In computer engineering, computer architecture is the conceptual design and fundamental operational structure of a computer system. It is a blueprint and functional description of requirements (especially speeds and interconnections) and design implementations for the various parts of a computer — focusing largely on the way by which the central processing unit (CPU) performs internally and accesses addresses in memory.
It may also be defined as the science and art of selecting and interconnecting hardware components to create computers that meet functional, performance and cost goals.
Computer architecture comprises at least three main subcategories:[1]
Instruction set architecture, or ISA, is the abstract image of a computing system that is seen by a machine language (or assembly language) programmer, including the instruction set, memory address modes, processor registers, and address and data formats.
Microarchitecture, also known as Computer organization is a lower level, more concrete and detailed, description of the system that involves how the constituent parts of the system are interconnected and how they interoperate in order to implement the ISA.[2] The size of a computer's cache for instance, is an organizational issue that generally has nothing to do with the ISA.
System Design which includes all of the other hardware components within a computing system such as:
system interconnects such as computer buses and switches
memory controllers and hierarchies
CPU off-load mechanisms such as direct memory access
issues like multi-processing.
Once both ISA and microarchitecture has been specified, the actual device needs to be designed into hardware. This design process is called implementation. Implementation is usually not considered architectural definition, but rather hardware design engineering.
Implementation can be further broken down into three (not fully distinct) pieces:
Logic Implementation - design of blocks defined in the microarchitecture at (primarily) the register-transfer and gate levels.
Circuit Implementation - transistor-level design of basic elements (gates, multiplexers, latches etc) as well as of some larger blocks (ALUs, caches etc) that may be implemented at this level, or even (partly) at the physical level, for performance reasons.
Physical Implementation - physical circuits are drawn out, the different circuit components are placed in a chip floor-plan or on a board and the wires connecting them are routed.
For CPUs, the entire implementation process is often called CPU design.
More specific usages of the term include more general wider-scale hardware architectures, such as cluster computing and Non-Uniform Memory Access (NUMA) architectures.
Tuesday, July 29, 2008
Computer hardware
Computer hardware is the physical part of a computer, including its digital circuitry, as distinguished from the computer software that executes within the hardware. The hardware of a computer is infrequently changed, in comparison with software and hardware data, which are "soft" in the sense that they are readily created, modified or erased on the computer. Firmware is a special type of software that rarely, if ever, needs to be changed and so is stored on hardware devices such as read-only memory (ROM) where it is not readily changed (and is, therefore, "firm" rather than just "soft").
Most computer hardware is not seen by normal users. It is in embedded systems in automobiles, microwave ovens, electrocardiograph machines, compact disc players, and other devices. Personal computers, the computer hardware familiar to most people, form only a small minority of computers (about 0.2% of all new computers produced in 2003)
Most computer hardware is not seen by normal users. It is in embedded systems in automobiles, microwave ovens, electrocardiograph machines, compact disc players, and other devices. Personal computers, the computer hardware familiar to most people, form only a small minority of computers (about 0.2% of all new computers produced in 2003)
Relationship to computer hardware
Computer software is so called to distinguish it from computer hardware, which encompasses the physical interconnections and devices required to store and execute (or run) the software. In computers, software is loaded into RAM and executed in the central processing unit. At the lowest level, software consists of a machine language specific to an individual processor. A machine language consists of groups of binary values signifying processor instructions which change the state of the computer from its preceding state. Software is an ordered sequence of instructions for changing the state of the computer hardware in a particular sequence. It is usually written in high-level programming languages that are easier and more efficient for humans to use (closer to natural language) than machine language. High-level languages are compiled or interpreted into machine language object code. Software may also be written in an assembly language, essentially, a mnemonic representation of a machine language using a natural language alphabet. Assembly language must be assembled into object code via an assembler.
The term "software" was first used in this sense by John W. Tukey in 1958.[3] In computer science and software engineering, computer software is all computer programs. The theory that is the basis for most modern software was first proposed by Alan Turing in his 1935 essay Computable numbers with an application to the Entscheidungsproblem
The term "software" was first used in this sense by John W. Tukey in 1958.[3] In computer science and software engineering, computer software is all computer programs. The theory that is the basis for most modern software was first proposed by Alan Turing in his 1935 essay Computable numbers with an application to the Entscheidungsproblem
Computer Software
Computer software is a general term used to describe a collection of computer programs, procedures and documentation that perform some tasks on a computer system.[1] The term includes application software such as word processors which perform productive tasks for users, system software such as operating systems, which interface with hardware to provide the necessary services for application software, and middleware which controls and co-ordinates distributed systems.
"Software" is sometimes used in a broader context to mean anything which is not hardware but which is used with hardware, such as film, tapes and records
"Software" is sometimes used in a broader context to mean anything which is not hardware but which is used with hardware, such as film, tapes and records
Modern programming
Quality requirements
Whatever the approach to the software development may be, the program must finally satisfy some fundamental properties; bearing them in mind while programming reduces the costs in terms of time and/or money due to debugging, further development and user support. Although quality programming can be achieved in a number of ways, following five properties are among the most relevant:
Efficiency: it is referred to the system resource consumption (computer processor, memory, slow devices, networks and to some extent even user interaction) which must be the lowest possible.
Reliability: the results of the program must be correct, which not only implies a correct code implementation but also reduction of error propagation (e.g. resulting from data conversion) and prevention of typical errors (overflow, underflow or zero division).
Robustness: a program must anticipate situations of data type conflict and all other incompatibilities which result in run time errors and stop the program. The focus of this aspect is the interaction with the user and the handling of error messages.
Portability: it should work as it is in any software and hardware environment, or at least without relevant reprogramming.
Readability: the purpose of the main program and of each subroutine must be clearly defined with appropriate comments and self explanatory choice of symbolic names (constants, variables, function names, classes, methods, ...).
Algorithmic complexity
The academic field and the engineering practice of computer programming are both largely concerned with discovering and implementing the most efficient algorithms for a given class of problem. For this purpose, algorithms are classified into orders using so-called Big O notation, O(n), which expresses resource use, such as execution time or memory consumption, in terms of the size of an input. Expert programmers are familiar with a variety of well-established algorithms and their respective complexities and use this knowledge to choose algorithms that are best suited to the circumstances.
Methodologies
The first step in most formal software development projects is requirements analysis, followed by modeling, implementation, and failure elimination (debugging). There exist a lot of differing approaches for each of those tasks. One approach popular for requirements analysis is Use Case analysis.
Popular modeling techniques include Object-Oriented Analysis and Design (OOAD) and Model-Driven Architecture (MDA). The Unified Modeling Language (UML) is a notation used for both OOAD and MDA.
A similar technique used for database design is Entity-Relationship Modeling (ER Modeling).
Implementation techniques include imperative languages (object-oriented or procedural), functional languages, and logic languages.
Debugging is most often done with IDEs like Visual Studio, NetBeans, and Eclipse. Separate debuggers like gdb are also used.
Measuring language usage
It is very difficult to determine what are the most popular of modern programming languages. Some languages are very popular for particular kinds of applications (e.g., COBOL is still strong in the corporate data center, often on large mainframes, FORTRAN in engineering applications, and C in embedded applications), while some languages are regularly used to write many different kinds of applications.
Methods of measuring language popularity include: counting the number of job advertisements that mention the language[4], the number of books teaching the language that are sold (this overestimates the importance of newer languages), and estimates of the number of existing lines of code written in the language (this underestimates the number of users of business languages such as COBOL).
Debugging
Debugging is a very important task in the software development process, because an erroneous program can have significant consequences for its users. Some languages are more prone to some kinds of faults because their specification does not require compilers to perform as much checking as other languages. Use of a static analysis tool can help detect some possible problems.
Whatever the approach to the software development may be, the program must finally satisfy some fundamental properties; bearing them in mind while programming reduces the costs in terms of time and/or money due to debugging, further development and user support. Although quality programming can be achieved in a number of ways, following five properties are among the most relevant:
Efficiency: it is referred to the system resource consumption (computer processor, memory, slow devices, networks and to some extent even user interaction) which must be the lowest possible.
Reliability: the results of the program must be correct, which not only implies a correct code implementation but also reduction of error propagation (e.g. resulting from data conversion) and prevention of typical errors (overflow, underflow or zero division).
Robustness: a program must anticipate situations of data type conflict and all other incompatibilities which result in run time errors and stop the program. The focus of this aspect is the interaction with the user and the handling of error messages.
Portability: it should work as it is in any software and hardware environment, or at least without relevant reprogramming.
Readability: the purpose of the main program and of each subroutine must be clearly defined with appropriate comments and self explanatory choice of symbolic names (constants, variables, function names, classes, methods, ...).
Algorithmic complexity
The academic field and the engineering practice of computer programming are both largely concerned with discovering and implementing the most efficient algorithms for a given class of problem. For this purpose, algorithms are classified into orders using so-called Big O notation, O(n), which expresses resource use, such as execution time or memory consumption, in terms of the size of an input. Expert programmers are familiar with a variety of well-established algorithms and their respective complexities and use this knowledge to choose algorithms that are best suited to the circumstances.
Methodologies
The first step in most formal software development projects is requirements analysis, followed by modeling, implementation, and failure elimination (debugging). There exist a lot of differing approaches for each of those tasks. One approach popular for requirements analysis is Use Case analysis.
Popular modeling techniques include Object-Oriented Analysis and Design (OOAD) and Model-Driven Architecture (MDA). The Unified Modeling Language (UML) is a notation used for both OOAD and MDA.
A similar technique used for database design is Entity-Relationship Modeling (ER Modeling).
Implementation techniques include imperative languages (object-oriented or procedural), functional languages, and logic languages.
Debugging is most often done with IDEs like Visual Studio, NetBeans, and Eclipse. Separate debuggers like gdb are also used.
Measuring language usage
It is very difficult to determine what are the most popular of modern programming languages. Some languages are very popular for particular kinds of applications (e.g., COBOL is still strong in the corporate data center, often on large mainframes, FORTRAN in engineering applications, and C in embedded applications), while some languages are regularly used to write many different kinds of applications.
Methods of measuring language popularity include: counting the number of job advertisements that mention the language[4], the number of books teaching the language that are sold (this overestimates the importance of newer languages), and estimates of the number of existing lines of code written in the language (this underestimates the number of users of business languages such as COBOL).
Debugging
Debugging is a very important task in the software development process, because an erroneous program can have significant consequences for its users. Some languages are more prone to some kinds of faults because their specification does not require compilers to perform as much checking as other languages. Use of a static analysis tool can help detect some possible problems.
History of programming
Prehistory :
The first programming languages predate the modern computer. From the first, the languages were codes.
During a nine-month period in 1842-1843, Ada Lovelace translated Italian mathematician Luigi Menabrea's memoir on Charles Babbage's newest proposed machine, the Analytical Engine. With the article, she appended a set of notes which specified in complete detail a method for calculating Bernoulli numbers with the Engine, recognized by some historians as the world's first computer program. But some biographers debate the extent of her original contributions versus those of her husband.
The Jacquard loom used holes in punched cards to represent sewing loom arm movements in order to generate decorative patterns automatically.
Herman Hollerith realized that he could encode information on punch cards when he observed that railroad train conductors would encode the appearance of the ticket holders on the train tickets using the position of punched holes on the tickets. Hollerith then proceeded to encode the 1890 census data on punch cards.
The first computer codes were specialized for the applications. In the first decades of the twentieth century, numerical calculations were based on decimal numbers. Eventually it was realized that logic could be represented with numbers, as well as with words. For example, Alonzo Church was able to express the lambda calculus in a formulaic way. The Turing machine was an abstraction of the operation of a tape-marking machine, for example, in use at the telephone companies. However, unlike the lambda calculus, Turing's code does not serve well as a basis for higher-level languages — its principal use is in rigorous analyses of algorithmic complexity.
Like many "firsts" in history, the first modern programming language is hard to identify. From the start, the restrictions of the hardware defined the language. Punch cards allowed 80 columns, but some of the columns had to be used for a sorting number on each card. Fortran included some keywords which were the same as English words, such as "IF", "GOTO" (go to) and "CONTINUE". The use of a magnetic drum for memory meant that computer programs also had to be interleaved with the rotations of the drum. Thus the programs were more hardware dependent than today.
To some people the answer depends on how much power and human-readability is required before the status of "programming language" is granted. Jacquard looms and Charles Babbage's Difference Engine both had simple, extremely limited languages for describing the actions that these machines should perform. One can even regard the punch holes on a player piano scroll as a limited domain-specific programming language, albeit not designed for human consumption.
The 1940s
In the 1940s the first recognizably modern, electrically powered computers were created. The limited speed and memory capacity forced programmers to write hand tuned assembly language programs. It was soon discovered that programming in assembly language required a great deal of intellectual effort and was error-prone.
In 1948, Konrad Zuse [1] published a paper about his programming language Plankalkül. However, it was not implemented in his time and his original contributions were isolated from other developments.
Some important languages that were developed in this period include:
1943 - Plankalkül (Konrad Zuse)
1943 - ENIAC coding system
1949 - C-10
The 1950s and 1960s
In the 1950s the first three modern programming languages whose descendants are still in widespread use today were designed:
FORTRAN, the "FORmula TRANslator, invented by John W. Backus et al.;
LISP, the "LISt Processor", invented by John McCarthy et al.;
COBOL, the COmmon Business Oriented Language, created by the Short Range Committee, heavily influenced by Grace Hopper.
Another milestone in the late 1950s was the publication, by a committee of American and European computer scientists, of "a new language for algorithms"; the Algol 60 Report (the "ALGOrithmic Language"). This report consolidated many ideas circulating at the time and featured two key innovations:
The use of Backus-Naur Form (BNF) for describing the language's syntax. Nearly all subsequent programming languages have used a variant of BNF to describe the context-free portion of their syntax.
The introduction of lexical scoping for names in arbitrarily nested scopes.
Algol 60 was particularly influential in the design of later languages, some of which soon became more popular. The Burroughs large systems were designed to be programmed in an extended subset of Algol.
The 1990s: the Internet age
The rapid growth of the Internet in the mid-1990s was the next major historic event in programming languages. By opening up a radically new platform for computer systems, the Internet created an opportunity for new languages to be adopted. In particular, the Java programming language rose to popularity because of its early integration with the Netscape Navigator web browser, and various scripting languages achieved widespread use in developing customized applications for web servers. Neither of these developments represented much fundamental novelty in language design; for example, the design of Java was a more conservative version of ideas explored many years earlier in the Smalltalk community, but the widespread adoption of languages that supported features like garbage collection and strong static typing was a major change in programming practice.
Some important languages that were developed in this period include:
1990 - Haskell
1991 - Python
1991 - Java
1993 - Ruby
1995 - PHP
2000 - C#
The first programming languages predate the modern computer. From the first, the languages were codes.
During a nine-month period in 1842-1843, Ada Lovelace translated Italian mathematician Luigi Menabrea's memoir on Charles Babbage's newest proposed machine, the Analytical Engine. With the article, she appended a set of notes which specified in complete detail a method for calculating Bernoulli numbers with the Engine, recognized by some historians as the world's first computer program. But some biographers debate the extent of her original contributions versus those of her husband.
The Jacquard loom used holes in punched cards to represent sewing loom arm movements in order to generate decorative patterns automatically.
Herman Hollerith realized that he could encode information on punch cards when he observed that railroad train conductors would encode the appearance of the ticket holders on the train tickets using the position of punched holes on the tickets. Hollerith then proceeded to encode the 1890 census data on punch cards.
The first computer codes were specialized for the applications. In the first decades of the twentieth century, numerical calculations were based on decimal numbers. Eventually it was realized that logic could be represented with numbers, as well as with words. For example, Alonzo Church was able to express the lambda calculus in a formulaic way. The Turing machine was an abstraction of the operation of a tape-marking machine, for example, in use at the telephone companies. However, unlike the lambda calculus, Turing's code does not serve well as a basis for higher-level languages — its principal use is in rigorous analyses of algorithmic complexity.
Like many "firsts" in history, the first modern programming language is hard to identify. From the start, the restrictions of the hardware defined the language. Punch cards allowed 80 columns, but some of the columns had to be used for a sorting number on each card. Fortran included some keywords which were the same as English words, such as "IF", "GOTO" (go to) and "CONTINUE". The use of a magnetic drum for memory meant that computer programs also had to be interleaved with the rotations of the drum. Thus the programs were more hardware dependent than today.
To some people the answer depends on how much power and human-readability is required before the status of "programming language" is granted. Jacquard looms and Charles Babbage's Difference Engine both had simple, extremely limited languages for describing the actions that these machines should perform. One can even regard the punch holes on a player piano scroll as a limited domain-specific programming language, albeit not designed for human consumption.
The 1940s
In the 1940s the first recognizably modern, electrically powered computers were created. The limited speed and memory capacity forced programmers to write hand tuned assembly language programs. It was soon discovered that programming in assembly language required a great deal of intellectual effort and was error-prone.
In 1948, Konrad Zuse [1] published a paper about his programming language Plankalkül. However, it was not implemented in his time and his original contributions were isolated from other developments.
Some important languages that were developed in this period include:
1943 - Plankalkül (Konrad Zuse)
1943 - ENIAC coding system
1949 - C-10
The 1950s and 1960s
In the 1950s the first three modern programming languages whose descendants are still in widespread use today were designed:
FORTRAN, the "FORmula TRANslator, invented by John W. Backus et al.;
LISP, the "LISt Processor", invented by John McCarthy et al.;
COBOL, the COmmon Business Oriented Language, created by the Short Range Committee, heavily influenced by Grace Hopper.
Another milestone in the late 1950s was the publication, by a committee of American and European computer scientists, of "a new language for algorithms"; the Algol 60 Report (the "ALGOrithmic Language"). This report consolidated many ideas circulating at the time and featured two key innovations:
The use of Backus-Naur Form (BNF) for describing the language's syntax. Nearly all subsequent programming languages have used a variant of BNF to describe the context-free portion of their syntax.
The introduction of lexical scoping for names in arbitrarily nested scopes.
Algol 60 was particularly influential in the design of later languages, some of which soon became more popular. The Burroughs large systems were designed to be programmed in an extended subset of Algol.
The 1990s: the Internet age
The rapid growth of the Internet in the mid-1990s was the next major historic event in programming languages. By opening up a radically new platform for computer systems, the Internet created an opportunity for new languages to be adopted. In particular, the Java programming language rose to popularity because of its early integration with the Netscape Navigator web browser, and various scripting languages achieved widespread use in developing customized applications for web servers. Neither of these developments represented much fundamental novelty in language design; for example, the design of Java was a more conservative version of ideas explored many years earlier in the Smalltalk community, but the widespread adoption of languages that supported features like garbage collection and strong static typing was a major change in programming practice.
Some important languages that were developed in this period include:
1990 - Haskell
1991 - Python
1991 - Java
1993 - Ruby
1995 - PHP
2000 - C#
Programming language
A programming language is an artificial language that can be used to control the behavior of a machine, particularly a computer.[1] Programming languages are defined by syntactic and semantic rules which describe their structure and meaning respectively. Many programming languages have some form of written specification of their syntax and semantics; some are defined only by an official implementation.
Programming languages are used to facilitate communication about the task of organizing and manipulating information, and to express algorithms precisely. Some authors restrict the term "programming language" to those languages that can express all possible algorithms;[2] sometimes the term "computer language" is used for more limited artificial languages.
Definitions :
Traits often considered important for constituting a programming language:
Function: A programming language is a language used to write computer programs, which involve a computer performing some kind of computation[4] or algorithm and possibly control external devices such as printers, robots,[5] and so on.
Target: Programming languages differ from natural languages in that natural languages are only used for interaction between people, while programming languages also allow humans to communicate instructions to machines. Some programming languages are used by one device to control another. For example PostScript programs are frequently created by another program to control a computer printer or display.
Constructs: Programming languages may contain constructs for defining and manipulating data structures or controlling the flow of execution.
Expressive power: The theory of computation classifies languages by the computations they can express (see Chomsky hierarchy). All Turing complete languages can implement the same set of algorithms. ANSI/ISO SQL and Charity are examples of languages that are not Turing complete yet often called programming languages.[6][7]
Non-computational languages, such as markup languages like HTML or formal grammars like BNF, are usually not considered programming languages. Often a programming language is embedded in the non-computational (host) language
Purpose :
A prominent purpose of programming languages is to provide instructions to a computer. As such, programming languages differ from most other forms of human expression in that they require a greater degree of precision and completeness. When using a natural language to communicate with other people, human authors and speakers can be ambiguous and make small errors, and still expect their intent to be understood. However, computers do exactly what they are told to do, and cannot understand the code the programmer "intended" to write. The combination of the language definition, the program, and the program's inputs must fully specify the external behavior that occurs when the program is executed.
Many languages have been designed from scratch, altered to meet new needs, combined with other languages, and eventually fallen into disuse. Although there have been attempts to design one "universal" computer language that serves all purposes, all of them have failed to be accepted in this role.[8] The need for diverse computer languages arises from the diversity of contexts in which languages are used:
Programs range from tiny scripts written by individual hobbyists to huge systems written by hundreds of programmers.
Programmers range in expertise from novices who need simplicity above all else, to experts who may be comfortable with considerable complexity.
Programs must balance speed, size, and simplicity on systems ranging from microcontrollers to supercomputers.
Programs may be written once and not change for generations, or they may undergo nearly constant modification.
Finally, programmers may simply differ in their tastes: they may be accustomed to discussing problems and expressing them in a particular language.
One common trend in the development of programming languages has been to add more ability to solve problems using a higher level of abstraction. The earliest programming languages were tied very closely to the underlying hardware of the computer. As new programming languages have developed, features have been added that let programmers express ideas that are more removed from simple translation into underlying hardware instructions. Because programmers are less tied to the needs of the computer, their programs can do more computing with less effort from the programmer. This lets them write more programs in the same amount of time.[9]
Natural language processors have been proposed as a way to eliminate the need for a specialized language for programming. However, this goal remains distant and its benefits are open to debate. Edsger Dijkstra took the position that the use of a formal language is essential to prevent the introduction of meaningless constructs, and dismissed natural language programming as "foolish."[10] Alan Perlis was similarly dismissive of the idea.
Programming languages are used to facilitate communication about the task of organizing and manipulating information, and to express algorithms precisely. Some authors restrict the term "programming language" to those languages that can express all possible algorithms;[2] sometimes the term "computer language" is used for more limited artificial languages.
Definitions :
Traits often considered important for constituting a programming language:
Function: A programming language is a language used to write computer programs, which involve a computer performing some kind of computation[4] or algorithm and possibly control external devices such as printers, robots,[5] and so on.
Target: Programming languages differ from natural languages in that natural languages are only used for interaction between people, while programming languages also allow humans to communicate instructions to machines. Some programming languages are used by one device to control another. For example PostScript programs are frequently created by another program to control a computer printer or display.
Constructs: Programming languages may contain constructs for defining and manipulating data structures or controlling the flow of execution.
Expressive power: The theory of computation classifies languages by the computations they can express (see Chomsky hierarchy). All Turing complete languages can implement the same set of algorithms. ANSI/ISO SQL and Charity are examples of languages that are not Turing complete yet often called programming languages.[6][7]
Non-computational languages, such as markup languages like HTML or formal grammars like BNF, are usually not considered programming languages. Often a programming language is embedded in the non-computational (host) language
Purpose :
A prominent purpose of programming languages is to provide instructions to a computer. As such, programming languages differ from most other forms of human expression in that they require a greater degree of precision and completeness. When using a natural language to communicate with other people, human authors and speakers can be ambiguous and make small errors, and still expect their intent to be understood. However, computers do exactly what they are told to do, and cannot understand the code the programmer "intended" to write. The combination of the language definition, the program, and the program's inputs must fully specify the external behavior that occurs when the program is executed.
Many languages have been designed from scratch, altered to meet new needs, combined with other languages, and eventually fallen into disuse. Although there have been attempts to design one "universal" computer language that serves all purposes, all of them have failed to be accepted in this role.[8] The need for diverse computer languages arises from the diversity of contexts in which languages are used:
Programs range from tiny scripts written by individual hobbyists to huge systems written by hundreds of programmers.
Programmers range in expertise from novices who need simplicity above all else, to experts who may be comfortable with considerable complexity.
Programs must balance speed, size, and simplicity on systems ranging from microcontrollers to supercomputers.
Programs may be written once and not change for generations, or they may undergo nearly constant modification.
Finally, programmers may simply differ in their tastes: they may be accustomed to discussing problems and expressing them in a particular language.
One common trend in the development of programming languages has been to add more ability to solve problems using a higher level of abstraction. The earliest programming languages were tied very closely to the underlying hardware of the computer. As new programming languages have developed, features have been added that let programmers express ideas that are more removed from simple translation into underlying hardware instructions. Because programmers are less tied to the needs of the computer, their programs can do more computing with less effort from the programmer. This lets them write more programs in the same amount of time.[9]
Natural language processors have been proposed as a way to eliminate the need for a specialized language for programming. However, this goal remains distant and its benefits are open to debate. Edsger Dijkstra took the position that the use of a formal language is essential to prevent the introduction of meaningless constructs, and dismissed natural language programming as "foolish."[10] Alan Perlis was similarly dismissive of the idea.
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