Jul 09, 2020 Programming languages for kids can help ease them onto a path that can lead to in-demand and lucrative future careers. Programming for kids can be learned through block style lessons or by learning a new programming language. Computer programming for kids is best taught using gaming and gaming-style coding to keep their interest.
- Python continues to be one of the best programming languages every developer should.
- Computer programming language, any of various languages for expressing a set of detailed instructions for a computer. The earliest programming languages were assembly languages, not far removed from instructions directly executed by hardware. Although there are many computer languages.
- Swift is a powerful and intuitive programming language for iOS, macOS, tvOS, and watchOS. Writing Swift code is interactive and fun, the syntax is concise yet expressive, and Swift includes modern features developers love. Swift code is safe by design, yet also produces software that runs lightning-fast.
- SNOBOL is distinctive in format and programming style, which are radically different from contemporary procedural languages such as Fortran and Algol. SNOBOL4 supports a number of built-in data types, such as integers and limited precision real numbers, strings, patterns, arrays, and tables (associative arrays), and also allows the programmer to define additional data types and new functions.
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- Object-oriented languages
- Document formatting languages
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- Elements of programming
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Computer programming language, any of various languages for expressing a set of detailed instructions for a digital computer. Such instructions can be executed directly when they are in the computer manufacturer-specific numerical form known as machine language, after a simple substitution process when expressed in a corresponding assembly language, or after translation from some “higher-level” language. Although there are many computer languages, relatively few are widely used.
Machine and assembly languages are “low-level,” requiring a programmer to manage explicitly all of a computer’s idiosyncratic features of data storage and operation. In contrast, high-level languages shield a programmer from worrying about such considerations and provide a notation that is more easily written and read by programmers.
Machine and assembly languages
A machine language consists of the numeric codes for the operations that a particular computer can execute directly. The codes are strings of 0s and 1s, or binary digits (“bits”), which are frequently converted both from and to hexadecimal (base 16) for human viewing and modification. Machine language instructions typically use some bits to represent operations, such as addition, and some to represent operands, or perhaps the location of the next instruction. Machine language is difficult to read and write, since it does not resemble conventional mathematical notation or human language, and its codes vary from computer to computer.
Assembly language is one level above machine language. It uses short mnemonic codes for instructions and allows the programmer to introduce names for blocks of memory that hold data. One might thus write “add pay, total” instead of “0110101100101000” for an instruction that adds two numbers.
Assembly language is designed to be easily translated into machine language. Although blocks of data may be referred to by name instead of by their machine addresses, assembly language does not provide more sophisticated means of organizing complex information. Like machine language, assembly language requires detailed knowledge of internal computer architecture. It is useful when such details are important, as in programming a computer to interact with input/output devices (printers, scanners, storage devices, and so forth).
Algorithmic languages are designed to express mathematical or symbolic computations. They can express algebraic operations in notation similar to mathematics and allow the use of subprograms that package commonly used operations for reuse. They were the first high-level languages.
The first important algorithmic language was FORTRAN (formula translation), designed in 1957 by an IBM team led by John Backus. It was intended for scientific computations with real numbers and collections of them organized as one- or multidimensional arrays. Its control structures included conditional IF statements, repetitive loops (so-called DO loops), and a GOTO statement that allowed nonsequential execution of program code. FORTRAN made it convenient to have subprograms for common mathematical operations, and built libraries of them.
FORTRAN was also designed to translate into efficient machine language. It was immediately successful and continues to evolve.
ALGOL (algorithmic language) was designed by a committee of American and European computer scientists during 1958–60 for publishing algorithms, as well as for doing computations. Like LISP (described in the next section), ALGOL had recursive subprograms—procedures that could invoke themselves to solve a problem by reducing it to a smaller problem of the same kind. ALGOL introduced block structure, in which a program is composed of blocks that might contain both data and instructions and have the same structure as an entire program. Block structure became a powerful tool for building large programs out of small components.
ALGOL contributed a notation for describing the structure of a programming language, Backus–Naur Form, which in some variation became the standard tool for stating the syntax (grammar) of programming languages. ALGOL was widely used in Europe, and for many years it remained the language in which computer algorithms were published. Many important languages, such as Pascal and Ada (both described later), are its descendants.
LISP (list processing) was developed about 1960 by John McCarthy at the Massachusetts Institute of Technology (MIT) and was founded on the mathematical theory of recursive functions (in which a function appears in its own definition). A LISP program is a function applied to data, rather than being a sequence of procedural steps as in FORTRAN and ALGOL. LISP uses a very simple notation in which operations and their operands are given in a parenthesized list. For example, (+ a (* bc)) stands for a + b*c. Although this appears awkward, the notation works well for computers. LISP also uses the list structure to represent data, and, because programs and data use the same structure, it is easy for a LISP program to operate on other programs as data.
LISP became a common language for artificial intelligence (AI) programming, partly owing to the confluence of LISP and AI work at MIT and partly because AI programs capable of “learning” could be written in LISP as self-modifying programs. LISP has evolved through numerous dialects, such as Scheme and Common LISP.
The C programming language was developed in 1972 by Dennis Ritchie and Brian Kernighan at the AT&T Corporation for programming computer operating systems. Its capacity to structure data and programs through the composition of smaller units is comparable to that of ALGOL. It uses a compact notation and provides the programmer with the ability to operate with the addresses of data as well as with their values. This ability is important in systems programming, and C shares with assembly language the power to exploit all the features of a computer’s internal architecture. C, along with its descendant C++, remains one of the most common languages.
COBOL (common business oriented language) has been heavily used by businesses since its inception in 1959. A committee of computer manufacturers and users and U.S. government organizations established CODASYL (Committee on Data Systems and Languages) to develop and oversee the language standard in order to ensure its portability across diverse systems.
COBOL uses an English-like notation—novel when introduced. Business computations organize and manipulate large quantities of data, and COBOL introduced the recorddata structure for such tasks. A record clusters heterogeneous data such as a name, ID number, age, and address into a single unit. This contrasts with scientific languages, in which homogeneous arrays of numbers are common. Records are an important example of “chunking” data into a single object, and they appear in nearly all modern languages.
- key people
- related topics
|Designed by||David J. Farber, Ralph E. Griswold and Ivan P. Polonsky|
|Developer||David J. Farber, Ralph E. Griswold, Ivan P. Polonsky, and Bell Labs|
|First appeared||1962; 58 years ago|
|AWK, SL5, Icon, bs, Lua|
SNOBOL ('StriNg Oriented and symBOlic Language') is a series of programming languages developed between 1962 and 1967 at AT&TBell Laboratories by David J. Farber, Ralph E. Griswold and Ivan P. Polonsky, culminating in SNOBOL4. It was one of a number of text-string-oriented languages developed during the 1950s and 1960s; others included COMIT and TRAC.
SNOBOL4 was quite widely taught in larger US universities in the late 1960s and early 1970s and was widely used in the 1970s and 1980s as a text manipulation language in the humanities.
In the 1980s and 1990s its use faded as newer languages such as AWK and Perl made string manipulation by means of regular expressions fashionable. SNOBOL4 patterns subsume BNF grammars, which are equivalent to context-free grammars and more powerful than regular expressions. The 'regular expressions' in current versions of AWK and Perl are in fact extensions of regular expressions in the traditional sense, but regular expressions, unlike SNOBOL4 patterns, are not recursive, which gives a distinct computational advantage to SNOBOL4 patterns. (Recursive expressions did appear in Perl 5.10, though, released in December 2007.)
The later SL5 (1977) and Icon (1978) languages were designed by Griswold to combine the backtracking of SNOBOL4 pattern matching with more standard ALGOL-like structuring.
The initial SNOBOL language was created as a tool to be used by its authors to work with the symbolic manipulation of polynomials. It was written in assembly language for the IBM 7090. It had a simple syntax, only one datatype, the string, no functions, and no declarations and very little error control. However, despite its simplicity and its 'personal' nature its use began to spread to other groups. As a result, the authors decided to extend it and tidy it up.
SNOBOL2 did exist but it was a short-lived intermediate development version without user-defined functions and was never released.
They rewrote SNOBOL1 and added functions, both standard and user-defined, and released the result as SNOBOL3. SNOBOL3 became quite popular and was rewritten for other computers than the IBM 7090 by other programmers. As a result, several incompatible dialects arose.
As SNOBOL3 became more popular the authors received more and more requests for extensions to the language. They also began to receive complaints about incompatibility and bugs in versions that they hadn't written. To address this and to take advantage of the new computers being introduced in the late 1960s, the decision was taken to develop SNOBOL4 with many extra datatypes and features but based on a virtual machine to allow improved portability across computers. The SNOBOL4 language translator was still written in assembly language. However the macro features of the assembler were used to define the virtual machine instructions of the SNOBOL Implementation Language, the SIL. This very much improved the portability of the language by making it relatively easy to port the virtual machine which hosted the translator by recreating its virtual instructions on any machine which included a macro assembler or indeed a high level language.
The machine-independent language SIL arose as a generalization of string manipulation macros by Douglas McIlroy, which were used extensively in the initial SNOBOL implementation. In 1969, McIlroy influenced the language again by insisting on addition of the table type to SNOBOL4.
SNOBOL is distinctive in format and programming style, which are radically different from contemporary procedural languages such as Fortran and Algol.
SNOBOL4 supports a number of built-in data types, such as integers and limited precision real numbers, strings, patterns, arrays, and tables (associative arrays), and also allows the programmer to define additional data types and new functions. SNOBOL4's programmer-defined data type facility was advanced at the time—it is similar to the records of the earlier COBOL and the later Pascal programming languages.
All SNOBOL command lines are of the form
- label subject pattern=object:transfer
Each of the five elements is optional. In general, the subject is matched against the pattern. If the object is present, any matched portion is replaced by the object via rules for replacement. The transfer can be an absolute branch or a conditional branch dependent upon the success or failure of the subject evaluation, the pattern evaluation, the pattern match, the object evaluation or the final assignment. It can also be a transfer to code created and compiled by the program itself during a run.
A SNOBOL pattern can be very simple or extremely complex. A simple pattern is just a text string (e.g. 'ABCD'), but a complex pattern may be a large structure describing, for example, the complete grammar of a computer language. It is possible to implement a language interpreter in SNOBOL almost directly from a Backus–Naur form expression of it, with few changes. Creating a macro assembler and an interpreter for a completely theoretical piece of hardware could take as little as a few hundred lines, with a new instruction being added with a single line.
Complex SNOBOL patterns can do things that would be impractical or impossible using the more primitive regular expressions used in most other pattern-matching languages. Some of this power derives from the so-called 'SPITBOL extensions' (which have since been incorporated in basically all modern implementations of the original SNOBOL 4 language too), although it is possible to achieve the same power without them. Part of this power comes from the side effects that it is possible to produce during the pattern matching operation, including saving numerous intermediate/tentative matching results and the ability to invoke user-written functions during the pattern match which can perform nearly any desired processing, and then influence the ongoing direction the interrupted pattern match takes, or even to indeed change the pattern itself during the matching operation. Patterns can be saved like any other first-class data item, and can be concatenated, used within other patterns, and used to create very complex and sophisticated pattern expressions. It is possible to write, for example, a SNOBOL4 pattern which matches 'a complete name and international postal mailing address', which is well beyond anything that is practical to even attempt using regular expressions.
SNOBOL4 pattern-matching uses a backtracking algorithm similar to that used in the logic programming language Prolog, which provides pattern-like constructs via DCGs. This algorithm makes it easier to use SNOBOL as a logic programming language than is the case for most languages.
SNOBOL stores variables, strings and data structures in a single garbage-collected heap.
The 'Hello, World!' program might be as follows...
A simple program to ask for a user's name and then use it in an output sentence...
To choose between three possible outputs...
To continue requesting input until no more is forthcoming...
The classic implementation was on the PDP-10; it has been used to study compilers, formal grammars, and artificial intelligence, especially machine translation and machine comprehension of natural languages. The original implementation was on an IBM 7090 at Bell Labs, Holmdel, N.J. SNOBOL4 was specifically designed for portability; the first implementation was started on an IBM 7094 in 1966 but completed on an IBM 360 in 1967. It was rapidly ported to many other platforms.
It is normally implemented as an interpreter because of the difficulty in implementing some of its very high-level features, but there is a compiler, the SPITBOL compiler, which provides nearly all the facilities that the interpreter provides.
The GnatAda Compiler comes with a package (GNAT.Spitbol) which implements all of the Spitbol string manipulation semantics. This can be called from within an Ada program.
The file editor for the Michigan Terminal System (MTS) provided pattern matching based on SNOBOL4 patterns.
Several implementations are currently available. Macro SNOBOL4 in C written by Phil Budne is a free, open source implementation, capable of running on almost any platform. Catspaw, Inc provided a commercial implementation of the SNOBOL4 language for many different computer platforms, including DOS, Macintosh, Sun, RS/6000, and others, and these implementations are now available free from Catspaw. Minnesota SNOBOL4, by Viktors Berstis, the closest PC implementation to the original IBM mainframe version (even including Fortran-like FORMAT statement support) is also free.
Although SNOBOL itself has no structured programming features, a SNOBOL preprocessor called Snostorm was designed and implemented during the 1970s by Fred G. Swartz for use under the Michigan Terminal System (MTS) at the University of Michigan. Snostorm was used at the eight to fifteen sites that ran MTS. It was also available at University College London (UCL) between 1982 and 1984.
Snocone by Andrew Koenig adds block-structured constructs to the SNOBOL4 language. Snocone is a self-contained programming language, rather than a proper superset of SNOBOL4.
The SPITBOL implementation also introduced a number of features which, while not using traditional structured programming keywords, nevertheless can be used to provide many of the equivalent capabilities normally thought of as 'structured programming', most notably nested if/then/else type constructs. These features have since been added to most recent SNOBOL4 implementations. After many years as a commercial product, in April 2009 SPITBOL was released as free software under the GNU General Public License.
According to Dave Farber, he, Griswold and Polonsky 'finally arrived at the name Symbolic EXpression Interpreter SEXI.'
All went well until one day I was submitting a batch job to assemble the system and as normal on my JOB card -- the first card in the deck, I, in BTL standards, punched my job and my name -- SEXI Farber.
One of the Comp Center girls looked at it and said, 'That's what you think' in a humorous way.
That made it clear that we needed another name!! We sat and talked and drank coffee and shot rubber bands and after much too much time someone said -- most likely Ralph -- 'We don't have a Snowball's chance in hell of finding a name'. All of us yelled at once, 'WE GOT IT -- SNOBOL' in the spirit of all the BOL languages. We then stretched our mind to find what it stood for.
Common backronyms of 'SNOBOL' are 'String Oriented Symbolic Language' or (as a quasi-initialism) 'StriNg Oriented symBOlic Language'.
- ^Gimpel, J. F. 1973. A theory of discrete patterns and their implementation in SNOBOL4. Commun. ACM 16, 2 (Feb. 1973), 91-100. DOI=http://doi.acm.org/10.1145/361952.361960
- ^'Dr. Dobb's: Programs That Transform Their Own Source Code; or: the Snobol Foot Joke'. Dobbscodetalk.com. Retrieved 2011-12-04.
- ^Contact details. 'perlre'. perldoc.perl.org. Retrieved 2011-12-04.
- ^'Recursive Regex Tutorial'. Retrieved 2017-03-19.
- ^Ralph E. Griswold, David R. Hanson, 'An Overview of SL5', SIGPLAN Notices12:4:40-50 (April 1977)
- ^See Chapter 1 of The Macro Implementation of SNOBOL4
- ^SNOBOL4 has been implemented using C to recreate the virtual machine instructions.
- ^Griswold, Ralph (1978). 'A history of the SNOBOL programming languages'(PDF). ACM SIGPLAN Notices. ACM. 13 (8): 275–308. ISSN0362-1340.
- ^Wexelblat, Richard L. (2014). History of Programming Languages. Academic Press. p. 784.
- ^Introduction to the MTS file editor, University of Michigan Computing Center, 1986.
- ^'SNOSTORM', MTS Volume 9: SNOBOL4 in MTS, Computing Center, University of Michigan, June 1979, pages 99-120. Retrieved 1 September 2014.
- ^'The Snocone Programming Language', Andrew Koenig, USENIX (Portland, Oregon), June 1985. Retrieved 2 September 2014.
- ^WORTH READING Wikipedia entry on SNOBOL -- the TRUE story NOT Wikipedias (Dave Farber, Interesting People mailing list, 26 December 2008)
- ^Computers and the humanities1:158, 1967.
- ^Jack Belzer et al., eds., Encyclopedia of Computer Science and Technology, CRC Press, 1979, ISBN0-8247-2263-9. 13:173 at Google Books
Basic Programming On Mac
- Emmer, Mark B. SNOBOL4+: The SNOBOL4 Language for the Personal Computer User. Englewood Cliffs, NJ: Prentice Hall, 1985 (ISBN0-13-815119-9).
- Gimpel, James F. Algorithms in SNOBOL4. New York: Wiley, 1976 (ISBN0-471-30213-9); republished Salida, CO: Catspaw, 1986 (ISBN0-939793-00-8).
- Griswold, Ralph E. The Macro Implementation of SNOBOL4. San Francisco, CA: W. H. Freeman and Company, 1972 (ISBN0-7167-0447-1).
- Griswold, Ralph E., J. F. Poage, and I. P. Polonsky. The SNOBOL4 Programming Language. Englewood Cliffs, NJ: Prentice Hall, 1968 (ISBN0-13-815373-6).
- Griswold, Ralph E. String and List Processing in SNOBOL4: Techniques and Applications. Englewood Cliffs, NJ: Prentice Hall, 1975 (ISBN0-13-853010-6).
- Hockey, Susan M.Snobol Programming for the Humanities. New York: Clarendon Press; Oxford: Oxford University Press, 1985 (ISBN0-19-824676-5).
- SNOBOL at Curlie
- Oral history interview with Ralph E. Griswold—Griswold discusses development of SNOBOL Charles Babbage Institute, University of Minnesota, Minneapolis.
- Charles Hall Collection on the SNOBOL Programming Language. Charles Babbage Institute, University of Minnesota, Minneapolis.
- Try It Online (Snobol4/CSNOBOL) Online compiler