note that:
in the real world of the software developer, usefulness trumps theory [from Robert C. Martin's Agile Principle, Patterns and Practices]
In other words, even if DI would break encapsulation, it wouldn't matter, because these techniques and patterns have proven to be very valuable, because it results in very flexible and maintainable systems. Practice trumps theory.
Summing up the question:
We have the ability for a Service to instantiate its own dependencies.
Yet, we also have the ability for a Service to simply define abstractions, and require an application to know about the dependent abstractions, create concrete implementations, and pass them in.
And the question is not, "Why we do it?" (Because we know there is a huge list of why). But the question is, "Doesn't option 2 break encapsulation?"
My "pragmatic" answer
I think Mark is the best bet for any such answers, and as he says: No, encapsulation isn't what people think it is.
Encapsulation is hiding away implementation details of a service or abstraction. A Dependency isn't an implementation detail. If you think of a service as a contract, and its subsequent sub-service dependencies as sub-contracts (etc etc chained along), then you really just end up with one huge contract with addendums.
Imagine I'm a caller and I want to use a legal service to sue my boss. My application would have to know about a service that does so. That alone breaks the theory that knowing about the services/contracts required to accomplish my goal is false.
The argument there is... yeah, but I just want to hire a lawyer, I don't care about what books or services he uses. I'll get some random dood off the interwebz and not care about his implementation details... like so:
sub main() {
LegalService legalService = new LegalService();
legalService.SueMyManagerForBeingMean();
}
public class LegalService {
public void SueMyManagerForBeingMean(){
// Implementation Details.
}
}
But it turns out, other services are required to get the job done, such as understanding workplace law. And also as it turns out... I am VERY Interested in the contracts that lawyer is signing under my name and the other stuff he's doing to steal my money. For example... Why the hell is this internet lawyer based in South Korea? How will THAT help me!?!? That isn't an implementation detail, that's part of a dependency chain of requirements I'm happy to manage.
sub main() {
IWorkLawService understandWorkplaceLaw = new CaliforniaWorkplaceLawService();
//IWorkLawService understandWorkplaceLaw = new NewYorkWorkplaceLawService();
LegalService legalService = new LegalService(understandWorkplaceLaw);
legalService.SueMyManagerForBeingMean();
}
public interface ILegalContract {
void SueMyManagerForBeingMean();
}
public class LegalService : ILegalContract {
private readonly IWorkLawService _workLawService;
public LegalService(IWorkLawService workLawService) {
this._workLawService = workLawService;
}
public void SueMyManagerForBeingMean() {
//Implementation Detail
_workLawService.DoSomething; // { implementation detail in there too }
}
}
Now, all I know is that I have a contract which has other contracts which might have other contracts. I am very well responsible for those contracts, and not their implementation details. Though I am more than happy to sign those contracts with concretions that are relevant to my requirements. And again, I don't care about how those concretions do their jobs, as long as I know I have a binding contract that says we exchange information in some defined way.
I will try to answer your questions, According to my understanding:
Is IoC a direct implementation of the Dependency Inversion Principle?
we can't label IoC as the direct implementation of DIP , as DIP focuses on making higher level modules depending on the abstraction and not on the concretion of lower level modules. But rather IoC is an implementation of Dependency Injection.
Does IoC always break encapsulation, and therefore OOP?
I don't think the mechanism of IoC will violate Encapsulation. But can make the system become Tightly coupled.
Should IoC be used sparingly, religiously or appropriately?
IoC can be used as a in many patterns like Bridge Pattern, where seperating Concretion from Abstraction improves the code. Thus can be used in order to achieve DIP.
What is the difference between IoC and an IoC container?
IoC is a mechanism of Dependency Inversion but containers are those which uses IoC.
Encapsulation does not contradict with Dependency Inversion Principles in Object-Oriented Programming world. For example in a car design, you will have an 'internal engine' which will be encapsulated from outside world, and also 'wheels' that can be replaced easily, and considered as outside component of the car. The car has specification (interface) to rotate the shaft of the wheels, and the wheels component implements part that interact with the shaft.
Here, The internal engine represents the encapsulation process, while the wheel components represent the Dependency Inversion Principles (DIP) in the car design. With DIP, basically we prevent building a monolithic object, and instead we make our object composable. Can you image you build a car, where you cannot replace the wheels because they are built-in into the car.
Also you can read more about Dependency Inversion Principles in more details in my blog Here.
I'm only going to answer one question as many other people have answered everything else. And keep in mind, there is no right or wrong answer, just user preferences.
Should IoC be used sparingly, religiously or appropriately?
My experience leads me to believe that Dependency Injection should only be used on classes that are general and might need changing in the future. Using it religiously will lead to some classes needing 15 interfaces in the constructor which can get really time consuming. That tends to lead to 20% development and 80% house keeping.
Someone brought up an example of a car, and how the builder of the car will want to change the tires. Dependency injection allows one to change the tires without caring of the specific implementation details. But if we take dependency injection religiously... Then we need to start building interfaces to the constituents of the tires as well... Well, what about the threads of the tire? What about the stitching in those tires? What about the chemical in those threads? What about the atoms in those chemical? Etc... Okay! Hey! At some point you're going to have to say "enough is enough"! Let's not turn every little thing into an interface... Because that can get too time consuming. It's okay to have some classes be self contained in and instantiated in the class itself! It's faster to develop, and instantiating the class is a ton easier.
Just my 2 cents.
I have found a case when ioc and dependency injection breaks encapsulation . Lets assume we have a ListUtil class . In that class there is a method called remove duplicates . This method accepts a List . There is an interface ISortAlgorith with a sort method . There is a class called QuickSort which implements this interface. When we write the alogorithm to remove duplicates we have to sort the list inside . Now if RemoveDuplicates allow an interface ISortAlgorithm as a parameter(IOC/Dependency Injection) to allow extensibility for others to choose an another algorithm for remove duplicate we are exposing the complexity of remove duplicate feature of the ListUtil class . Thus violating the foundation stone of Oops.
I know this question's been asked before (e.g., What is the difference between the bridge pattern and the strategy pattern?).
However, could someone please explain, using clear-cut examples, what the difference is and in what sorts of cases one must be selected over the other? Less conceptual theory, more practical "real-life" scenarios would be appreciated.
The Bridge Pattern makes a distinction between an abstraction and an implementation in such a way that the two can vary independently. I will use the example from
Patterns in Java, Volume 1: A Catalog of Reusable Design Patterns Illustrated with UML, Second Edition
You need to provide classes that access physical sensors such as found in scales, speed measuring devices etc. Each sensor produces a number but the number could mean different things. For the scale it could mean the weight and for the speed measuring device it may mean speed.
So you can start by creating a Sensor abstract class to represent the commonality between all sensors and various subclasses for the different types of sensors. This is a robust design allowing you to provide many more types of sensors in the future.
Now suppose that sensors are provided by different manufacturers. You will have to create a heirarchy of sensor classes for manufacturer X and another for manufacturer Y. The problem now is that the clients would need to know the difference between the manufacturers. And if you decide to support a third manufacturer...?
The solution is to provide the main abstraction heirarchy, ie. the Sensor abstract class and sub classes such as SpeedSensor and WeightSensor and so on. Then provide the interface (Bridge) that will exist between the abstraction and the implementation. So there will be a SensorInterface, WeightSensorInterface and SpeedSensorInterface, which dictates the interface that each concrete sensor class must provide. The abstraction does not know about the implementation, rather it knows about the interface. Finally, you can create an concreate implementation for each manufacturer. That is, XSensor, XWeightSensor and XSpeedSensor, YSensor, YSpeedSensor and YWeightSensor.
Clients depend only on the abstraction but any implementation could be plugged in. So in this setup, the abstraction could be changed without changing any of the concrete classes, and the implementation could be changed without worrying about the abstraction.
As you can see this describes a way to structure your classes.
The Strategy on the other hand is concerned with changing the behaviour of an object at run time. I like to use the example of a game with a character that possesses several different types of weapons. The character can attack but the behaviour of attack depends on the weapon that the character is holding at the time, and this cannot be known at compile time.
So you make the weapon behaviour pluggable and inject it into the character as needed. Hence a behavioral pattern.
These two patterns solve different problems. The strategy is concerned with making algorithms interchangeable while the Bridge is concerned with decoupling the abstraction from the inplementation so that you can provide multiple implementations for the same abstraction. That is, the bridge is concerned with entire structures.
Here are a few links that might be useful:
Bridge Pattern
Strategy Pattern
I can tell this is hard to explain. Many people who use it and understand it have a hard time explaining it to newbies.
For those like me who think in terms of analogies:
Strategy Pattern
So strategy is kind-of a one-dimensional concept. Think of a one-dimensional array of strategies to choose from.
Example 1: Plumber's tools
The strategy pattern is like a plumber who has various tools to get a pipe unclogged. The job is the same each time; it's to unclog the pipe. But the tool he chooses to get this done can vary depending on the situation. Maybe he'll try one and if that doesn't work he'll try another.
In this analogy, "unclog the pipe" is the method that will implement one of the strategies. Snake brush, power auger, and draino are the concrete strategies, and the plumber is the class containing the method (labeled "Context" in most diagrams).
Example 2: Multi-bit screwdriver
Or you could think of the interchangeable bits on a multi-bit screwdriver.
They are meant to be changed out at run-time to suit the job at hand, which is to screw something.
Bridge Pattern
So bridge is a two-dimensional concept. Think of one dimension (the rows) being the list of methods that need to be implemented, and the second dimension (the columns) being the Implementors who will implement each one of those methods.
Example 1: Apps and devices
The bridge pattern is like a person that has many ways that they can communicate (email, text, google voice, phone, skype) and many devices on with which they can communicate in these various ways - a PC, a tablet, and a smart phone.
The various ways to communicate (email, text, phone) would be the methods on an abstract interface, let's call it "CommunicationDevice". In this pattern, CommunicationDevice is the Implementor. Each device in this analogy (PC, tablet, smart phone) is the ConcreteImplementor that implements all these methods (email, text, phone).
Example 2: Odbc database drivers and odbc functions
Another ready example of bridge is the odbc or oledb database driver modules from Windows. They all implement the various methods on the same standard "database driver" interface, but they implement that interface in different ways. Even if you are using the same database, say Sql Server, there are still different drivers that can talk to Sql Server, albeit in different ways under the covers.
Example 3: Implementors (columns) implementing methods (rows)
Strategy pattern
This pattern lets the algorithm that executes vary independently from the clients that use it. i.e. Instead of having a fixed algorithm to exeucte for a given sitaution, it allows one among many algorithms to be selected on-the-fly at runtime. This involves removing an algorithm from its host class and putting it in a separate class.
For example, suppose one wants to travel from a city to another, then he has several choices: take a bus, hire a car, catch a train, etc. So each mode of transport selected would transpire into a separate algorithm to be executed. The mode of transport chosen will depend on various factors decided at runtime (cost, time, etc.). In other words, the strategy chosen to execute will be decided on-the-fly.
Another example, suppose one wants to implement a SortedList class(main controller) that Sorts based on a strategy. The strategy is the method that one uses to sort (like MergeSort, QuickSort).
Comparison with the Bridge pattern
The main difference (even though both patterns have the same UML) is that unlike the bridge pattern (which is a structural pattern), the strategy pattern is a behavioral pattern. Structural patterns suggest ways in which objects are composed or associated or inherited to forms larger objects i.e. they focus on object composition. While behavioral patterns deal with the algorithm or business logic (and not on the object creation itself) i.e. they focus on the collaboration between objects.
Note that most algorithms can be implementated as static or singleton classes required only single instance creation (i.e. new is not called for everytime a strategy is set).
A closer look at the implementation of the two patterns will reveal that in the bridge pattern one creates the concrete implementation of the object and then the call.
// Set implementation and call
// i.e. Returns (creates) the concrete implementation of the object,
// subsequently operation is called on the concrete implementation
ab.Implementor = new ConcreteImplementorA();
ab.Operation();
Whereas in the case of the strategy pattern, one will not use the concrete implementation of the algorithm directly, instead he will create the context in which the strategy should execute,
// Set the context with a strategy
// i.e. Sets the concrete strategy into the context, concrete implementation of the class not
// directly available as a data object (only the algorithm is available).
context = new Context (new ConcreteStrategyA());
context.contextInterface();
// Strategy can be reused instead of creating a new instance every time it is used.
// Sort example
MergeSort mergeSort = new MergeSort();
QuickSort quickSort = new QuickSort();
...
context = new Context (mergeSort);
context.Sort();
...
context = new Context (quickSort);
context.Sort();
...
context = new Context (mergeSort);
context.Sort();
The Bridge pattern tells how organize classes, the Strategy - how organize algorithms.
Difference between bridge and strategy pattern:
Bridge pattern gives us the ability to re implement, being running business structure as per our current situation , other side strategy pattern gives us ability to implement our various business strategy and encapsulate them and use them as per situation or at a time.
Main difference between both is using bridge pattern we can change our whole structure but using strategy we are able to change our business strategy parallelly.
I have elaborated two very important design patter below as per my understanding.
please carefully go throw this i think it will clear your understanding about both them.
Bridge Pattern:
What is Bridge Design Pattern?
The sense of GoF suggested Bridge pattern is decouple the implementation of an component from it's abstraction.
When we will use the Bridge Design Pattern?
Let imagine a situation where a component already implemented, and it's running well as per your business need. Suddenly the organisation changed their business strategy. For this you need to be change or re-implemented the component. At this situation, what you will do change the previous one that are running well last few years, or you Create the new component. At this situation bridge pattern beautifully handled the scenario. See the example below for better understanding.
// Main component
public interface Ibridge
{
void function1();
}
// Already Implemented that are currently being using
public class Bridge1 : Ibridge
{
public void function1()
{
Console.WriteLine("Implemented function from bridge 1");
}
}
//New Implementation as per Organisation needs
public class Bridge2 : Ibridge
{
public void function1()
{
Console.WriteLine("Implemented function from bridge2");
}
}
//Abstract Calling functionalities
public interface IAbstractBridge
{
void CallFunc1();
}
// implementation of calling implemented component at a time
public class AbstractBridge:IAbstractBridge
{
protected Ibridge _ibridge;
public Ibridge Ibridge
{
set { _ibridge = value; }
}
public void CallFunc1()
{
this._ibridge.function1();
}
}
class Program
{
static void Main(string[] args)
{
AbstractBridge abp = new AbstractBridge();
/*
here you see that now being using the previous implemented component.
but need change newly implemented component so here we need just changed
the implementation of component, please see below
*/
//Commented old one
abp.Ibridge = new Bridge1();
//using new one just change the "Bridge1" to "Bridge2"
abp.Ibridge = new Bridge2();
abp.CallFunc1();
}
}
Strategy design Pattern:
What is Strategy Design Pattern?
The sense of GoF suggested Strategy pattern is Define a family of algorithms, encapsulate each one, and make them interchangeable. Strategy lets the algorithm vary independently from clients that use it.
When we will use the Strategy Design Pattern?
Let imagine a situation where a owner of shopping complex want to attract customer giving different discount offer based on their various occasion and the discount offer any time owner can switch from discount mode to normal mode vice versa ,then how to handle this situation At this situation strategy pattern handled the scenario. Lets See the example below for better understanding.
All Strategy:
public interface ISellingStrategy
{
void selling();
}
public class BasicStrategy : ISellingStrategy
{
public void selling()
{
Console.WriteLine("Buy Three get 5% discount.");
}
}
public class ChrismasStrategy : ISellingStrategy
{
public void selling()
{
Console.WriteLine("Buy Three get one offer + extra 5% discount.");
}
}
public class HoliFestiveStrategy : ISellingStrategy
{
public void selling()
{
Console.WriteLine("Buy two get one offer + extra 5% discount.");
}
}
public class DurgapuljaStrategy : ISellingStrategy
{
public void selling()
{
Console.WriteLine("Buy one get one offer + extra 5% discount.");
}
}
Billing:
public class Billing
{
private ISellingStrategy strategy;
public void SetStrategy(ISellingStrategy _strategy)
{
this.strategy = _strategy;
}
public void ApplyStrategy()
{
strategy.selling();
Console.WriteLine("Please wait offer is being applying...");
Console.WriteLine("Offer is now Applied and ready for billing..");
}
}
Factory patter for Creating Object of Billing Class
public class BillingFactory
{
public static Billing CreateBillingObject()
{
return new Billing();
}
}
Calling
class Program
{
static void Main(string[] args)
{
Billing billing = BillingFactory.CreateBillingObject();
billing.SetStrategy(new BasicStrategy());
billing.ApplyStrategy();
Console.ReadLine();
}
}
Both patterns separate interface from implementation. I think the key distinction is that the Bridge Pattern uses inheritance ("is a") while the Strategy Pattern uses composition ("has a").
Bridge Pattern:
class Sorter abstract
{
virtual void Sort() = 0;
}
// MergeSorter IS A Sorter
class MergeSorter : public Sorter
{
virtual void Sort() override;
}
Strategy Pattern:
class SortStrategy abstract
{
virtual void Sort() = 0;
}
// Sorter HAS A SortStrategy
class Sorter
{
Sorter(SortStragety *strategy) : mStrat(strategy) {}
void Sort() {mStrat->Sort();}
SortStrategy *mStrat;
}
The Strategy pattern encapsulates algorithms so that they can be used and changed in a complex program (without gumming up the works) and the Bridge pattern allows two interfaces loosely bound so that they can interact but be changed independently of one another.
You can find PHP examples of the Bridge and Strategy patterns here:
http://www.php5dp.com/category/design-patterns/bridge/
and
http://www.php5dp.com/category/design-patterns/strategy/
You'll find a lot of examples for both patterns that may be helpful.
Strategy:
Strategy is behavioral design pattern. If is used to switch between family of algorithms.
This pattern contains one abstract strategy interface and many concrete strategy implementations (algorithms) of that interface.
The application uses strategy interface only. Depending in some configuration parameter, the concrete strategy will be tagged to interface.
Bridge:
It allows both abstractions and implementations to vary independently.
It uses composition over inheritance.
Bridge is a structural pattern.
However, could someone please explain, using clear-cut examples, what the difference is and in what sorts of cases one must be selected over the other?
Refer to below post to get insight on use cases of Strategy and Bridge patterns:
Real World Example of the Strategy Pattern
When do you use the Bridge Pattern? How is it different from Adapter pattern?
On quick note:
Use Strategy pattern to dynamically change the implementation by replacing one strategy with other strategy.
One real word example : Airlines offering discounts during off-peak months. Simply change fare discount strategy with no-discount strategy during high peak time.
Use Bridge pattern when Abstractions and implementations have not been decided at compile time and can vary independently
One real world example in Automobile industry : Different type of Gears can be assembled into different types of Cars. Both Car and Gear specification and implementation can change independently.
Let me recite the answers from the linked question.
The bridge pattern is a structural pattern, that is, it lays out ideas of how to build a component of your project. It is used to hide two levels of abstractions. The sample code on Wikipedia (http://en.wikipedia.org/wiki/Bridge_pattern) explains it in most unambiguous terms.
The strategy pattern is a dynamic pattern. When any wild function can implement the requirements, a strategy pattern is used. Examples can be any program that allows for plugins to be developed and installed. On the Wikipedia pageg(http://en.wikipedia.org/wiki/Strategy_pattern), ConcreteStrategyAdd, ConcreteStrategySubtract, etc is plugin used in the ConcreteStrategy class. Any method could be used there that implements the interface Strategy.
Can any one describe the exact difference between loose coupling and tight coupling in Object oriented paradigm?
Tight coupling is when a group of classes are highly dependent on one another.
This scenario arises when a class assumes too many responsibilities, or when one concern is spread over many classes rather than having its own class.
Loose coupling is achieved by means of a design that promotes single-responsibility and separation of concerns.
A loosely-coupled class can be consumed and tested independently of other (concrete) classes.
Interfaces are a powerful tool to use for decoupling. Classes can communicate through interfaces rather than other concrete classes, and any class can be on the other end of that communication simply by implementing the interface.
Example of tight coupling:
class CustomerRepository
{
private readonly Database database;
public CustomerRepository(Database database)
{
this.database = database;
}
public void Add(string CustomerName)
{
database.AddRow("Customer", CustomerName);
}
}
class Database
{
public void AddRow(string Table, string Value)
{
}
}
Example of loose coupling:
class CustomerRepository
{
private readonly IDatabase database;
public CustomerRepository(IDatabase database)
{
this.database = database;
}
public void Add(string CustomerName)
{
database.AddRow("Customer", CustomerName);
}
}
interface IDatabase
{
void AddRow(string Table, string Value);
}
class Database implements IDatabase
{
public void AddRow(string Table, string Value)
{
}
}
Another example here.
Explanation without any code
Simple analogy to explain the concept. Code can come later.
Summary Example of Loose Coupling:
In the picture above, the Hat is "loosely coupled" to the body. This means you can easily take the hat off without making any changes to the person/body. When you can do that then you have "loose coupling". See below for elaboration.
Detailed Example
Think of your skin. It's stuck to your body. It fits like a glove. But what if you wanted to change your skin colour from say white to black? Can you imagine just how painful it would be to peel off your skin, dye it, and then to paste it back on etc? Changing your skin is difficult because it is tightly coupled to your body. You just can't make changes easily. You would have to fundamentally redesign a human being in order to make this possible.
Key Point #1: In other words, if you want to change the skin, you would also HAVE TO change the design of your body as well because the two are joined together - they are tightly coupled.
God was not a good object oriented programmer.
Loose coupling (Detailed Example)
Now think of getting dressed in the morning. You don't like blue? No problems: you can put a red shirt on instead. You can do this easily and effortlessly because the shirt is not really connected to your body the same way as your skin. The shirt doesn't know or care about what body it is going on. In other words, you can change your clothes, without really changing your body.
That's key point #2. If you change your shirt, then you are not forced to change your body - when you can do that, then you have loose coupling. When you can't do that, then you have tight coupling.
That's the basic concept in a nutshell.
Why is all of this important?
What do changing shirts have to do with software?
Change. It's inevitable when writing software. If we know in advance that a change is going to come in a particular place, we should loosely couple on that point: then we could make those changes easily and quickly, without bugs.....Consider some examples which might help elaborate:
Loose Coupling in Software:
CSV/JSON Examples: Early on in my career, my manager said: "give me the output as a CSV file". I created a routine that worked like a charm. Then one or two weeks later, he says: "actually, I want the output for another client in JSON".
I had to rewrite the entire thing. But this time, I rewrote it using interfaces - a loosely coupled design pattern. Now, adding new output formats, is so much easier. I can edit the JSON portions without fear I will break my CSV output.
DB Examples: if you want to switch from sqlLite to PostGreSQL easily - loosely coupled code makes it really easy to switch (i.e. to put on a red shirt instead of a blue shirt). The Rails ActiveRecord library is loosely coupled on its database implementation. This makes it super easy for someone to use their own database implementation, while using the same code base!
Cloud Provider examples: Or if you're using AWS and they start charging too much because of market dominance, you should be able to somewhat easily switch to Google or Azure etc. This is precisely the reason why libraries like Active Storage exist - they provide users with a healthy indifference as to the specific cloud provider being used (Azure, AWS S3, GCS etc.). You can easily change cloud providers with just a one-line code change. The implementation details of the cloud storage providers are loosely coupled.
Testing: if you want to test your software, with predetermined outputs and inputs - how are you going to do it? With loosely coupled software - it's a breeze: you can run your tests, and you can also deploy your production code and do it all in the same code base. With tightly coupled code, testing your production code is nearly impossible.
Do we need to make everything "loosely coupled"? Probably not. We should exercise judgement. Some amount of coupling is inevitable. But consider minimizing it if you know in advance where it will change. I would also counsel against guessing where things will change, and loosely coupling everything. Loosely couple, only when you need to.
Summary
In short, loose coupling makes code easier to change.
The answers above provide some code which is worth reading.
Advanced Topics
Loose coupling goes hand-in-hand with polymorphism and interfaces. If you like cartoons and analogies, consider some other posts I have written:
What is Polymorphism?
What is an interface?
What do you mean by 'leaky abstractions' - not written by me.
Picture Attribution.
In object oriented design, the amount of coupling refers to how much the design of one class depends on the design of another class. In other words, how often do changes in class A force related changes in class B? Tight coupling means the two classes often change together, loose coupling means they are mostly independent. In general, loose coupling is recommended because it's easier to test and maintain.
You may find this paper by Martin Fowler (PDF) helpful.
In general Tight Coupling is bad in but most of the time, because it reduces flexibility and re-usability of code, it makes changes much more difficult, it impedes testability etc.
Tightly Coupled Object is an object need to know quite a bit about each other and are usually highly dependent on each other interfaces. Changing one object in a tightly coupled application often requires changes to a number of other objects, In small application we can easily identify the changes and there is less chance to miss anything. But in large applications these inter-dependencies are not always known by every programmer or chance is there to miss changes. But each set of loosely coupled objects are not dependent on others.
In short we can say, loose coupling is a design goal that seeks to reduce the interdependencies between components of a system with the goal of reducing the risk that changes in one component will require changes in any other component. Loose coupling is a much more generic concept intended to increase the flexibility of a system, make it more maintainable, and make the entire framework more 'stable'.
Coupling refers to the degree of direct knowledge that one element has of another. we can say an eg: A and B, only B change its behavior only when A change its behavior. A loosely coupled system can be easily broken down into definable elements.
Tight Coupling means one class is dependent on another class.
Loose Coupling means one class is dependent on interface rather than class.
In tight coupling, there are hard-coded dependency declared in methods.
In loose coupling, we must pass dependency externally at runtime instead of hard-coded. (Loose couple systems use interface for decreased dependency with class.)
For example, we have a system that can send output in two or more ways like JSON output, CSV output, etc.
Tight Coupled
public interface OutputGenerator {
public void generateOutput();
}
public class CSVOutputGenerator implements OutputGenerator {
public void generateOutput() {
System.out.println("CSV Output Generator");
}
}
public class JSONOutputGenerator implements OutputGenerator {
public void generateOutput() {
System.out.println("JSON Output Generator");
}
}
// In Other Code, we write Output Generator like...
public class Class1 {
public void generateOutput() {
// Here Output will be in CSV-Format, because of hard-coded code.
// This method tightly coupled with CSVOutputGenerator class, if we want another Output, we must change this method.
// Any method, that calls Class1's generateOutput will return CSVOutput, because Class1 is tight couple with CSVOutputGenerator.
OutputGenerator outputGenerator = new CSVOutputGenerator();
output.generateOutput();
}
}
In the example above, if we want to change the output in JSON, then we need to find and change in the whole code, because Class1 is tightly coupled with the CSVOutputGenerator class.
Loose Coupled
public interface OutputGenerator {
public void generateOutput();
}
public class CSVOutputGenerator implements OutputGenerator {
public void generateOutput() {
System.out.println("CSV Output Generator");
}
}
public class JSONOutputGenerator implements OutputGenerator {
public void generateOutput() {
System.out.println("JSON Output Generator");
}
}
// In Other Code, we write Output Generator like...
public class Class1 {
public void generateOutput(OutputGenerator outputGenerator) {
// if you want to write JSON, pass object of JSONOutputGenerator (Dependency will be passed externally to this method)
// if you want to write CSV, pass object of CSVOutputGenerator (Dependency will be passed externally to this method)
// Due to loose couple with class, we don't need to change code of Class1, because Class1 is loose coupled with CSVOutputGenerator or JSONOutputGenerator class
// Any method, that calls Class1's generateOutput will desired output, because Class1 does not tight couple with CSVOutputGenerator or JSONOutputGenerator class
OutputGenerator outputGenerator = outputGenerator;
output.generateOutput();
}
}
When two objects are loosely coupled, they can interact but have very little knowledge of
each other.
Loosely coupled designs allow us to build flexible OO systems that can handle change.
Observer design pattern is a good example for making classes loosely coupled, you can have a look on it in Wikipedia.
Loose coupling means that the degree of dependency between two components is very low.
Example: GSM SIM
Tight coupling means that the degree of dependency between two components is very high.
Example: CDMA Mobile
There are a lot of nice answers here using analogies, but a friend at work gave me an example that I liked more than all of the ones mentioned here... Eyes and Glasses!
Tight Coupling
Tight coupling would be the eyes. If I want to fix my vision, it's very expensive to get an eye transplant and holds a fair amount of risk. But what if the designer (being the human race) found a better way. Add a feature that is loosely coupled to the body so it can be easily changed! (yes.. glasses)
Loose coupling
I can easily replace my glasses without breaking my underlying vision. I can take off the glasses and my vision will be how it was before (not better or worse). Using different pairs of glasses changes how we see the world through our eyes with little risk and easy maintainability.
Summary
So next time someone asks you "who cares if my code is tightly-coupled?" The answer is all about effort to change, effort to maintain and risk of change.
So how is this done in C#? Interfaces and Dependency Injection!
EDIT
This is a good example of the Decorator pattern as well, where the eyes are the class we are decorating by meeting interface requirements but giving different functionality (e.g. sunglasses, reading glasses, magnifying glasses for jewelers, etc.)
An extract from my blog post on coupling:
What is Tight Coupling:-
As par above definition a Tightly Coupled Object is an object that needs to know about other objects and are usually highly dependent on each other's interfaces.
When we change one object in a tightly coupled application often it requires changes to a number of other objects. There is no problem in a small application we can easily identify the change. But in the case of a large applications these inter-dependencies are not always known by every consumer or other developers or there is many chance of future changes.
Let’s take a shopping cart demo code to understand the tight coupling:
namespace DNSLooseCoupling
{
public class ShoppingCart
{
public float Price;
public int Quantity;
public float GetRowItemTotal()
{
return Price * Quantity;
}
}
public class ShoppingCartContents
{
public ShoppingCart[] items;
public float GetCartItemsTotal()
{
float cartTotal = 0;
foreach (ShoppingCart item in items)
{
cartTotal += item.GetRowItemTotal();
}
return cartTotal;
}
}
public class Order
{
private ShoppingCartContents cart;
private float salesTax;
public Order(ShoppingCartContents cart, float salesTax)
{
this.cart = cart;
this.salesTax = salesTax;
}
public float OrderTotal()
{
return cart.GetCartItemsTotal() * (2.0f + salesTax);
}
}
}
Problems with the above example
Tight Coupling creates some difficulties.
Here, OrderTotal() methods is give us complete amount for the current items of the carts. If we want to add the discount features in this cart system. It is very hard to do in above code because we have to make changes at every class as it is very tightly coupled.
The way I understand it is, that tightly coupled architecture does not provide a lot of flexibility for change when compared to loosely coupled architecture.
But in case of loosely coupled architectures, message formats or operating platforms or revamping the business logic does not impact the other end. If the system is taken down for a revamp, of course the other end will not be able to access the service for a while but other than that, the unchanged end can resume message exchange as it was before the revamp.
There are certain tools that provide dependency injection through their library, for example in .net we have ninject Library .
If you are going further in java then spring provides this capabilities.
Loosly coupled objects can be made by introducing Interfaces in your code, thats what these sources do.
Say in your code you are writing
Myclass m = new Myclass();
now this statement in your method says that you are dependent on myclass this is called a tightly coupled. Now you provide some constructor injection , or property injection and instantiating object then it will become loosly coupled.
It's about classes dependency rate to another ones which is so low in loosely coupled and so high in tightly coupled. To be clear in the service orientation architecture, services are loosely coupled to each other against monolithic which classes dependency to each other is on purpose
Loose coupling is and answer to to old style hardcoded dependencies and related issues issues like frequent recompilation when anything changes and code reuse. It stresses on implementing the worker logic in components and avoiding solution specific wire up code there.
Loose Coupling = IoC
See this for easier explanation.
Loose Coupling is the process of giving the dependency your class needs indirectly without providing all the information of the dependency(i.e in the from of interface) in case tight coupling you directly give in the dependency which is not good way of coding.
If an object's creation/existence dependents on another object which can't be tailored, its tight coupling. And, if the dependency can be tailored, its loose coupling. Consider an example in Java:
class Car {
private Engine engine = new Engine( "X_COMPANY" ); // this car is being created with "X_COMPANY" engine
// Other parts
public Car() {
// implemenation
}
}
The client of Car class can create one with ONLY "X_COMPANY" engine.
Consider breaking this coupling with ability to change that:
class Car {
private Engine engine;
// Other members
public Car( Engine engine ) { // this car can be created with any Engine type
this.engine = engine;
}
}
Now, a Car is not dependent on an engine of "X_COMPANY" as it can be created with types.
A Java specific note: using Java interfaces just for de-coupling sake is not a proper desing approach. In Java, an interface has a purpose - to act as a contract which intrisically provides de-coupling behavior/advantage.
Bill Rosmus's comment in accepted answer has a good explanation.
Loose and Tight coupling is about dependency one program component from another. This means dependency not only with programming class, it is about programming system components at all.
For example if you use only simple raw SQL Query to receive data from SQL Server this is Loose coupling. The opposite of Loose Coupling and simple raw SQL Query is Tight Coupling and Entity Framework Core. In Entity Framework Core you have to full model with POCO class in your code reflect database structure, than means any changing in database you have to reflect in code.
So, Tight Coupling between program code and database structure is Entity Framework, the opposite of this approach is refuse to use any ORM and refuse to have full mirror database structures in your program code.
The Open/Closed Principle states that software entities (classes, modules, etc.) should be open for extension, but closed for modification. What does this mean, and why is it an important principle of good object-oriented design?
It means that you should put new code in new classes/modules. Existing code should be modified only for bug fixing. New classes can reuse existing code via inheritance.
Open/closed principle is intended to mitigate risk when introducing new functionality. Since you don't modify existing code you can be assured that it wouldn't be broken. It reduces maintenance cost and increases product stability.
Specifically, it is about a "Holy Grail" of design in OOP of making an entity extensible enough (through its individual design or through its participation in the architecture) to support future unforseen changes without rewriting its code (and sometimes even without re-compiling **).
Some ways to do this include Polymorphism/Inheritance, Composition, Inversion of Control (a.k.a. DIP), Aspect-Oriented Programming, Patterns such as Strategy, Visitor, Template Method, and many other principles, patterns, and techniques of OOAD.
** See the 6 "package principles", REP, CCP, CRP, ADP, SDP, SAP
More specifically than DaveK, it usually means that if you want to add additional functionality, or change the functionality of a class, create a subclass instead of changing the original. This way, anyone using the parent class does not have to worry about it changing later on. Basically, it's all about backwards compatibility.
Another really important principle of object-oriented design is loose coupling through a method interface. If the change you want to make does not affect the existing interface, it really is pretty safe to change. For example, to make an algorithm more efficient. Object-oriented principles need to be tempered by common sense too :)
Open Closed Principle is very important in object oriented programming and it's one of the SOLID principles.
As per this, a class should be open for extension and closed for
modification. Let us understand why.
class Rectangle {
public int width;
public int lenth;
}
class Circle {
public int radius;
}
class AreaService {
public int areaForRectangle(Rectangle rectangle) {
return rectangle.width * rectangle.lenth;
}
public int areaForCircle(Circle circle) {
return (22 / 7) * circle.radius * circle.radius;
}
}
If you look at the above design, we can clearly observe that it's not
following Open/Closed Principle. Whenever there is a new
shape(Tiangle, Square etc.), AreaService has to be modified.
With Open/Closed Principle:
interface Shape{
int area();
}
class Rectangle implements Shape{
public int width;
public int lenth;
#Override
public int area() {
return lenth * width;
}
}
class Cirle implements Shape{
public int radius;
#Override
public int area() {
return (22/7) * radius * radius;
}
}
class AreaService {
int area(Shape shape) {
return shape.area();
}
}
Whenever there is new shape like Triangle, Square etc. you can easily
accommodate the new shapes without modifying existing classes. With
this design, we can ensure that existing code doesn't impact.
Software entities should be open for extension but closed for modification
That means any class or module should be written in a way that it can be used as is, can be extended, but neve modified
Bad Example in Javascript
var juiceTypes = ['Mango','Apple','Lemon'];
function juiceMaker(type){
if(juiceTypes.indexOf(type)!=-1)
console.log('Here is your juice, Have a nice day');
else
console.log('sorry, Error happned');
}
exports.makeJuice = juiceMaker;
Now if you want to add Another Juice type, you have to edit the module itself, By this way, we are breaking OCP .
Good Example in Javascript
var juiceTypes = [];
function juiceMaker(type){
if(juiceTypes.indexOf(type)!=-1)
console.log('Here is your juice, Have a nice day');
else
console.log('sorry, Error happned');
}
function addType(typeName){
if(juiceTypes.indexOf(typeName)==-1)
juiceTypes.push(typeName);
}
function removeType(typeName){
let index = juiceTypes.indexOf(typeName)
if(index!==-1)
juiceTypes.splice(index,1);
}
exports.makeJuice = juiceMaker;
exports.addType = addType;
exports.removeType = removeType;
Now, you can add new juice types from outside the module without editing the same module.
Let's break down the question in three parts to make it easier to understand the various concepts.
Reasoning Behind Open-Closed Principle
Consider an example in the code below. Different vehicles are serviced in a different manner. So, we have different classes for Bike and Car because the strategy to service a Bike is different from the strategy to service a Car. The Garage class accepts various kinds of vehicles for servicing.
Problem of Rigidity
Observe the code and see how the Garage class shows the signs of rigidity when it comes to introducing a new functionality:
class Bike {
public void service() {
System.out.println("Bike servicing strategy performed.");
}
}
class Car {
public void service() {
System.out.println("Car servicing strategy performed.");
}
}
class Garage {
public void serviceBike(Bike bike) {
bike.service();
}
public void serviceCar(Car car) {
car.service();
}
}
As you may have noticed, whenever some new vehicle like Truck or Bus is to be serviced, the Garage will need to be modified to define some new methods like serviceTruck() and serviceBus(). That means the Garage class must know every possible vehicle like Bike, Car, Bus, Truck and so on. So, it violates the open-closed principle by being open for modification. Also it's not open for extension because to extend the new functionality, we need to modify the class.
Meaning Behind Open-Closed Principle
Abstraction
To solve the problem of rigidity in the code above we can use the open-closed principle. That means we need to make the Garage class dumb by taking away the implementation details of servicing of every vehicle that it knows. In other words we should abstract the implementation details of the servicing strategy for each concrete type like Bike and Car.
To abstract the implementation details of the servicing strategies for various types of vehicles we use an interface called Vehicle and have an abstract method service() in it.
Polymorphism
At the same time, we also want the Garage class to accept many forms of the vehicle, like Bus, Truck and so on, not just Bike and Car. To do that, the open-closed principle uses polymorphism (many forms).
For the Garage class to accept many forms of the Vehicle, we change the signature of its method to service(Vehicle vehicle) { } to accept the interface Vehicle instead of the actual implementation like Bike, Car etc. We also remove the multiple methods from the class as just one method will accept many forms.
interface Vehicle {
void service();
}
class Bike implements Vehicle {
#Override
public void service() {
System.out.println("Bike servicing strategy performed.");
}
}
class Car implements Vehicle {
#Override
public void service() {
System.out.println("Car servicing strategy performed.");
}
}
class Garage {
public void service(Vehicle vehicle) {
vehicle.service();
}
}
Importance of Open-Closed Principle
Closed for modification
As you can see in the code above, now the Garage class has become closed for modification because now it doesn't know about the implementation details of servicing strategies for various types of vehicles and can accept any type of new Vehicle. We just have to extend the new vehicle from the Vehicle interface and send it to the Garage. That's it! We don't need to change any code in the Garage class.
Another entity that's closed for modification is our Vehicle interface.
We don't have to change the interface to extend the functionality of our software.
Open for extension
The Garage class now becomes open for extension in the context that it will support the new types of Vehicle, without the need for modifying.
Our Vehicle interface is open for extension because to introduce any new vehicle, we can extend from the Vehicle interface and provide a new implementation with a strategy for servicing that particular vehicle.
Strategy Design Pattern
Did you notice that I used the word strategy multiple times? That's because this is also an example of the Strategy Design Pattern. We can implement different strategies for servicing different types of Vehicles by extending it. For example, servicing a Truck has a different strategy from the strategy of servicing a Bus. So we implement these strategies inside the different derived classes.
The strategy pattern allows our software to be flexible as the requirements change over time. Whenever the client changes their strategy, just derive a new class for it and provide it to the existing component, no need to change other stuff! The open-closed principle plays an important role in implementing this pattern.
That's it! Hope that helps.
It's the answer to the fragile base class problem, which says that seemingly innocent modifications to base classes may have unintended consequences to inheritors that depended on the previous behavior. So you have to be careful to encapsulate what you don't want relied upon so that the derived classes will obey the contracts defined by the base class. And once inheritors exist, you have to be really careful with what you change in the base class.
Purpose of the Open closed Principle in SOLID Principles is to
reduce the cost of a business change requirement.
reduce testing of existing code.
Open Closed Principle states that we should try not to alter existing
code while adding new functionalities. It basically means that
existing code should be open for extension and closed for
modification(unless there is a bug in existing code). Altering existing code while adding new functionalities requires existing features to be tested again.
Let me explain this by taking AppLogger util class.
Let's say we have a requirement to log application wide errors to a online tool called Firebase. So we create below class and use it in 1000s of places to log API errors, out of memory errors etc.
open class AppLogger {
open fun logError(message: String) {
// reporting error to Firebase
FirebaseAnalytics.logException(message)
}
}
Let's say after sometime, we add Payment Feature to the app and there is a new requirement which states that only for Payment related errors we have to use a new reporting tool called Instabug and also continue reporting errors to Firebase just like before for all features including Payment.
Now we can achieve this by putting an if else condition inside our existing method
fun logError(message: String, origin: String) {
if (origin == "Payment") {
//report to both Firebase and Instabug
FirebaseAnalytics.logException(message)
InstaBug.logException(message)
} else {
// otherwise report only to Firebase
FirebaseAnalytics.logException(message)
}
}
Problem with this approach is that it violates Single Responsibility Principle which states that a method should do only one thing. Another way of putting it is a method should have only one reason to change. With this approach there are two reasons for this method to change (if & else blocks).
A better approach would be to create a new Logger class by inheriting the existing Logger class like below.
class InstaBugLogger : AppLogger() {
override fun logError(message: String) {
super.logError(message) // This uses AppLogger.logError to report to Firebase.
InstaBug.logException(message) //Reporting to Instabug
}
}
Now all we have to do is use InstaBugLogger.logError() in Payment features to log errors to both Instabug and Firebase. This way we reduce/isolate the testing of new error reporting requirement to only Payment feature as code changes are done only in Payment Feature. The rest of the application features need not be tested as there are no code changes done to the existing Logger.
The principle means that it should easy to add new functionality without having to change existing, stable, and tested functionality, saving both time and money.
Often, polymorhism, for instance using interfaces, is a good tool for achieving this.
An additional rule of thumb for conforming to OCP is to make base classes abstract with respect to functionality provided by derived classes. Or as Scott Meyers says 'Make Non-leaf classes abstract'.
This means having unimplemented methods in the base class and only implement these methods in classes which themselves have no sub classes. Then the client of the base class cannot rely on a particular implementation in the base class since there is none.
I just want to emphasize that "Open/Closed", even though being obviously useful in OO programming, is a healthy method to use in all aspects of development. For instance, in my own experience it's a great painkiller to use "Open/Closed" as much as possible when working with plain C.
/Robert
This means that the OO software should be built upon, but not changed intrinsically. This is good because it ensures reliable, predictable performance from the base classes.
I was recently given an additional idea of what this principle entails: that the Open-Closed Principle describes at once a way of writing code, as well as an end-result of writing code in a resilient way.
I like to think of Open/Closed split up in two closely-related parts:
Code that is Open to change can either change its behavior to correctly handle its inputs, or requires minimum modification to provide for new usage scenarios.
Code that is Closed for modification does not require much if any human intervention to handle new usage scenarios. The need simply does not exist.
Thus, code that exhibits Open/Closed behavior (or, if you prefer, fulfills the Open/Closed Principle) requires minimal or no modification in response to usage scenarios beyond what it was originally built for.
As far as implementation is concerned? I find that the commonly-stated interpretation, "Open/Closed refers to code being polymorphic!" to be at best an incomplete statement. Polymorphism in code is one tool to achieve this sort of behavior; Inheritance, Implementation...really, every object-oriented design principle is necessary to write code that is resilient in the way implied by this principle.
In Design principle, SOLID – the "O" in "SOLID" stands for the open/closed principle.
Open Closed principle is a design principle which says that a class, modules and functions should be open for extension but closed for modification.
This principle states that the design and writing of the code should be done in a way that new functionality should be added with minimum changes in the existing code (tested code). The design should be done in a way to allow the adding of new functionality as new classes, keeping as much as possible existing code unchanged.
Benefit of Open Closed Design Principle:
Application will be more robust because we are not changing already tested class.
Flexible because we can easily accommodate new requirements.
Easy to test and less error prone.
My blog post on this:
http://javaexplorer03.blogspot.in/2016/12/open-closed-design-principle.html