Object-oriented programming

 

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Object-oriented programming (OOP) is a programming paradigm using "objects" –i.e. instances of a class consisting of data fields and methods together with their interactions – to design applications and computer programs. Programming techniques may include features such as data abstraction, encapsulation, messaging, modularity, polymorphism, and inheritance. Many modern programming languages now support OOP, at least as an option.

Overview

An object-oriented program may be viewed as a collection of interacting objects, as opposed to the conventional model, in which a program is seen as a list of tasks (subroutines) to perform. In OOP, each object is capable of receiving messages, processing data, and sending messages to other objects. Each object can be viewed as an independent "machine" with a distinct role or responsibility. The actions (or "methods") on these objects are closely associated with the object. For example, OOP data structures tend to "carry their own operators around with them" (or at least "inherit" them from a similar object or class) - except when they have to be serialized.

Simple, non-OOP programs may be one "long" list of statements (or commands). More complex programs will often group smaller sections of these statements into functions or subroutines each of which might perform a particular task. With designs of this sort, it is common for some of the program's data to be 'global', i.e. accessible from any part of the program. As programs grow in size, allowing any function to modify any piece of data means that bugs can have wide-reaching effects.

In contrast, the object-oriented approach encourages the programmer to place data where it is not directly accessible by the rest of the program. Instead, the data is accessed by calling specially written functions, commonly called methods, which are either bundled in with the data or inherited from "class objects." These act as the intermediaries for retrieving or modifying the data they control. The programming construct that combines data with a set of methods for accessing and managing those data is called an object. The practice of using subroutines to examine or modify certain kinds of data was also used in non-OOP modular programming, well before the widespread use of object-oriented programming.

An object-oriented program will usually contain different types of objects, each type corresponding to a particular kind of complex data to be managed or perhaps to a real-world object or concept such as a bank account, a hockey player, or a bulldozer. A program might well contain multiple copies of each type of object, one for each of the real-world objects the program is dealing with. For instance, there could be one bank account object for each real-world account at a particular bank. Each copy of the bank account object would be alike in the methods it offers for manipulating or reading its data, but the data inside each object would differ reflecting the different history of each account.

Objects can be thought of as wrapping their data within a set of functions designed to ensure that the data are used appropriately, and to assist in that use. The object's methods will typically include checks and safeguards that are specific to the types of data the object contains. An object can also offer simple-to-use, standardized methods for performing particular operations on its data, while concealing the specifics of how those tasks are accomplished. In this way alterations can be made to the internal structure or methods of an object without requiring that the rest of the program be modified. This approach can also be used to offer standardized methods across different types of objects. As an example, several different types of objects might offer print methods. Each type of object might implement that print method in a different way, reflecting the different kinds of data each contains, but all the different print methods might be called in the same standardized manner from elsewhere in the program. These features become especially useful when more than one programmer is contributing code to a project or when the goal is to reuse code between projects.

Object-oriented programming has roots that can be traced to the 1960s. As hardware and software became increasingly complex, manageability often became a concern. Researchers studied ways to maintain software quality and developed object-oriented programming in part to address common problems by strongly emphasizing discrete, reusable units of programming logic^{[citation needed]}. The technology focuses on data rather than processes, with programs composed of self-sufficient modules ("classes"), each instance of which ("objects") contains all the information needed to manipulate its own data structure ("members"). This is in contrast to the existing modular programming that had been dominant for many years that focused on the function of a module, rather than specifically the data, but equally provided for code reuse, and self-sufficient reusable units of programming logic, enabling collaboration through the use of linked modules (subroutines).

History

The terms "objects" and "oriented" in something like the modern sense of object-oriented programming seem to make their 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. 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, linked data structures ("plexes", in that dialect) directly with procedures, prefiguring what were later termed "messages", "methods" and "member functions".

Objects as a formal concept in programming were introduced in the 1960s in Simula 67, a major revision of Simula I, a programming language designed for discrete event simulation, created by Ole-Johan Dahl and Kristen Nygaard of the Norwegian Computing Center in Oslo. Simula 67 was influenced by SIMSCRIPT and C.A.R. "Tony" Hoare's proposed "record classes". Simula introduced the notion of classes and instances or objects (as well as subclasses, virtual methods, coroutines, and discrete event simulation) as part of an explicit programming paradigm. The language also used automatic garbage collection that had been invented earlier for the functional programming language Lisp. Simula was used for physical modeling, such as models to study and improve the movement of ships and their content through cargo ports. The ideas of Simula 67 influenced many later languages, including Smalltalk, derivatives of LISP (CLOS), Object Pascal, and C++.

The Smalltalk language, which was developed at Xerox PARC (by Alan Kay and others) in the 1970s, introduced the term object-oriented programming to represent the pervasive use of objects and messages as the basis for computation. Smalltalk creators were influenced by the ideas introduced in Simula 67, but Smalltalk was designed to be a fully dynamic system in which classes could be created and modified dynamically rather than statically as in Simula 67. Smalltalk and with it OOP were introduced to a wider audience by the August 1981 issue of Byte Magazine.

In the 1970s, Kay's Smalltalk work had influenced the Lisp community to incorporate object-based techniques that were introduced to developers via the Lisp machine. Experimentation with various extensions to Lisp (like LOOPS and Flavors introducing multiple inheritance and mixins), eventually led to the Common Lisp Object System (CLOS, a part of the first standardized object-oriented programming language, ANSI Common Lisp), 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.

Object-oriented programming developed as the dominant programming methodology in the early and mid 1990s when programming languages supporting the techniques became widely available. These included Visual FoxPro 3.0, C++^{[citation needed]}, and Delphi^{[citation needed]}. Its dominance was further enhanced by the rising popularity of 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). Some feel that association with GUIs (real or perceived) was what propelled OOP into the programming mainstream.

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. The approach is unlike Smalltalk, and very unlike C++.

Object-oriented features have been added to many existing languages during that time, including Ada, BASIC, Fortran, Pascal, and others. 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 yet compatible with procedural methodology, such as Python and Ruby. Probably the most commercially important recent object-oriented languages are Visual Basic.NET (VB.NET) and C#, both designed for Microsoft's .NET platform, and Java, developed by Sun Microsystems. Both frameworks show the benefit of using OOP by creating an abstraction from implementation in their own way. VB.NET and C# support cross-language inheritance, allowing classes defined in one language to subclass classes defined in the other language. Developers usually compile Java to bytecode, allowing Java to run on any operating system for which a Java virtual machine is available. VB.NET and C# make use of the Strategy pattern to accomplish cross-language inheritance, whereas Java makes use of the Adapter pattern^{[citation needed]}.

Just as procedural programming led to refinements of techniques such as structured programming, modern object-oriented software design methods include refinements^{[citation needed]} such as the use of design patterns, design by contract, and modeling languages (such as UML).

Fundamental features and concepts

See also: List of object-oriented programming terms

A survey by Deborah J. Armstrong of nearly 40 years of computing literature identified a number of "quarks", or fundamental concepts, found in the strong majority of definitions of OOP.

Not all of these concepts are to be found in all object-oriented programming languages. For example, 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.

Benjamin C. Pierce and some other researchers view as futile any attempt to distill OOP to a minimal set of features. He nonetheless identifies fundamental features that support the OOP programming style in most object-oriented languages:

• Dynamic dispatch – when a method is invoked on an object, the object itself determines what code gets executed by looking up the method at run time in a table associated with the object. This feature distinguishes an object from an abstract data type (or module), which has a fixed (static) implementation of the operations for all instances. It is a programming methodology that gives modular component development while at the same time being very efficient.
• Encapsulation (or multi-methods, in which case the state is kept separate)
• Subtype polymorphism
• Object inheritance (or delegation)
• Open recursion – a special variable (syntactically it may be a keyword), usually called this or self, that allows a method body to invoke another method body of the same object. 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.

Similarly, in his 2003 book, Concepts in programming languages, John C. Mitchell identifies four main features: dynamic dispatch, abstraction, subtype polymorphism, and inheritance. Michael Lee Scott in Programming Language Pragmatics considers only encapsulation, inheritance and dynamic dispatch.

Additional concepts used in object-oriented programming include:

• Classes of objects
• Instances of classes
• Methods which act on the attached objects.
• Message passing
• Abstraction

Decoupling

Decoupling refers to careful controls that separate code modules from particular use cases, which increases code re-usability. A common use of decoupling in OOP is to polymorphically decouple the encapsulation (see Bridge pattern and Adapter pattern) - for example, using a method interface which an encapsulated object must satisfy, as opposed to using the object's class.

Formal semantics

See also: Formal semantics of programming languages

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:

• coalgebraic 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_<: 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"). OBJECT:=>> 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.

OOP languages

See also: List of object-oriented programming languages

Simula (1967) is generally accepted as the first language to have 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 arguably the canonical example, and the one with which much of the theory of object-oriented programming 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: Eiffel, Emerald., JADE, Obix, Scala, Smalltalk
• Languages designed mainly for OO programming, but with some procedural elements. Examples: C++, Java, C#, VB.NET, Python.
• Languages that are historically procedural languages, but have been extended with some OO features. Examples: Visual Basic (derived from BASIC), Fortran, Perl, COBOL 2002, PHP, ABAP.
• Languages with most of the features of objects (classes, methods, inheritance, reusability), but in a distinctly original form. Examples: Oberon (Oberon-1 or Oberon-2) and Common Lisp.
• Languages with abstract data type support, but not all features of object-orientation, sometimes called object-based languages. Examples: Modula-2 (with excellent encapsulation and information hiding), Pliant, CLU.

OOP in dynamic languages

In recent years, object-oriented programming has become especially popular in dynamic programming languages. Python, 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 5.

The Document Object Model of HTML, XHTML, and XML documents on the Internet have 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. Another scripting language that takes this approach is Lua. Earlier versions of ActionScript (a partial superset of the ECMA-262 R3, otherwise known as ECMAScript) also used a prototype-based object model. Later versions of ActionScript incorporate a combination of classification and prototype-based object models based largely on the currently incomplete ECMA-262 R4 specification, which has its roots in an early JavaScript 2 Proposal. Microsoft's JScript.NET also includes a mash-up of object models based on the same proposal, and is also a superset of the ECMA-262 R3 specification.

Design patterns

Challenges of object-oriented design are addressed by several methodologies. 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 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

See also: Object oriented design

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 need to 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

Main article: Design pattern (computer science)

Design Patterns: Elements of Reusable Object-Oriented Software is an influential book published in 1995 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

Main articles: Object-Relational impedance mismatch, Object-relational mapping, and Object database

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 libraries like 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 Negative 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 had 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, developer 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.

Criticism

A number of well-known researchers and programmers have analysed the utility of OOP. Here is an incomplete list:

• Luca Cardelli wrote a paper titled "Bad Engineering Properties of Object-Oriented Languages".
• Richard Stallman wrote in 1995, "Adding OOP to Emacs is not clearly an improvement; I used OOP when working on the Lisp Machine window systems, and I disagree with the usual view that it is a superior way to program."
• 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. Date and Darwen propose a theoretical foundation on OOP that uses OOP as a kind of customizable type system to support RDBMS.
• Alexander Stepanov suggested that OOP provides a mathematically limited viewpoint and called it "almost as much of a hoax as Artificial Intelligence. I have yet to see an interesting piece of code that comes from these OO people. In a sense, I am unfair to AI: I learned a lot of stuff from the MIT AI Lab crowd, they have done some really fundamental work....".
• Paul Graham has suggested that the purpose of OOP is to act as a "herding mechanism" that keeps mediocre programmers in mediocre organizations from "doing too much damage". This is at the expense of slowing down productive programmers who know how to use more powerful and more compact techniques.
• Joe Armstrong, the principal inventor of Erlang, 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."
• Richard Mansfield, author and former editor of COMPUTE! magazine, states that "like countless other intellectual fads over the years ("relevance", communism, "modernism", and so on—history is littered with them), OOP will be with us until eventually reality asserts itself. But considering how OOP currently pervades both universities and workplaces, OOP may well prove to be a durable delusion. Entire generations of indoctrinated programmers continue to march out of the academy, committed to OOP and nothing but OOP for the rest of their lives." He also is quoted as saying "OOP is to writing a program, what going through airport security is to flying".
• Steve Yegge, making a roundabout comparison with Functional programming, writes, "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 over 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.
• Carnegie-Mellon University Professor Robert Harper in March 2011 wrote: "This semester Dan Licata and I are co-teaching a new course on functional programming for first-year prospective CS majors... Object-oriented programming is eliminated entirely from the introductory curriculum, because it is both anti-modular and anti-parallel by its very nature, and hence unsuitable for a modern CS curriculum. A proposed new course on object-oriented design methodology will be offered at the sophomore level for those students who wish to study this topic."

See also

• Aspect-oriented programming
• CADES
• Circle-ellipse problem
• Comparison of programming languages (object-oriented programming)
• Comparison of programming paradigms
• Component-based software engineering
• Concurrent object-oriented programming
• Constructor overloading
• CORBA
• DCOM
• Design by contract
• GRASP
• IDEF4
• Interface description language
• Structured programming
• Lepus3
• Modular programming
• Object association
• Object database
• Object-oriented analysis and design
• Object-relational impedance mismatch (and The Third Manifesto)
• Object-relational mapping
• Procedural programming
• Refactoring
• SOLID
• System Object Model
• Visual FoxPro
• ZZT-oop
• Jeroo

Further reading

• [|Weisfeld, Matt] (2009). The Object-Oriented Thought Process, Third Edition. Addison-Wesley. ISBN 0-672-33016-4. 
• Schach, Stephen (2006). Object-Oriented and Classical Software Engineering, Seventh Edition. McGraw-Hill. ISBN 0-07-319126-4. 
• Abadi, Martin; Luca Cardelli (1998). A Theory of Objects. Springer Verlag. ISBN 0-387-94775-2. 
• Abelson, Harold; Gerald Jay Sussman, (1997). Structure and Interpretation of Computer Programs. MIT Press. ISBN 0-262-01153-0. http://mitpress.mit.edu/sicp/. 
• Armstrong, Deborah J. (February 2006). "The Quarks of Object-Oriented Development". Communications of the ACM 49 (2): 123–128. doi:10.1145/1113034.1113040. ISSN 0001-0782. http://portal.acm.org/citation.cfm?id=1113040. Retrieved 8 August 2006. 
• Booch, Grady (1997). Object-Oriented Analysis and Design with Applications. Addison-Wesley. ISBN 0-8053-5340-2. 
• Eeles, Peter; Oliver Sims (1998). Building Business Objects. John Wiley & Sons. ISBN 0-471-19176-0. 
• Gamma, Erich; Richard Helm, Ralph Johnson, John Vlissides (1995). Design Patterns: Elements of Reusable Object Oriented Software. Addison-Wesley. ISBN 0-201-63361-2. 
• Harmon, Paul; William Morrissey (1996). The Object Technology Casebook - Lessons from Award-Winning Business Applications. John Wiley & Sons. ISBN 0-471-14717-6. 
• Jacobson, Ivar (1992). Object-Oriented Software Engineering: A Use Case-Driven Approach. Addison-Wesley. ISBN 0-201-54435-0. 
• Kay, Alan. The Early History of Smalltalk. http://gagne.homedns.org/~tgagne/contrib/EarlyHistoryST.html. 
• Meyer, Bertrand (1997). Object-Oriented Software Construction. Prentice Hall. ISBN 0-13-629155-4. 
• Rumbaugh, James; Michael Blaha, William Premerlani, Frederick Eddy, William Lorensen (1991). Object-Oriented Modeling and Design. Prentice Hall. ISBN 0-13-629841-9. 
• Taylor, David A. (1992). Object-Oriented Information Systems - Planning and Implementation. John Wiley & Sons. ISBN 0-471-54364-0. 
• Schreiner, Axel-Tobias (1993). Object oriented programming with ANSI-C. Hanser. ISBN 3-446-17426-5. hdl:1850/8544. 

External links

• Object-oriented programming at the Open Directory Project
• Chapter on implementing OOP in the programming language C by David Polberger
• Programming Styles: Procedural, OOP, and AOP
• What is OOP? (Tutorial on OOP in PHP)
• Basic Concepts of OOP with PHP
• Discussion about the flaws of OOD
• OOP Concepts (Java Tutorials)
• MDS Model Driven C Code Generation
• Intel blog - killing OOP