Object-oriented programming (OOP) is a programming paradigm based on the concept of "objects", which can contain data, in the form of fields (often known as attributes or properties), and code, in the form of procedures (often known as methods). A feature of objects is an object's procedures that can access and often modify the data fields of the object with which they are associated (objects have a notion of "this" or "self"). In OOP, computer programs are designed by making them out of objects that interact with one another. OOP languages are diverse, but the most popular ones are class-based, meaning that objects are instances of classes, which also determine their types.
Many of the most widely used programming languages (such as C++, Java, Python, etc.) are multi-paradigm and they support object-oriented programming to a greater or lesser degree, typically in combination with imperative, procedural programming. Significant object-oriented languages include Java, C++, C#, Python, R, PHP, JavaScript, Ruby, Perl, Object Pascal, Objective-C, Dart, Swift, Scala, Kotlin, Common Lisp, MATLAB, and Smalltalk.
Features
Object-oriented
programming uses objects, but not all of the associated techniques and
structures are supported directly in languages that claim to support
OOP. The features listed below are common among languages considered to
be strongly class- and object-oriented (or multi-paradigm with OOP support), with notable exceptions mentioned.
- 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.
Objects and classes
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".
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.
Object-oriented programming is more than just classes and objects; it's a whole programming paradigm based around [sic] objects
(data structures) that contain data fields and methods. It is essential
to understand this; using classes to organize a bunch of unrelated
methods together is not object orientation.
Junade Ali, Mastering PHP Design Patterns
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 one
- 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 only to 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, a significantly different
yet analogous terminology is used to define the concepts of object and instance.
Class-based vs prototype-based
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 doesn't 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.
Dynamic dispatch/message passing
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, and distinguishes an object from an abstract data type
(or module), which has a fixed (static) implementation of the
operations for all instances. 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.
Encapsulation
Encapsulation
is an object-oriented programming concept that binds together the data
and functions that manipulate the data, and that keeps both safe from
outside interference and misuse. Data encapsulation led to the important
OOP concept of data hiding.
If a class does not allow calling code to access internal object
data and permits access through methods only, this is a strong form of
abstraction or information hiding known as encapsulation.
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. 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). In other languages (like Python) this is
enforced only by convention (for example, private methods may have names that start with an underscore). 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.
Composition, inheritance, and delegation
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.
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 don't share a common parent.
Abstract classes
cannot be instantiated into objects; they exist only for the purpose of
inheritance into other "concrete" classes which can be instantiated.
In Java, the
final keyword can be used to prevent a class from being subclassed.
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.
Polymorphism
Subtyping – a form of polymorphism
– is when calling code can be agnostic as to 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 which simplifies code external to the class hierarchy and enables strong separation of concerns.
Open recursion
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.
History
Terminology invoking "objects" and "oriented" in the modern sense of object-oriented programming made its first appearance at MIT in the late 1950s and early 1960s. In the environment of the artificial intelligence group, as early as 1960, "object" could refer to identified items (LISP atoms) with properties (attributes);
Alan Kay was later to cite a detailed understanding of LISP internals as a strong influence on his thinking in 1966:
I thought of objects
being like biological cells and/or individual computers on a network,
only able to communicate with messages (so messaging came at the very
beginning – it took a while to see how to do messaging in a programming
language efficiently enough to be useful).
Alan Kay
Another early MIT example was Sketchpad created by Ivan Sutherland
in 1960–61; in the glossary of the 1963 technical report based on his
dissertation about Sketchpad, Sutherland defined notions of "object" and
"instance" (with the class concept covered by "master" or
"definition"), albeit specialized to graphical interaction.
Also, an MIT ALGOL
version, AED-0, established a direct link between data structures
("plexes", in that dialect) and procedures, prefiguring what were later
termed "messages", "methods", and "member functions".
In the 1960s, object-oriented programming was put into practice with the Simula language, which introduced important concepts that are today an essential part of object-oriented programming, such as class and object, inheritance, and dynamic binding. Simula was also designed to take account of programming and data security. For programming security purposes a detection process was implemented so that through reference counts a last resort garbage collector deleted unused objects in the random-access memory (RAM). But although the idea of data objects had already been established by 1965, data encapsulation through levels of scope for variables,
such as private (-) and public (+), were not implemented in Simula
because it would have required the accessing procedures to be also
hidden.
In 1962, Kristen Nygaard initiated a project for a simulation language at the Norwegian Computing Center, based on his previous use of the Monte Carlo simulation and his work to conceptualise real-world systems. Ole-Johan Dahl formally joined the project and the Simula programming language was designed to run on the Universal Automatic Computer (UNIVAC) 1107. In the early stages Simula was supposed to be a procedure package for the programming language ALGOL
60. Dissatisfied with the restrictions imposed by ALGOL the
researchers decided to develop Simula into a fully-fledged programming
language, which used the UNIVAC ALGOL 60 compiler. Simula launched in
1964, and was promoted by Dahl and Nygaard throughout 1965 and 1966,
leading to increasing use of the programming language in Sweden, Germany
and the Soviet Union. In 1968, the language became widely available through the Burroughs B5500 computers, and was later also implemented on the URAL-16 computer. In 1966, Dahl and Nygaard wrote a Simula compiler. They became preoccupied with putting into practice Tony Hoare's record class concept, which had been implemented in the free-form, English-like general-purpose simulation language SIMSCRIPT.
They settled for a generalised process concept with record class
properties, and a second layer of prefixes. Through prefixing a process
could reference its predecessor and have additional properties. Simula
thus introduced the class and subclass hierarchy, and the possibility of
generating objects from these classes. The Simula 1 compiler and a new
version of the programming language, Simula 67, was introduced to the
wider world through the research paper "Class and Subclass Declarations"
at a 1967 conference.
A Simula 67 compiler was launched for the System/360 and System/370 IBM mainframe computers in 1972. In the same year a Simula 67 compiler was launched free of charge for the French CII 10070 and CII Iris 80 mainframe computers.
By 1974, the Association of Simula Users had members in 23 different
countries. Early 1975 a Simula 67 compiler was released free of charge
for the DECsystem-10
mainframe family. By August the same year the DECsystem-10 Simula 67
compiler had been installed at 28 sites, 22 of them in North America.
The object-oriented Simula programming language was used mainly by
researchers involved with physical modelling, such as models to study and improve the movement of ships and their content through cargo ports.
In the 1970s, the first version of the Smalltalk programming language was developed at Xerox PARC by Alan Kay, Dan Ingalls and Adele Goldberg. Smaltalk-72 included a programming environment and was dynamically typed, and at first was interpreted, not compiled.
Smalltalk got noted for its application of object orientation at the
language level and its graphical development environment. Smalltalk went
through various versions and interest in the language grew.
While Smalltalk was influenced by the ideas introduced in Simula 67 it
was designed to be a fully dynamic system in which classes could be
created and modified dynamically.
In the 1970s, Smalltalk influenced the Lisp community to incorporate object-based techniques that were introduced to developers via the Lisp machine. Experimentation with various extensions to Lisp (such as LOOPS and Flavors introducing multiple inheritance and mixins) eventually led to the Common Lisp Object System, which integrates functional programming and object-oriented programming and allows extension via a Meta-object protocol.
In the 1980s, there were a few attempts to design processor
architectures that included hardware support for objects in memory but
these were not successful. Examples include the Intel iAPX 432 and the Linn Smart Rekursiv.
In 1981, Goldberg edited the August 1981 issue of Byte Magazine, introducing Smalltalk and object-oriented programming to a wider audience. In 1986, the Association for Computing Machinery organised the first Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA), which was unexpectedly attended by 1,000 people. In the mid-1980s Objective-C was developed by Brad Cox, who had used Smalltalk at ITT Inc., and Bjarne Stroustrup, who had used Simula for his PhD thesis, eventually went to create the object-oriented C++. In 1985, Bertrand Meyer also produced the first design of the Eiffel language.
Focused on software quality, Eiffel is a purely object-oriented
programming language and a notation supporting the entire software
lifecycle. Meyer described the Eiffel software development method, based
on a small number of key ideas from software engineering and computer
science, in Object-Oriented Software Construction. Essential to the quality focus of Eiffel is Meyer's reliability mechanism, Design by Contract, which is an integral part of both the method and language.
The TIOBE programming language popularity index graph from 2002 to 2018. In the 2000s the object-oriented Java (blue) and the procedural C (black) competed for the top position.
In the early and mid-1990s object-oriented programming developed as the dominant programming paradigm when programming languages supporting the techniques became widely available. These included Visual FoxPro 3.0, C++, and Delphi. Its dominance was further enhanced by the rising popularity o graphical user interfaces,
which rely heavily upon object-oriented programming techniques. An
example of a closely related dynamic GUI library and OOP language can be
found in the Cocoa frameworks on Mac OS X, written in Objective-C, an object-oriented, dynamic messaging extension to C based on Smalltalk. OOP toolkits also enhanced the popularity of event-driven programming (although this concept is not limited to OOP).
At ETH Zürich, Niklaus Wirth and his colleagues had also been investigating such topics as data abstraction and modular programming (although this had been in common use in the 1960s or earlier). Modula-2 (1978) included both, and their succeeding design, Oberon, included a distinctive approach to object orientation, classes, and such.
Object-oriented features have been added to many previously existing languages, including Ada, BASIC, Fortran, Pascal, and COBOL.
Adding these features to languages that were not initially designed for
them often led to problems with compatibility and maintainability of
code.
More recently, a number of languages have emerged that are
primarily object-oriented, but that are also compatible with procedural
methodology. Two such languages are Python and Ruby. Probably the most commercially important recent object-oriented languages are Java, developed by Sun Microsystems, as well as C# and Visual Basic.NET (VB.NET), both designed for Microsoft's .NET
platform. Each of these two frameworks shows, in its own way, the
benefit of using OOP by creating an abstraction from implementation.
VB.NET and C# support cross-language inheritance, allowing classes
defined in one language to subclass classes defined in the other
language.
OOP languages
Simula
(1967) is generally accepted as being the first language with the
primary features of an object-oriented language. It was created for
making simulation programs, in which what came to be called objects were the most important information representation. Smalltalk
(1972 to 1980) is another early example, and the one with which much of
the theory of OOP was developed. Concerning the degree of object
orientation, the following distinctions can be made:
- Languages called "pure" OO languages, because everything in them is treated consistently as an object, from primitives such as characters and punctuation, all the way up to whole classes, prototypes, blocks, modules, etc. They were designed specifically to facilitate, even enforce, OO methods. Examples: Python, Ruby, Scala, Smalltalk, Eiffel, Emerald, JADE, Self, Raku.
- Languages designed mainly for OO programming, but with some procedural elements. Examples: Java, C++, C#, Delphi/Object Pascal, VB.NET.
- Languages that are historically procedural languages, but have been extended with some OO features. Examples: PHP, Perl, Visual Basic (derived from BASIC), MATLAB, COBOL 2002, Fortran 2003, ABAP, Ada 95, Pascal.
- Languages with most of the features of objects (classes, methods, inheritance), but in a distinctly original form. Examples: Oberon (Oberon-1 or Oberon-2).
- Languages with abstract data type support which may be used to resemble OO programming, but without all features of object-orientation. This includes object-based and prototype-based languages. Examples: JavaScript, Lua, Modula-2, CLU.
- Chameleon languages that support multiple paradigms, including OO. Tcl stands out among these for TclOO, a hybrid object system that supports both prototype-based programming and class-based OO.
OOP in dynamic languages
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.
OOP in a network protocol
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 AS/400 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).
Design patterns
Challenges of object-oriented design are addressed by several approaches. Most common is known as the design patterns codified by Gamma et al.. More broadly, the term "design patterns"
can be used to refer to any general, repeatable, solution pattern to a
commonly occurring problem in software design. Some of these commonly
occurring problems have implications and solutions particular to
object-oriented development.
Inheritance and behavioral subtyping
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.
Gang of Four design patterns
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.
As of April 2007, the book was in its 36th printing.
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
Object-orientation and databases
Both object-oriented programming and relational database management systems (RDBMSs) are extremely common in software today. Since relational databases
don't 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. 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.
Real-world modeling and relationships
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
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.
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" (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). This problem may cause OOP to suffer more convoluted solutions than procedural programming.
OOP and control flow
OOP was developed to increase the reusability and maintainability of source code. 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.
Responsibility- vs. data-driven design
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 and GRASP guidelines
SOLID is a mnemonic invented by Michael Feathers that stands for and advocates five programming practices:
- 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.
Criticism
The
OOP paradigm has been criticised for a number of reasons, including not
meeting its stated goals of reusability and modularity,
and for overemphasizing one aspect of software design and modeling
(data/objects) at the expense of other important aspects
(computation/algorithms).
Luca Cardelli
has claimed that OOP code is "intrinsically less efficient" than
procedural code, that OOP can take longer to compile, and that OOP
languages have "extremely poor modularity properties with respect to
class extension and modification", and tend to be extremely complex. The latter point is reiterated by Joe Armstrong, the principal inventor of Erlang, who is quoted as saying:
The problem with object-oriented languages is they've got all this implicit environment that they carry around with them. You wanted a banana but what you got was a gorilla holding the banana and the entire jungle.
A study by Potok et al. has shown no significant difference in productivity between OOP and procedural approaches.
Christopher J. Date
stated that critical comparison of OOP to other technologies,
relational in particular, is difficult because of lack of an agreed-upon
and rigorous definition of OOP; however, Date and Darwen have proposed a theoretical foundation on OOP that uses OOP as a kind of customizable type system to support RDBMS.
In an article Lawrence Krubner claimed that compared to other
languages (LISP dialects, functional languages, etc.) OOP languages have
no unique strengths, and inflict a heavy burden of unneeded complexity.
Alexander Stepanov compares object orientation unfavourably to generic programming:
I find OOP technically unsound. It attempts to decompose the world in terms of interfaces that vary on a single type. To deal with the real problems you need multisorted algebras — families of interfaces that span multiple types. I find OOP philosophically unsound. It claims that everything is an object. Even if it is true it is not very interesting — saying that everything is an object is saying nothing at all.
Paul Graham
has suggested that OOP's popularity within large companies is due to
"large (and frequently changing) groups of mediocre programmers".
According to Graham, the discipline imposed by OOP prevents any one
programmer from "doing too much damage".
Leo Brodie has suggested a connection between the standalone nature of objects and a tendency to duplicate code in violation of the don't repeat yourself principle of software development.
Steve Yegge noted that, as opposed to functional programming:
Object Oriented Programming puts the Nouns first and foremost. Why would you go to such lengths to put one part of speech on a pedestal? Why should one kind of concept take precedence over another? It's not as if OOP has suddenly made verbs less important in the way we actually think. It's a strangely skewed perspective.
Rich Hickey, creator of Clojure,
described object systems as overly simplistic models of the real world.
He emphasized the inability of OOP to model time properly, which is
getting increasingly problematic as software systems become more
concurrent.
Eric S. Raymond, a Unix programmer and open-source software
advocate, has been critical of claims that present object-oriented
programming as the "One True Solution", and has written that
object-oriented programming languages tend to encourage thickly layered
programs that destroy transparency. Raymond compares this unfavourably to the approach taken with Unix and the C programming language.
Rob Pike, a programmer involved in the creation of UTF-8 and Go, has called object-oriented programming "the Roman numerals of computing" and has said that OOP languages frequently shift the focus from data structures and algorithms to types. Furthermore, he cites an instance of a Java professor whose "idiomatic" solution to a problem was to create six new classes, rather than to simply use a lookup table.
Formal semantics
Objects are the run-time entities in an object-oriented system. They
may represent a person, a place, a bank account, a table of data, or any
item that the program has to handle.
There have been several attempts at formalizing the concepts used
in object-oriented programming. The following concepts and constructs
have been used as interpretations of OOP concepts:
- co algebraic data types
- abstract data types (which have existential types) allow the definition of modules but these do not support dynamic dispatch
- recursive types
- encapsulated state
- inheritance
- records are basis for understanding objects if function literals can be stored in fields (like in functional-programming languages), but the actual calculi need be considerably more complex to incorporate essential features of OOP. Several extensions of System F<: sub=""> that deal with mutable objects have been studied; these allow both subtype polymorphism and parametric polymorphism (generics)
Attempts to find a consensus definition or theory behind objects have
not proven very successful (however, see Abadi & Cardelli, A Theory of Objects
for formal definitions of many OOP concepts and constructs), and often
diverge widely. For example, some definitions focus on mental
activities, and some on program structuring. One of the simpler
definitions is that OOP is the act of using "map" data structures or
arrays that can contain functions and pointers to other maps, all with
some syntactic and scoping sugar on top. Inheritance can be performed by cloning the maps (sometimes called "prototyping").
