when was oop invented?

Object-oriented programming (OOP) is a programming paradigm based on the concept of "objects", which can contain data and code. The data is in the form of fields (often known as attributes or properties), and the code is in the form of procedures (often known as methods).

A common feature of objects is that procedures (or methods) are attached to them and can access and modify the object's data fields. In this brand of OOP, there is usually a special name such as this or self used to refer to the current object. In OOP, computer programs are designed by making them out of objects that interact with one another.[1][2] 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: Ada, ActionScript, C++, Common Lisp, C#, Dart, Eiffel, Fortran 2003, Haxe, Java, JavaScript, Kotlin, logo, MATLAB, Objective-C, Object Pascal, Perl, PHP, Python, R, Raku, Ruby, Scala, SIMSCRIPT, Simula, Smalltalk, Swift, Vala and Visual Basic.NET.

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);[3][4] Alan Kay later cited a detailed understanding of LISP internals as a strong influence on his thinking in 1966.[5]

Another early MIT example was Sketchpad created by Ivan Sutherland in 1960–1961; 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.[6] 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".[7][8]

Simula introduced important concepts that are today an essential part of object-oriented programming, such as class and object, inheritance, and dynamic binding.[9] 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.[9]

In the 1970s, the first version of the Smalltalk programming language was developed at Xerox PARC by Alan Kay, Dan Ingalls and Adele Goldberg. Smalltalk-72 included a programming environment and was dynamically typed, and at first was interpreted, not compiled. Smalltalk became 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.[10] 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.[11]

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 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++.[10] 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.

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,[12][13][14] C++,[15] 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).

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.

Object-oriented programming uses objects, but not all of the associated techniques and structures are supported directly in languages that claim to support OOP. It performs operations on operands. 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.[16][17][18][19]

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:

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".[20] 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:

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 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.

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. 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). In C#, Swift & Kotlin languages, internal keyword permits access only to files present in same assembly, package or module as that of the class.[21]

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.[22]

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 that 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.

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.

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:

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:

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

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.

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. As of April 2007, the book was in its 36th printing.

The book describes the following patterns:

Both object-oriented programming and relational database management systems (RDBMSs) are extremely common in software today[update]. 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.[24] 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[25] 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.[26] 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"[27] (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).[28] This problem may cause OOP to suffer more convoluted solutions than procedural programming.[29]

OOP was developed to increase the reusability and maintainability of source code.[30] 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.[31][32][33][34]

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:

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

The OOP paradigm has been criticised for a number of reasons, including not meeting its stated goals of reusability and modularity,[35][36] and for overemphasizing one aspect of software design and modeling (data/objects) at the expense of other important aspects (computation/algorithms).[37][38]

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.[35] The latter point is reiterated by Joe Armstrong, the principal inventor of Erlang, who is quoted as saying:[36]

A study by Potok et al. has shown no significant difference in productivity between OOP and procedural approaches.[39]

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;[40] however, Date and Darwen have proposed a theoretical foundation on OOP that uses OOP as a kind of customizable type system to support RDBMS.[41]

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.[42]

Alexander Stepanov compares object orientation unfavourably to generic programming:[37]

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".[43]

Leo Brodie has suggested a connection between the standalone nature of objects and a tendency to duplicate code[44] in violation of the don't repeat yourself principle[45] of software development.

Steve Yegge noted that, as opposed to functional programming:[46]

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.[38]

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.[47] Raymond compares this unfavourably to the approach taken with Unix and the C programming language.[47]

Rob Pike, a programmer involved in the creation of UTF-8 and Go, has called object-oriented programming "the Roman numerals of computing"[48] and has said that OOP languages frequently shift the focus from data structures and algorithms to types.[49] 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.[50]

Regarding inheritance, Bob Martin states that because they are software, related classes do not necessarily share the relationships of the things they represent.[51]

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:

Attempts to find a consensus definition or theory behind objects have not proven very successful (however, see Abadi & Cardelli, A Theory of Objects[53] 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").

The functional and imperative programming paradigms we use today were first explored mathematically in the 1930s with lambda calculus and the Turing machine, which are alternative formulations of universal computation (formalized systems which can perform general computation). The Church Turing Thesis showed that lambda calculus and Turing machines are functionally equivalent — that anything that can be computed using a Turing machine can be computed using lambda calculus, and vice versa.

Lambda calculus represents a top-down, function application approach to computation, while the ticker tape/register machine formulation of the Turing machine represents a bottom-up, imperative (step-by-step) approach to computation.

Low level languages like machine code and assembly appeared in the 1940s, and by the end of the 1950s, the first popular high-level languages appeared. Lisp dialects are still in common use today, including Clojure, Scheme, AutoLISP, etc. FORTRAN and COBOL both appeared in the 1950s and are examples of imperative high-level languages still in use today, though C-family languages have replaced both COBOL and FORTRAN for most applications.

Both imperative programming and functional programming have their roots in the mathematics of computation theory, predating digital computers. “Object-Oriented Programming” (OOP) was coined by Alan Kay circa 1966 or 1967 while he was at grad school.

Ivan Sutherland’s seminal Sketchpad application was an early inspiration for OOP. It was created between 1961 and 1962 and published in his Sketchpad Thesis in 1963. The objects were data structures representing graphical images displayed on an oscilloscope screen, and featured inheritance via dynamic delegates, which Ivan Sutherland called “masters” in his thesis. Any object could become a “master”, and additional instances of the objects were called “occurrences”. Sketchpad’s masters share a lot in common with JavaScript’s prototypal inheritance.

The first programming language widely recognized as “object oriented” was Simula, specified in 1965. Like Sketchpad, Simula featured objects, and eventually introduced classes, class inheritance, subclasses, and virtual methods.

Alan Kay coined the term “object oriented programming” at grad school in 1966 or 1967. The big idea was to use encapsulated mini-computers in software which communicated via message passing rather than direct data sharing — to stop breaking down programs into separate “data structures” and “procedures”.

“The basic principal of recursive design is to make the parts have the same power as the whole.” ~ Bob Barton, the main designer of the B5000, a mainframe optimized to run Algol-60.

Smalltalk was developed by Alan Kay, Dan Ingalls, Adele Goldberg, and others at Xerox PARC. Smalltalk was more object-oriented than Simula — everything in Smalltalk is an object, including classes, integers, and blocks (closures). The original Smalltalk-72 did not feature subclassing. That was introduced in Smalltalk-76 by Dan Ingalls.

While Smalltalk supported classes and eventually subclassing, Smalltalk was not about classes or subclassing things. It was a functional language inspired by Lisp as well as Simula. Alan Kay considers the industry’s focus on subclassing to be a distraction from the true benefits of object oriented programming.

In a 2003 email exchange, Alan Kay clarified what he meant when he called Smalltalk “object-oriented”:

In other words, according to Alan Kay, the essential ingredients of OOP are:

Notably, inheritance and subclass polymorphism were NOT considered essential ingredients of OOP by Alan Kay, the man who coined the term and brought OOP to the masses.

The combination of message passing and encapsulation serve some important purposes:

These ideas were inspired by biological cells and/or individual computers on a network via Alan Kay’s background in biology and influence from the design of Arpanet (an early version of the internet). Even that early on, Alan Kay imagined software running on a giant, distributed computer (the internet), where individual computers acted like biological cells, operating independently on their own isolated state, and communicating via message passing.

By “get rid of data”, Alan Kay was surely aware of shared mutable state problems and tight coupling caused by shared data — common themes today.

But in the late 1960s, ARPA programmers were frustrated by the need to choose a data model representation for their programs in advance of building software. Procedures that were too tightly coupled to particular data structures were not resilient to change. They wanted a more homogenous treatment of data.

Objects can abstract away and hide data structure implementations. The internal implementation of an object could change without breaking other parts of the software system. In fact, with extreme late binding, an entirely different computer system could take over the responsibilities of an object, and the software could keep working. Objects, meanwhile, could expose a standard interface that works with whatever data structure the object happened to use internally. The same interface could work with a linked list, a tree, a stream, and so on.

Alan Kay also saw objects as algebraic structures, which make certain mathematically provable guarantees about their behaviors:

This has proven to be true, and forms the basis for objects such as promises and lenses, both inspired by category theory.

The algebraic nature of Alan Kay’s vision for objects would allow objects to afford formal verifications, deterministic behavior, and improved testability, because algebras are essentially operations which obey a few rules in the form of equations.

In programmer lingo, algebras are like abstractions made up of functions (operations) accompanied by specific laws enforced by unit tests those functions must pass (axioms/equations).

Those ideas were forgotten for decades in most C-family OO languages, including C++, Java, C#, etc., but they’re beginning to find their way back into recent versions of most widely used OO languages.

You might say the programming world is rediscovering the benefits of functional programming and reasoned thought in the context of OO languages.

Like JavaScript and Smalltalk before it, most modern OO languages are becoming more and more “multi-paradigm languages”. There is no reason to choose between functional programming and OOP. When we look at the historical essence of each, they are not only compatible, but complementary ideas.

Because they share so many features in common, I like to say that JavaScript is Smalltalk’s revenge on the world’s misunderstanding of OOP. Both Smalltalk and JavaScript support:

What is essential to OOP (according to Alan Kay)?

What is non-essential?

If your background is Java or C#, you may be thinking static types and Polymorphism are essential ingredients, but Alan Kay preferred dealing with generic behaviors in algebraic form. For example, from Haskell:

This is the functor map signature, which acts generically over unspecified types a and b, applying a function from a to b in the context of a functor of a to produce a functor of b. Functor is math jargon that essentially means “supporting the map operation”. If you're familiar with [].map() in JavaScript, you already know what that means.

Here are two examples in JavaScript:

The .map() method is generic in the sense that a and b can be any type, and .map() handles it just fine because arrays are data structures that implement the algebraic functor laws. The types don't matter to .map() because it doesn't try to manipulate them directly, instead applying a function that expects and returns the correct types for the application.

This generic type relationship is difficult to express correctly and thoroughly in a language like TypeScript, but was pretty easy to express in Haskell’s Hindley Milner types with support for higher kinded types (types of types).

Most type systems have been too restrictive to allow for free expression of dynamic and functional ideas, such as function composition, free object composition, runtime object extension, combinators, lenses, etc. In other words, static types frequently make it harder to write composable software.

If your type system is too restrictive (e.g., TypeScript, Java), you’re forced to write more convoluted code to accomplish the same goals. That doesn’t mean static types are a bad idea, or that all static type implementations are equally restrictive. I have encountered far fewer problems with Haskell’s type system.

If you’re a fan of static types and you don’t mind the restrictions, more power to you, but if you find some of the advice in this text difficult because it’s hard to type composed functions and composite algebraic structures, blame the type system, not the ideas. People love the comfort of their SUVs, but nobody complains that they don’t let you fly. For that, you need a vehicle with more degrees of freedom.

If restrictions make your code simpler, great! But if restrictions force you to write more complicated code, perhaps the restrictions are wrong.

Objects have clearly taken on a lot of connotations over the years. What we call “objects” in JavaScript are simply composite data types, with none of the implications from either class-based programming or Alan Kay’s message-passing.

In JavaScript, those objects can and frequently do support encapsulation, message passing, behavior sharing via methods, even subclass polymorphism (albeit using a delegation chain rather than type-based dispatch). You can assign any function to any property. You can build object behaviors dynamically, and change the meaning of an object at runtime. JavaScript also supports encapsulation using closures for implementation privacy. But all of that is opt-in behavior.

Our current idea of an object is simply a composite data structure, and does not require anything more to be considered an object. But programming using these kinds of objects does not make your code “object-oriented” any more than programming with functions makes your code “functional”.

Because “object” in modern programming languages means much less than it did to Alan Kay, I’m using “component” instead of “object” to describe the rules of real OOP. Many objects are owned and manipulated directly by other code in JavaScript, but components should encapsulate and control their own state.

Real OOP means:

Most component behaviors can be specified generically using algebraic data structures. Inheritance is not needed here. Components can reuse behaviors from shared functions and modular imports without sharing their data.

Manipulating objects or using class inheritance in JavaScript does not mean that you’re “doing OOP”. Using components in this way does. But popular usage is how words get defined, so perhaps we should abandon OOP and call this “Message Oriented Programming (MOP)” instead of “Object Oriented Programming (OOP)”?

Is it coincidence that mops are used to clean up messes?

In most modern software, there is some UI responsible for managing user interactions, some code managing application state (user data), and code managing system or network I/O.

Each of those systems may require long-lived processes, such as event listeners, state to keep track of things like the network connection, ui element status, and the application state itself.

Good MOP means that instead of all of these systems reaching out and directly manipulating each other’s state, the system communicates with other components via message dispatch. When the user clicks on a save button, a "SAVE" message might get dispatched, which an application state component might interpret and relay to a state update handler (such as a pure reducer function). Perhaps after the state has been updated, the state component might dispatch a "STATE_UPDATED" message to a UI component, which in turn will interpret the state, reconcile what parts of the UI need to be updated, and relay the updated state to the subcomponents that handle those parts of the UI.

Meanwhile, the network connection component might be monitoring the user’s connection to another machine on the network, listening for messages, and dispatching updated state representations to save data on a remote machine. It’s internally keeping track of a network heartbeat timer, whether the connection is currently online or offline, and so on.

These systems don’t need to know about the details of the other parts of the system. Only about their individual, modular concerns. The system components are decomposable and recomposable. They implement standardized interfaces so that they are able to interoperate. As long as the interface is satisfied, you could substitute replacements which may do the same thing in different ways, or completely different things with the same messages. You may even do so at runtime, and everything would keep working properly.

Components of the same software system may not even need to be located on the same machine. The system could be decentralized. The network storage might shard the data across a decentralized storage system like IPFS, so that the user is not reliant on the health of any particular machine to ensure their data is safely backed up, and safe from hackers who might want to steal it.

OOP was partially inspired by Arpanet, and one of the goals of Arpanet was to build a decentralized network that could be resilient to attacks like atomic bombs. According to director of DARPA during Arpanet development, Stephen J. Lukasik (“Why the Arpanet Was Built”):

Note: The primary impetus of Arpanet was convenience rather than nuclear threat, and its obvious defense advantages emerged later. ARPA was using three separate computer terminals to communicate with three separate computer research projects. Bob Taylor wanted a single computer network to connect each project with the others.

A good MOP system might share the internet’s robustness using components that are hot-swappable while the application is running. It could continue to work if the user is on a cell phone and they go offline because they entered a tunnel. It could continue to function if a hurricane knocks out the power to one of the data centers where servers are located.

It’s time for the software world to let go of the failed class inheritance experiment, and embrace the math and science principles that originally defined the spirit of OOP.

It’s time for us to start building more flexible, more resilient, better-composed software, with MOP and functional programming working in harmony.

Object-Oriented Programming, 1961-1967

Ole-Johan Dahl and Kristen Nygaard created the Simula programming languages in the 1960s at the Norwegian Computer Center. They introduced a new way of modeling and simulating complex tasks. Object-oriented programming is now dominant in systems development. It is an integral part of computer science curricula, as are languages built on object-oriented programming concepts, such as Smalltalk, C++, Java, and Python.

59.9436196, 10.7183287 Gaustadalléen 23B, N-0316 Oslo, Norway. 59.943329 N, 10.717839 E

Inside, in the ground floor entrance hall, for instance on a brick-wall.

The building is open to the public during normal opening hours.

A video of the dedication ceremony may be viewed here

In 1961 Ole-Johan Dahl and Kristen Nygaard started working together to develop a description language for computer simulations. The two scientists developed a simulation language called SIMULA. This resulted in several versions of the language, including SIMULA 1. After completing SIMULA 1, they developed a high-level general programming language with real-time capabilities, on top of strong simulation constructs. The resulting language was called SIMULA 67, completed in 1967.

The language introduced all elements of what today are considered essential in an object-oriented language: encapsulation, inheritance, late binding, and dynamic object creation. And hiding mechanisms were added to the language shortly after.

This gives a natural way of modeling real world problems, letting objects reflect the things of interest, including clients or service providers. An object resembles an autonomous unit in that it has capabilities and may be asked to perform services by other units. This style of organizing the code and data was later termed "object-oriented programming" (OOP).

Object orientation and object-oriented programming became popular world-wide when the ideas of SIMULA were adopted in wide-spread languages such as C++ and Java. In the 1970s in USA, Alan Kay picked up the ideas of SIMULA in his Smalltalk language. Around 1980, Bjarne Stroustrup, who was taught SIMULA by Nygaard, decided to introduce the SIMULA philosophy to the C systems developers community, thus creating the C++ object-oriented language. Another ten years later Java was developed under the auspices of SUN by James Gosling who adhered to the SIMULA object-oriented mechanisms even more closely than C++.

Object-oriented programming, originating from the work on SIMULA, is by far the most popular paradigm for computer programming today and has been so for the last 20 years. This has been acknowledged by several prestigious awards including the Turing award and the von Neumann medal.

Today, nearly all computer programmers works with or have worked with a language that supports object-oriented programming and most of the large software systems that we now run every day have been programmed this way.

Object-oriented programming, originating from the work on SIMULA, is by far the most popular paradigm for computer programming today and has been so for the last 20 years.

The language incorporated fundamentally new mechanisms for programming and for program structuring, compared to existing languages. It introduced the class concept for encapsulation of data structure and code, subclasses for reuse of code, late binding for flexible inheritance, as well as dynamic and static instantiation of classes. Instead of seeing a program as a monolithic structure, the code of a SIMULA program was organized in a number of classes and blocks. Classes could be dynamically instantiated at run-time, and such an instance was called an "object". An object was an autonomous entity, with its own data and computational capabilities organized in procedures (methods), and objects could cooperate by asking another object to perform a procedure (i.e., by a remote call to a procedure of another object).

The co-routine mechanism of SIMULA allowed one to think of the objects as units that were operating concurrently. This lead to the notion of concurrent objects and inspired the combination of concurrency and object orientation.

It is widely accepted that object orientation refers to the combination of three main features: 1) encapsulation of data and code 2) inheritance and late binding 3) dynamic object generation. This combination was first made by the Simula67 language completed in 1967. Through its class construct Simula67 made a unification of the three features. Before 1967 there had been some advances in each of the three main features of object orientation. For instance, terminology involving "objects", "oriented", and "instance" first appeared at MIT in the late 1950s and early 1960s in the artificial intelligence group and in Sketchpad created by Ivan Sutherland (but specialized to graphical interaction). The ALGOL version, AED-0, also introduced a concept which prefigured what was later termed "messages", "methods", and "member functions". And Lisp had made use of dynamic (late) binding of functions. The Simula67 language was inspired by some of these works, in particular the block construct of Algol60 and the record mechanism suggested by Tony Hoare [Hoare, C. A. (Nov 1965). "Record Handling". ALGOL Bulletin (21): 39–69]."

Definition

[1] Ole-Johan Dahl and Kristen Nygaard. “Class and subclass declarations”. Norsk Regnesentral, 1967, 17 bl. Also in: Software Pioneers. Contributions to Software Engineering. Ed. by Manfred Broy and Ernst Denert. Reprint. (File:ClassAndSubclass.pdf)

[2] Ole-Johan Dahl and Kristen Nygaard. SIMULA 67. Common base definition. Norwegian Computing Center, 1967, 31, [3] bl. (File:CommonBaseDefinition1967.pdf)

[3] Ole-Johan Dahl. “Discrete event simulation languages”. In: Programming languages. Ed. by NATO Advanced Study Institute. London: Academic Press, 1968, pp. 349–395.

[4] Ole-Johan Dahl and C.A.R. Hoare. “Hierarchical program structures”. In: Ole-Johan Dahl, C.A.R. Hoare, and Edsger W. Dijkstra. Structured programming. Academic press, 1972. Chap. 3, pp. 175–220.

Importance

[5] Bjarne Stroustrup. “A history of C++: 1979–1991”. In: History of programming languages. Ed. by Richard L. Wexelblat. ACM, 1996, pp. 699–755. (File:Stroustrup1996.pdf)

[6] ACM Turing Award. Kristen Nygaard. 2001. (File:TuringAwardNygaard.pdf)

[7] ACM Turing Award. Ole-Johan Dahl. 2001. (File:TuringAwardDahl.pdf)

[8] Bertrand Meyer. “In memory of Ole-Johan Dahl and Kristen Nygaard,” in: Journal of Object-Technology, 1.4 (2002). (File:Meyer2002.pdf)

[9] Jonathan Aldrich. The Power of Interoperability. Why Objects Are Inevitable. 2013. (File:Aldrich2013.pdf)

[10] IEEE Awards. IEEE John von Neumann Medal Recipients. (File:IEEEaward.pdf)

History

[11] Kristen Nygaard and Ole-Johan Dahl. “The development of the SIMULA languages”. In: History of programming languages. Ed. by Richard L. Wexelblat. ACM, 1978, pp. 439–480. (File:DahlNygaard1978.pdf)

[12] Laszlo Böszörmenyi and Stefan Podlipnig. People behind informatics. Institute of Information Technology, University of Klagenfurt, 2003. URL: [1]

[13] Ole-Johan Dahl. “The birth of object-orientation. The Simula languages”. 2001. Also in: From object-orientation to formal methods. Essays in memory of Ole-Johan Dahl. Ed. by Olaf Owe, Stein Krogdahl, and Tom Lyche. Springer, 2004, pp. 15–25 ISBN : 3-540-21366-x. (File:Dahl2001.pdf)

Citation for IEEE von Neumann award, 2002: "When Ole-Johan Dahl and Kristen Nygaard created the Simula languages in the 1960s at the Norwegian Computing Center, they introduced a new way of modeling and programming complex tasks. Object-oriented programming is now dominant in system development, and is everywhere part of the computer science curricula, as are languages built on OOP concepts, such as Smalltalk, C++, Eiffel and Java.

Kristen Nygaard analyzed complex problems by computer simulation, requiring interaction between many very dissimilar components. He saw the need for a description language that could be used to comprehend, describe and communicate complex systems, and also make it possible for computers to execute models of what had been described.

Ole-Johan Dahl joined Kristen Nygaard at the NCC. They designed the Simula concepts and language together, and Dahl carried out the difficult task of writing the program that translated descriptions into computer instructions. In 1968 Dahl became the University of Oslo’s first computer science professor and built its Informatics Department. Later he has contributed to the theory of proving correctness of programs. Nygaard continued OOP, but also became the driving force in the “Scandinavian school of system development.” His efforts now are aimed at improving the teaching and conceptual platform for computer science. Dahl and Nygaard are Professors Emeriti at the University of Oslo. They both have been named Commander of the Order of Saint Olav by the King of Norway and Honorary Fellows of the Object Management Group, have received the Norwegian Rosing Prize and the 2001 ACM A.M. Turing Award."

Citation for ACM Turing award, 2002: "... for ideas fundamental to the emergence of object oriented programming, through their design of the programming languages Simula I and Simula 67."

“Object-Oriented Programming” (OOP) was coined by Alan Kay circa 1966 or 1967 while he was at grad school. Ivan Sutherland's seminal Sketchpad application was an early inspiration for OOP. It was created between 1961 and 1962 and published in his Sketchpad Thesis in 1963.