Object-oriented programming

• Variables that can store information formatted in a small number of built-in data types like integers and alphanumeric characters. This may include data structures like strings, lists, and hash tables that are either built-in or result from combining variables using memory pointers.
• Procedures – also known as functions, methods, routines, or subroutines – that take input, generate output, and manipulate data. Modern languages include structured programming constructs like loops and conditionals.

Modular programming support provides the ability to group procedures into files and modules for organizational purposes. Modules are namespaced so identifiers in one module will not conflict with a procedure or variable sharing the same name in another file or module.

Languages that support object-oriented programming (OOP) typically use inheritance for code reuse and extensibility in the form of either classes or prototypes. Those that use classes support two main concepts:

• Classes – the definitions for the data format and available procedures for a given type or class of object; may also contain data and procedures (known as class methods) themselves, i.e. classes contain the data members and member functions
• Objects – instances of classes

Objects sometimes correspond to things found in the real world. For example, a graphics program may have objects such as "circle", "square", "menu". An online shopping system might have objects such as "shopping cart", "customer", and "product".[23] Sometimes objects represent more abstract entities, like an object that represents an open file, or an object that provides the service of translating measurements from U.S. customary to metric.

Each object is said to be an instance of a particular class (for example, an object with its name field set to "Mary" might be an instance of class Employee). Procedures in object-oriented programming are known as methods; variables are also known as fields, members, attributes, or properties. This leads to the following terms:

• Class variables – belong to the class as a whole; there is only one copy of each variable, shared across all instances of the class
• Instance variables or attributes – data that belongs to individual objects; every object has its own copy of each one
• Member variables – refers to both the class and instance variables that are defined by a particular class
• Class methods – belong to the class as a whole and have access to only class variables and inputs from the procedure call
• Instance methods – belong to individual objects, and have access to instance variables for the specific object they are called on, inputs, and class variables

Objects are accessed somewhat like variables with complex internal structure, and in many languages are effectively pointers, serving as actual references to a single instance of said object in memory within a heap or stack. They provide a layer of abstraction which can be used to separate internal from external code. External code can use an object by calling a specific instance method with a certain set of input parameters, read an instance variable, or write to an instance variable. Objects are created by calling a special type of method in the class known as a constructor. A program may create many instances of the same class as it runs, which operate independently. This is an easy way for the same procedures to be used on different sets of data.

Object-oriented programming that uses classes is sometimes called class-based programming, while prototype-based programming does not typically use classes. As a result, significantly different yet analogous terminology is used to define the concepts of object and instance.

In some languages classes and objects can be composed using other concepts like traits and mixins.

In class-based languages the classes are defined beforehand and the objects are instantiated based on the classes. If two objects apple and orange are instantiated from the class Fruit, they are inherently fruits and it is guaranteed that you may handle them in the same way; e.g. a programmer can expect the existence of the same attributes such as color or sugar_content or is_ripe.

In prototype-based languages the objects are the primary entities. No classes even exist. The prototype of an object is just another object to which the object is linked. Every object has one prototype link (and only one). New objects can be created based on already existing objects chosen as their prototype. You may call two different objects apple and orange a fruit, if the object fruit exists, and both apple and orange have fruit as their prototype. The idea of the fruit class does not exist explicitly, but as the equivalence class of the objects sharing the same prototype. The attributes and methods of the prototype are delegated to all the objects of the equivalence class defined by this prototype. The attributes and methods owned individually by the object may not be shared by other objects of the same equivalence class; e.g. the attribute sugar_content may be unexpectedly not present in apple. Only single inheritance can be implemented through the prototype.

It is the responsibility of the object, not any external code, to select the procedural code to execute in response to a method call, typically by looking up the method at run time in a table associated with the object. This feature is known as dynamic dispatch. If the call variability relies on more than the single type of the object on which it is called (i.e. at least one other parameter object is involved in the method choice), one speaks of multiple dispatch.

A method call is also known as message passing. It is conceptualized as a message (the name of the method and its input parameters) being passed to the object for dispatch.

Data abstraction is a design pattern in which data are visible only to semantically related functions, so as to prevent misuse. The success of data abstraction leads to frequent incorporation of data hiding as a design principle in object oriented and pure functional programming.

If a class does not allow calling code to access internal object data and permits access through methods only, this is a form of information hiding known as abstraction. Some languages (Java, for example) let classes enforce access restrictions explicitly, for example denoting internal data with the private keyword and designating methods intended for use by code outside the class with the public keyword.[24] Methods may also be designed public, private, or intermediate levels such as protected (which allows access from the same class and its subclasses, but not objects of a different class).[24] In other languages (like Python) this is enforced only by convention (for example, private methods may have names that start with an underscore). In C#, Swift & Kotlin languages, internal keyword permits access only to files present in same assembly, package or module as that of the class.[25]

Encapsulation prevents external code from being concerned with the internal workings of an object. This facilitates code refactoring, for example allowing the author of the class to change how objects of that class represent their data internally without changing any external code (as long as "public" method calls work the same way). It also encourages programmers to put all the code that is concerned with a certain set of data in the same class, which organizes it for easy comprehension by other programmers. Encapsulation is a technique that encourages decoupling.

Objects can contain other objects in their instance variables; this is known as object composition. For example, an object in the Employee class might contain (either directly or through a pointer) an object in the Address class, in addition to its own instance variables like "first_name" and "position". Object composition is used to represent "has-a" relationships: every employee has an address, so every Employee object has access to a place to store an Address object (either directly embedded within itself, or at a separate location addressed via a pointer).

Languages that support classes almost always support inheritance. This allows classes to be arranged in a hierarchy that represents "is-a-type-of" relationships. For example, class Employee might inherit from class Person. All the data and methods available to the parent class also appear in the child class with the same names. For example, class Person might define variables "first_name" and "last_name" with method "make_full_name()". These will also be available in class Employee, which might add the variables "position" and "salary". This technique allows easy re-use of the same procedures and data definitions, in addition to potentially mirroring real-world relationships in an intuitive way. Rather than utilizing database tables and programming subroutines, the developer utilizes objects the user may be more familiar with: objects from their application domain.[26]

Subclasses can override the methods defined by superclasses. Multiple inheritance is allowed in some languages, though this can make resolving overrides complicated. Some languages have special support for mixins, though in any language with multiple inheritance, a mixin is simply a class that does not represent an is-a-type-of relationship. Mixins are typically used to add the same methods to multiple classes. For example, class UnicodeConversionMixin might provide a method unicode_to_ascii() when included in class FileReader and class WebPageScraper, which do not share a common parent.

Abstract classes cannot be instantiated into objects; they exist only for the purpose of inheritance into other "concrete" classes that can be instantiated. In Java, the final keyword can be used to prevent a class from being subclassed.[27]

The doctrine of composition over inheritance advocates implementing has-a relationships using composition instead of inheritance. For example, instead of inheriting from class Person, class Employee could give each Employee object an internal Person object, which it then has the opportunity to hide from external code even if class Person has many public attributes or methods. Some languages, like Go do not support inheritance at all.

The "open/closed principle" advocates that classes and functions "should be open for extension, but closed for modification".

Delegation is another language feature that can be used as an alternative to inheritance.

Subtyping – a form of polymorphism – is when calling code can be independent of which class in the supported hierarchy it is operating on – the parent class or one of its descendants. Meanwhile, the same operation name among objects in an inheritance hierarchy may behave differently.

For example, objects of type Circle and Square are derived from a common class called Shape. The Draw function for each type of Shape implements what is necessary to draw itself while calling code can remain indifferent to the particular type of Shape being drawn.

This is another type of abstraction that simplifies code external to the class hierarchy and enables strong separation of concerns.

In languages that support open recursion, object methods can call other methods on the same object (including themselves), typically using a special variable or keyword called this or self. This variable is late-bound; it allows a method defined in one class to invoke another method that is defined later, in some subclass thereof.

In recent years, object-oriented programming has become especially popular in dynamic programming languages. Python, PowerShell, Ruby and Groovy are dynamic languages built on OOP principles, while Perl and PHP have been adding object-oriented features since Perl 5 and PHP 4, and ColdFusion since version 6.

The Document Object Model of HTML, XHTML, and XML documents on the Internet has bindings to the popular JavaScript/ECMAScript language. JavaScript is perhaps the best known prototype-based programming language, which employs cloning from prototypes rather than inheriting from a class (contrast to class-based programming). Another scripting language that takes this approach is Lua.

The messages that flow between computers to request services in a client-server environment can be designed as the linearizations of objects defined by class objects known to both the client and the server. For example, a simple linearized object would consist of a length field, a code point identifying the class, and a data value. A more complex example would be a command consisting of the length and code point of the command and values consisting of linearized objects representing the command's parameters. Each such command must be directed by the server to an object whose class (or superclass) recognizes the command and is able to provide the requested service. Clients and servers are best modeled as complex object-oriented structures. Distributed Data Management Architecture (DDM) took this approach and used class objects to define objects at four levels of a formal hierarchy:

• Fields defining the data values that form messages, such as their length, code point and data values.
• Objects and collections of objects similar to what would be found in a Smalltalk program for messages and parameters.
• Managers similar to IBM i Objects, such as a directory to files and files consisting of metadata and records. Managers conceptually provide memory and processing resources for their contained objects.
• A client or server consisting of all the managers necessary to implement a full processing environment, supporting such aspects as directory services, security and concurrency control.

The initial version of DDM defined distributed file services. It was later extended to be the foundation of Distributed Relational Database Architecture (DRDA).

It is intuitive to assume that inheritance creates a semantic "is a" relationship, and thus to infer that objects instantiated from subclasses can always be safely used instead of those instantiated from the superclass. This intuition is unfortunately false in most OOP languages, in particular in all those that allow mutable objects. Subtype polymorphism as enforced by the type checker in OOP languages (with mutable objects) cannot guarantee behavioral subtyping in any context. Behavioral subtyping is undecidable in general, so it cannot be implemented by a program (compiler). Class or object hierarchies must be carefully designed, considering possible incorrect uses that cannot be detected syntactically. This issue is known as the Liskov substitution principle.

Design Patterns: Elements of Reusable Object-Oriented Software is an influential book published in 1994 by Erich Gamma, Richard Helm, Ralph Johnson, and John Vlissides, often referred to humorously as the "Gang of Four". Along with exploring the capabilities and pitfalls of object-oriented programming, it describes 23 common programming problems and patterns for solving them.

The book describes the following patterns:

• Creational patterns (5): Factory method pattern, Abstract factory pattern, Singleton pattern, Builder pattern, Prototype pattern
• Structural patterns (7): Adapter pattern, Bridge pattern, Composite pattern, Decorator pattern, Facade pattern, Flyweight pattern, Proxy pattern
• Behavioral patterns (11): Chain-of-responsibility pattern, Command pattern, Interpreter pattern, Iterator pattern, Mediator pattern, Memento pattern, Observer pattern, State pattern, Strategy pattern, Template method pattern, Visitor pattern

Both object-oriented programming and relational database management systems (RDBMSs) are extremely common in software today. Since relational databases do not store objects directly (though some RDBMSs have object-oriented features to approximate this), there is a general need to bridge the two worlds. The problem of bridging object-oriented programming accesses and data patterns with relational databases is known as object-relational impedance mismatch. There are a number of approaches to cope with this problem, but no general solution without downsides.[29] One of the most common approaches is object-relational mapping, as found in IDE languages such as Visual FoxPro and libraries such as Java Data Objects and Ruby on Rails' ActiveRecord.

There are also object databases that can be used to replace RDBMSs, but these have not been as technically and commercially successful as RDBMSs.

OOP can be used to associate real-world objects and processes with digital counterparts. However, not everyone agrees that OOP facilitates direct real-world mapping (see Criticism section) or that real-world mapping is even a worthy goal; Bertrand Meyer argues in Object-Oriented Software Construction[30] that a program is not a model of the world but a model of some part of the world; "Reality is a cousin twice removed". At the same time, some principal limitations of OOP have been noted.[31] For example, the circle-ellipse problem is difficult to handle using OOP's concept of inheritance.

However, Niklaus Wirth (who popularized the adage now known as Wirth's law: "Software is getting slower more rapidly than hardware becomes faster") said of OOP in his paper, "Good Ideas through the Looking Glass", "This paradigm closely reflects the structure of systems 'in the real world', and it is therefore well suited to model complex systems with complex behaviours"[32] (contrast KISS principle).

Steve Yegge and others noted that natural languages lack the OOP approach of strictly prioritizing things (objects/nouns) before actions (methods/verbs).[33] This problem may cause OOP to suffer more convoluted solutions than procedural programming.[34]

OOP was developed to increase the reusability and maintainability of source code.[35] Transparent representation of the control flow had no priority and was meant to be handled by a compiler. With the increasing relevance of parallel hardware and multithreaded coding, developing transparent control flow becomes more important, something hard to achieve with OOP.[36][37][38][39]

Responsibility-driven design defines classes in terms of a contract, that is, a class should be defined around a responsibility and the information that it shares. This is contrasted by Wirfs-Brock and Wilkerson with data-driven design, where classes are defined around the data-structures that must be held. The authors hold that responsibility-driven design is preferable.

SOLID is a mnemonic invented by Michael Feathers which spells out five software engineering design principles:

• Single responsibility principle
• Open/closed principle
• Liskov substitution principle
• Interface segregation principle
• Dependency inversion principle

GRASP (General Responsibility Assignment Software Patterns) is another set of guidelines advocated by Craig Larman.

• CADES
• Common Object Request Broker Architecture (CORBA)
• Distributed Component Object Model
• Distributed Data Management Architecture
• Jeroo

• IDEF4
• Interface description language
• Lepus3
• UML