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ALGOL (ALGO rithmic Language) is one of several high level languages designed specifically for programming scientific computations. I t started out in the late 1950's, first formalized in a report titled ALGOL 58, and then progressed through reports ALGOL 60, and ALGOL 68.
I t was designed by an international committee to be a universal language. T heir original conference, which took place in Zurich, was one of the first formal attempts to address the issue of software portability. ALGOL&#
39;s machine independence permitted the designers to be more creative, but it made implementation much more difficult. A lthough ALGOL never reached the level of commercial popularity of FORTRAN and COBOL, it is considered the most important language of its era in terms of its influence on later language development. ALGOL' s lexical and syntactic structures became so popular that virtually all languages designed since have been referred to as «ALGOL — like»; that is, they have a hierarchical in structure with nesting of both environments and control structures. S ee Backus [1, 2], Baumann, Feliciano, Samelson [3], Naur, Backus, Bauer, Green, Katz, McCarthy, Perlis, Rutishauer, Samelson, Vauquois, Wegstein, van Wijngaarden, and Woodger [12] and many subsequent papers. T
he papers by Naur and Perlis in Wexelblatt [18, pp. 75−139] give a very comprehensive discussion of ALGOL’s history on both sides of the Atlantic. Although ALGOL was implemented on a new powerful Boroughs machine in about 1960 (IBM wouldn’t have anything to do with it), it was originally intended as a language for the expression and communication of algorithms in general; at one time, Communications of the Association for Computing Machinery published algorithms in ALGOL.
" G race Hopper led a group at Univac to develop FLOWMATIC in 1955. T he goal was to develop business applications using a form of English like text. I n 1959, the U.S. Department of Defense sponsored a meeting to develop Common Business Language (CBL), which would be a business-oriented language that used English as much as possible for its notation. B
ecause of divergent activities from many companies, a Short Range Committee was formed to quickly develop this language. A lthough they thought they were designing an interim language, the specifications, published in 1960, were the designs for COBOL (Common Business Oriented Language). COBOL was revised in 1961 and 1962, standardized in 1968, and revised again in 1974 and 1984." Pratt and Zelkowitz [13, p.
6].
The original version was LISP 1, invented (some historians prefer the use of the word «discovered») by John McCarthy at MIT in the late 1950s. McCarthy [11]. LISP is actually older than any other high level language still in use except FORTRAN, and has undergone considerable change over the years. Modern variants are quite different in detail. See below.
With the introduction of its new 360 line of computers in 1963, IBM developed NPL (New Programming Language) at its Hursley Laboratory in England. After some complaints by the English National Physical Laboratory, the name was changed to MPPL (Multi-Purpose Programming Language), which was then shortened to just PL/I. PL/I merged the numerical attributes of FORTRAN with the business programming features of COBOL and the syntax of ALGOL. PL/I achieved modest success in the 1970s, but its use today is dwindling as it is replaced by C, C++ and Ada. The Cornell University educational subset PL/C achieved modest success in the 1970s as a student PL/I compiler.
These originated in the work of the NATS Project (National Activity for Testing Software), sponsored by the National Science Foundation in the 1960's, and are precursors of BLAS (Basic Linear Algebra Subprograms), a collection of high quality «building block» routines for performing basic vector and matrix operations. Level 1 BLAS do vector-vector operations, Level 2 BLAS do matrix-vector operations, and Level 3 BLAS do matrix-matrix operations. Because the BLAS are efficient, portable, and widely available, they’re commonly used in the development of other high quality linear algebra software.
Lawson, Kincaid, Krogh [10]. A modern version is LAPACK, which is written in Fortran77 and provides routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems. The associated matrix factorizations (LU, Cholesky, QR, SVD, Schur, generalized Schur) are also provided, as are related computations such as reordering of the Schur factorizations and estimating condition numbers. Dense and banded matrices are handled, but not general sparse matrices. In all areas, similar functionality is provided for real and complex matrices, in both single and double precision.
http://www.netlib.org/lapack/index.html, accessed 06/17/03 .
According to Charles Renfro [14], LIMDEP began in 1974 at the University of Wisconsin as an implementation of a RAND Corporation report by M. Nerlove and S. J. Press on multivariate loglinear and logistic models for the analysis of categorical data. RATS was also launched about this time as well.
Subsequently described in Kernighan and Ritchie [9].
Opinions, however, are not uniformly laudatory. One critic describes C++ as «a huge, bloated, hackridden monster.» C++ is a fairly complicated object-oriented language derived from C. The syntax of C++ is a lot like C, with various extensions and extra keywords needed to support classes, inheritance and other object-oriented features. C++ was originally developed as an extension to C, but quickly evolved into a separate language.
O bject-oriented languages define not only the data type of a data structure, but also the types of operations (functions) that can be applied to the data structure. I n this way, the data structure becomes an object that includes both data and functions. I n addition, programmers can create relationships between one object and another. F
or example, objects can inherit characteristics from other objects. O ne of the principal advantages of object-oriented programming techniques over procedural programming techniques is that they enable programmers to create modules that do not need to be changed when a new type of object is added. A programmer can simply create a new object that inherits many of its features from existing objects. This makes object-oriented programs easier to modify.
The original object-oriented language, Smalltalk, was developed by Alan Kay in 1973. Modern variants include Java as well as C++, Dictionary of Programming Languages [7].
These languages themselves are largely written in FORTRAN, C and C++.
In a paper also in this issue, Houston Stokes [38] describes his development of B34S which evolved from an LS regression package beginning in about 1968.
C ringely [5] says that these clones were made possible by the technique of «reverse engineering» which IBM had used to produce a non-patent-infringing version of the Apple using components available off the shelf, but such a characterization appears nowhere else that I have been able to find. H owever, Kildall and IBM did develop a key element crucial to the wide-spread use of the PC, which was spread by «reverse engineering,» the code they called BIOS (for Basic Input/Output System). T his code, or modifications of it, permitted essentially the operating system to run on many different clones. (C eruzzi {4, pp.
238−239].)
There were antecedents, of course: IBM created a machine in 1975, the Model 5100, with a proprietary IBM cpu, which is sometimes described as the first portable, but it weighed about 50−60 pounds, so is questionably described as «portable. The Model 5100 incorporated in one piece all the parts, including the screen, the keyboard and the system unit. It is this one piece construction that suggests its portability. The Osborne 1, released in 1981, although it weighed in at 24 pounds, could be described as the first «Notebook.»
Many computations can be best done by first expressing the result one wants analytically and then evaluating the analytical result numerically for some specific values of the arguments. This convergence is surely an example of the Hotelling principle in which hot dog vendors competing on a finite beach with a uniformly distributed demand converge toward the center of the beach. Davidson [6]
