About high-level and not-very-high-level programming languages (APL vs. classical languages )

par Andrei Buzin



Twenty five years ago I was a student in applied mathematics fter a concise course of programming by machine codes we began study the programming language ALGOL - one of a few high-level language of that time. rogramming with ALGOL was essentially more intellectual work than programming with machine codes. Nevertheless, I was very surprised, when the teacher gave us the task to calculate the result of 22 multiplication. Too much routine operations we must make to solve this elementary problem:  a)to write the program with head, begin, output, end; b)supply the program with operating system directives; c)debug, translate, and start in special manner.

Computers have made the giant progress in last 25 years...Now anybody knows that 22 is an example not for computers but for calculators, and test example for modern programming languages is not the printing of 4, but the printing of "Hello World". Let we see how the modern JAVA carries out this task [1]:


class HelloWorld {

public static void main (String args[]) {

System.out.println("Hello World");}}

Are here not too many words for describing such a work?

The high-level programming languages differ from low-level languages firstly by their possibility to operate with the named (not numerated) data, secondly by substitution of often used command constructions by more accustomed lexems (FOR...NEXT, IF...THEN..., WRITE etc.). The evolution of classical programming paradigm (procedural, structural, object-oriented) concerns the structure of program code, in little extent - the structure of data; practically nothing was to simplify the elementary language constructions. Descriptions of input/output, using of external libraries, processing of complex data structures remain very diffuse in classical programming languages. These languages don't shoulder the work, which must be by intellectual assistant - the automatic research of data used and relief in processing, input and output of the data in the whole (not by their elements). In this sense C++ remains on FORTRAN level.

The reason is that the modern programming languages was developed by programmers for programmers, unlike first programming languages, which was developed for engineers and applied scientists. Not the universal languages but corresponding software packages was proposed to use for applicators (engineers and scientists). This makes the human-computer interaction more effective in many cases, and this tendency will remain in future apparently. The necessity to wield a universal programming language will be the portion of system programmers only.

Nevertheless it is avowed that engineers and applied mathematicians must study programming languages. There are some reasons in this tradition. Really, it is not always possible to find quickly inexpensive adequate software. Really, the study of programming languages gives the practice of algorithmization and of information structurization. Really, some software systems can be extended by the user, if this user knows one of popular programming language.

But the question about the efficiency of teaching classical universal programming language for applicators is problematic. Why such a user must know how the processor registers works and how the memory is allocated; why must he write such programs, the most part of which has no direct relation to the problem? Is it interesting for you how is organized the coffee-grinder, you are using to prepare your coffee?

Two cultures


To see the large difference between mathematical and programming cultures we can compare the difference in their terminology. The terms "variable", "function", "operator" are used both in mathematics and in programming, but the meanings of this words are essentially different in each scope.

The other confirmation of divergence of two cultures is their approach to data arrays. The commonly used operations with data arrays such as transposition MT, inverse M‑1, minimax, trace , minor , where M is a matrix, or mean  , norm, where x is a vector, are accustomed in mathematics, but are programmed by unwieldy cycles. The operations with functions (in mathematical sense) is also diffuse; for example, if we want designate the first derivation of a function, we must write few lines of code (and double cycle for Jacobian); unlike the mathematical notation, which is very concise.

Thoughthere are libraries' procedures for operations with arrays and functions, these can not cover all desirable operations. The elementary matrix by scalar multiplication demands in general case the using of double cycle. We must use the double cycle by multiplication of column-vector by row-vector too. Moreover, the programmer must explain to computer, that the result will be two-dimensional array (matrix) and must describe it especially.

Arrays and functions are not the most complex objects considered in mathematics. Until the last time (when the structure type appeared in C) the classical programming languages do not give the convenient means for nested arrays representation. It is impossible to describe the structure such as genealogical tree in PASCAL, and rather hard it can be made in C.

Worth to say that the object-oriented paradigm has partly solved the problem of definition of new operations with arbitrary structures (so called overloading of operations), but the detailed descriptions of structures and operations definitions take a bit of doing.

Two problems are important for programmer, but not interesting for mathematician: the memory allocation of data and organization of cycles.

First problem arises because the representation of data can influence on program processing. The programmer must know how the variable with value 2, for example is represented in the memory: is it integer or real, of ordinary or of double precision. The result of the division 4/2 is unambiguous for mathematician, but it is not true for programmer.

What about cycles, we can say, that a programmer thinks in terms of cycles. To qualify the programmer means to drill the students to speak in terms of cycles. Diong so is the most complex task in teaching programming, because the cycle are not very often in natural and in mathematical languages. Why the task Say the maximal value in this numerical set is easy for scholar, but the task of writing the computer program in programming language, which find the maximal value among the numbers, claims special training? The reason is that by using classical programming we must represent the problem as repetition of some unified operations. But the cycle is not the essence of problem involved (see, by the way, that there are many types of cycles, which solves this problem). In English or in mathematical language (), the solution is more concise; I believe the human mind does not work cyclically solving this task.

We can regret that if we discard the cycles, then the students will not be able to solve the problems algorithmicaly, but these doubt is of the same sort as the doubt about using calculator in the school.

Brevity is the sister of talent


Let we see how the classical Pascal solves the problem to find maximum among the set of numbers. The following text is adopted from tutorial [2]; but the solution is analogues in other classical languages.




Program Max(input,output); (*1*)

const M=10;N=20; (*2*)

var i,j:M..N; (*3*)

X:array [M..N] of real; (*4*)

begin (*5*)

for i:=M to N do (*6*)

read (X[I]); (*7*)

j:=M; (*8*)

for i:=M+1 to N do (*9*)

if X[i]>X[j] (*10*)

then j:=i; (*11*)

writeln(X[j]); (*12*)

end. (*13*)


This program inputs eleven numbers from keyboard and outputs one maximal value among these numbers (lines are enumerated for citation).

The first word Program is to show the head program in software package (which consists of only one program in our case). It is synonym of Main in C. Second word Max is the name of program and is, of course, necessary.

After this in parenthesis (input, output) is the message that the program will interact with input/output devices. Can the translator guess this fact from lines 7 and 12 or not? This message looks in C as preprocessor directive such as #include <iostream.h>.

Semicolons are out discussing - it is a matter of taste.

Line 2 can be used for the sake of rapid modification of the program, in the case if the data involved will be consisted of twelve, not eleven numbers. Can the translator count the numbers, which will be inputted? Why not?

Line 3 works out two problems. At first, - allocate two bytes for each of variables i and j and describe the format of these bytes. Secondly, - tell to translator to watch the variables i and j can not pass the limits M and N. The last instruction is reasonable: it enhances the reliability of the program. But what is interesting: we make themselves the asperity by using the concrete (i-th) elements of array (X[i]), then we solve the problem of consistency of variable i. More logically will be to say for translator: do it with all elements of array.

Line 4. Reserve 11 four-bytes cells for elements of vector X. Check X can not be the simple variable, two-dimensional array or vulgarism. If you do not confide to the user (there are, of course, some grounds for such disbelief), is it not more simple to check his input in line 7?

Lines 2-4 are the impost for our blunt translator. We are questioned for input some numbers and output one of them in the screen. Note, in formulation of our problem there are no word that input and output must have the names. What is the reason to invent five names? I think, it is routine work and can be done by computer.

Lines 5 and 13. In classical languages it is always necessary to separate something from function (program) body. Writing Begin and End was bored for inventors of C and they changed them for unique symbols { and } consistently. Thats more convenient, but you can see, that this separation is the consequence of grammatical parting of program. The classical program has usually three part: head, descriptions and the body.

Lines 6 and 7. Input of X array. Of course, we must order this work for translator. But why must we do the input 11 times for each element of X? In line 4 we have told to our translator, that X has 11 elements, now we must ask about first, second and so on elements separately. We converse with translator as with child of three years; the child of four years can answer the less detailed question Say some numbers already. If anything is known about X, then to realize the instruction Read X is not more complex then the lines 6-7. Why must the programmer grind this fact to translator?

Lines 8-12 are the essence of solution. They are, in fact, the phraseFind maximum element in numerical set given translated from English to Pascal.This phrase is, of course, ineluctable and if the translator can understand it only in such form, then we must write it in this form. It characterize only the possibilities of the translator. Other translators (Excel, Mathematica, mathematician, Russian, Englishmen, Japanese) can understand this phrase in other form (see Table).


Language Problem formulation
Russian .
English Find maximum element in numerical set given.
Pascal j:=M;for i:=M+1 to N do if X[i]>X[j] then j:=i; writeln(X[j]);
C++ j=M;for (int i=M+1;i<N;i++) if(X[i]>X[j])then j=i;cout<<X[j];
Excel and other languages with function Max Max(X)
Mathematics max {xM, xM+1,..., xN}


Lines 8-12 reflect not only the essence of the problem, but the style of thinking, bound up with the classical programming languages. If you are proposed to find the maximum among eleven numbers, will you operate in such a manner: memorize the first number, consider the second, if it is more then memorized number, then change the later, consider the third... and so on? I believe not.

Let we discuss the line 12 separately (This discussion is also true for line 7). This line gives to the translator a directive to output j-th element of X to the screen, then move the cursor to the next line. Firstly, the parenthesis here are surplus: writeln is an special keyword and to separate this word from argument one special symbol (which can not be used as the first symbol of argument) can be used (blank, for example). Note, that in the case, when the name of output procedure is constructed by the symbols, prohibited for argument, the separation will be quite unnecessary. Secondly, let we see, what will happen, if we will forget to write the name writeln. It will remain the expression X[j]. Pascal treats this expression as an error. But it is very natural to treat this expression as the request to output the value X[j]. In this case the notation will be more concise and, what is important, more usually: to compute 22 we must write only 22, and to output Hello World - only 'Hello World'.

Summarize our analysis of program involved. To claim the computer to give one maximum from the set of numbers, we had writtten about 150 symbols. Much of that we had written, has no relation to the essence of problem involved, but describes the structure of data and very detailed instructions how to operate these data (in terms of described structure). Really, Pascal is more convenient in comparison with assembler, but do you not feeling that it concuss the programmer to do the routine work?

A Programming Language


What orders we must deliver to the computer to solve the maximum problem? Try to formulate this orders in such a manner, that on the one hand, they will be represented as clear algorithm, on the other hand, they will be not very complex to translate in classical programming language (that is not very complex to translate in machine code):


[0] Max

[1] Check_whether_the_operations_correspond_to_the_objects_processed

[2] Insert_the_elementary_maximum_function_between_the_elements_of_the_object_inputed_from_keyboard_and_compute_the_expression


Such a program will calculate the maximum of input set of numbers and output the maximum to the screen, because we believe that the explicit result of expression (calculated in line [2]) will be printed in the screen by default.

Now we use some abbreviations in our algorithm (numeration is only for citation):


[0] Max

[1] R TRAP0 'C' '''Some error!'''

[2] /R


If you mean, that this program is the product of my dreams, you are mistaken! It is the real program in APL (version DyalogAPL/W v.7.2.5).

Let we see now that the problem is resolved in essence by this program. Are you asking for data input? Yes; the program asked for the data by the aid of symbol R in line [2]. It may be this symbol makes afraid, because it is not present on the keyboard and you must memorize the keyboard placement of such symbols. May be it is easier for you to remember that input is designated by read or cin, or mouthful istrstream? Every man to his own taste. If you want, you can redesignate R by read or even by read(X). But the symbol R has a strong advantage in comparison with other inputs in different languages: it is simultaneously the input order and the variable, which has the value of input! We are asked to analyze the input, not the unknown X, and in APL we must not invent some new name for this input. Line [2] includes the instruction to proceed the input.

Left from the symbol R in line [2] you can see what the translator must do with the input, that is the description of computing algorithm. But be not afraid that you must memorize the exotic names such as /. Though this is really the name of function maximum of the number set, it consists of two independent lexems, which describe two separate actions:  is the name of elementary function of maximum between two numbers and / is the name of so called reduction - operation, which inserts the name of any dyadic function between the elements of the set (if possible). So, notation / designate the concise notation of algorithm which looks for a maximum in the number set (if the number set is represented as one-dimensional array, then the result is obvious; in other cases there are some default conventions about grouping of elements).

Now then, in line [2] is the following instruction: insert the maximum function between elements of input. If, for example, we shell input the numbers 4,7,5 then the function / generates the expression 475, which will be treated by APL-translator as max{4,max{7,5}} and gives the number 7. Explicit result will be put on the screen by default. Let we see the protocol of work of our APL-function:




7 4 5 19 23.7 4 28 6 28 11 11



So, the algorithm of solving is in all in line 2. What is the mission of lines [0] and [1]?

Line [1] executes the checking of input data. In fact it simulates the implicit checking which is made by Pascal due to descriptions of the data. This line reveals some types of errors in input, for example, if the input is symbolic, not numerical. It seems strange, that APL, which disembarrasses the user from routine operations, ask him for checking the data manually. But the time to describe this checking is comparable with the time spending for descriptions of data. On the other hand the programmer is free in his choice by controlling the data.

Line [0] serves to block all operations (check and maximum search) in one function. If you dont need the data checking, you can solve the problem interactively in one line:




7 4 8 3


What are the conclusions of our comparative analysis of two programming styles? APL excuses us from practically all operations, which has no relations with the problem. We must not invent the names of memory cells, which will be used by computer solution. We must not describe their structure. We was delivered from element by element input and output of data. And finally, the algorithm was described only by two symbols.

The expression /R is on one hand the correct APL-expression, on the other hand, it can be used always, where the function Max must be used. The algorithm expressed by this three symbols means: Input the data, Find the maximum and Output the result. Important is that it is not the mnemonic name, but real algorithm, written by three separately lexems. Similarly, summation of one-dimensional array of numbers, which are inputted from keyboard, can be written in such a way:




7 4 8 3


The product of elements of arbitrary numeric vector X can be coded as /X.

The result of expression is explicit result and can be used in other expression:


 1+—/7 4 8 3


Note, that the reason of conciseness of APL-notation is not the same as in languages, which have a giant number of built-in functions (Mathematica, MathCad etc.). The notation of maximum algorithm is very concise because of a)using of operation (/), defined on function and

b)using the special symbols (,R).

The second reason is not principal, because the notation #max #reduction #input is also essentially more laconic than of classical languages one.

APL tries to deliver the programmer from routine work. In this sense it is more intellectual and is the language of higher level in comparison with Pascal, C and so on.

How the native language is chosen


The famous Russian poet Majakovski wrote, that he would choose the Russian language because Lenin was spoken it. I believe that the reason to chose C++ is of this type: Bill Gates and his company speak it. Choice of method of communication with computer is determinated not only by effectiveness of this method, but also by its accessibility and by its popularity in your environment. For example, OS/2 is evaluated by many programmers as more effective than Windows, but the later is essentially more popular.

Traditionally the education in computer science means the study of classical programming language. The selection one of this language depends to a great extent from taste of teacher, not from advantages of language. Sometimes there are absurd situation, when the students study Basic at first year, Pascal at second, C at third. The difference between this languages is linguistic, not ideological.

The ideological innovations are that what make the languages more effective. For example, the object-oriented idea permits to make programming more effective with the mean of fast cloning of large objects. Object-oriented Pascal 7.0 differ from Pascal 4.0 more then from C++.

At the beginning of computer era the communication with computer was in the level of baby talk. Now the computers are in the age of maturity and we can communicate with them by more serious languages. The language used depends, of course, on the theme of communication. If you are using computer to create the booklets, the 3DSudio is more useful for you than Pascal. This languages is prior for educational institution, which profess admen. Teaching baby talk is not serious work.

There is some by-effect in study of classical procedural languages. They educate in the students some order in problem solution. This means the partition of the problem in such parts, which have obvious solution. But obvious solution is not common term! People say that Landau (the Nobel laureate in physics) liked to stump his colleagues by the phrase Its obvious! related with very nontrivial mathematical statements.

If the standard course of mathematics includes the concept of maximum, scalar and vector product, matrix multiplication etc., then why their notations in programming language are in terms of arrays elements? May be more serious language can be chosen to code mathematical operations?

Once more about APL

These ideas came to my mind while I think about the new course of computer science for applied mathematicians. It is obvious that in teaching computer science the evolution of computer technologies in direction to the user must be considered. If for some specialities there are not the special software and the universal programming language is useful, why is this language C or Pascal? This languages are not convenient for fast programming and modification of mathematical models. I mean, fast enough to see the computer as an intellectual assistant for applied mathematicians, who develops and investigates very often changed models. The solution of any auxiliary problem (sort of array, matrix inverse and so on) takes too much time and attention.

My shift to APL was stimulated in great extent by some monographs in computer investigation of mathematical models. Very large part of these books was occupied by the text with programming code.

The situation changes striking with APL. In one lab you can solve several standard problems. It is promoted by APL-ideology and conciseness of this language.

Let we see some examples of problem solution by APL. Note, that sometimes you can solve the problem not in form of function (program), but in form of one interactive expression. At first, see the simplicity of input/output operations with arrays.


1)Add 1 to each component of the vector:

1+2 3 4 5 Programmers directive

3 4 5 6 Answer


2)Add 1 to input:

1+ΠProgrammers directive

Œ: Input demand

31 2 3 Input

4 7 10 Answer

Note that input can be an expression!


3)Summarize all components of a vector:

+/3 4 5



4) Assign to variable M the value of 32-matrix and output the matrix to the screen:

+M„3 29 8 7 6 5 4

9 8

7 6

5 4


5) Calculate the minimum in each column of matrix M:


5 4


6) Square each element of matrix M:


81 64

49 36

25 16


7)Define Sin as the name of function to calculate sine:


Sine in APL is a special case so-called trigonometric primitive .

This example shows, that APL submits the possibility of overdetermination of functions’ names; practically you can achieve similarity of your programs with text in Pascal or other classical language by such overdeterminations.


8) Sine of squares of elements of matrix M:

Sin M*2

0.6298879943 0.9200260382

0.9537526528 0.9917788534

0.1323517501 0.2879033167


9) Calculate MMT (matrix product M and transposed M)


145 111 77

111 85 59

77 59 41


10) Generate, assign to variable A and output to the screen one random 33-matrix with elements in interval [0; 1]:

+A„0.1?3 310

0.5 0.8 1

0.8 0.3 0.1

0.8 0.4 0.7


11) Generate, assign to variable A and output to the screen one unit 33-matrix:


1 0 0

0 1 0

0 0 1


12) Inverse matrix (E-A)-1:


0.1617507136 0.608943863 0.742150333

0.3044719315 0.6184586108 0.808753568

0.8372978116 0.7992388202 0.2759276879


13) Four first powers of matrix A:


0.5 0.8 1 1.69 1.04 1.28 2.701 2.176 2.69 5.2433 3.8896 4.8016

0.8 0.3 0.1 0.72 0.77 0.9 1.696 1.167 1.427 2.9232 2.2777 2.8116

0.8 0.4 0.7 1.28 1.04 1.33 2.536 1.868 2.315 4.6144 3.5152 4.3433


14) Number of negative elements in matrix (E-A)-1:




APL works successful with arrays, containing the data of different types and structure.

15) Assign and output the variable Q as a matrix with numbers and symbols:


+Q„†('' 'ao' 'empo' 'Copo')('' 10 20 30)('' 3 2 1)('Aycm' 4 5 60000) Programmer directive

ao empo Copo |

10 20 30 |

3 2 1 |Answer

Aycm 4 5 60000 |


Note that output was formatted automatically.

16)Add the Total column to matrix Q:

(Q),(›' Total'),+š1 1‡Q

Aycm otal

ao 10 3 4 17

empo 20 2 5 27

Copo 30 1 60000 60031


17)APL works with data structures of arbitrary complexity; its description is constructive! You can see below example of a matrix which elements are scalars, nested matrix, vectors and function definition yet. Different elements are enclosed in frames for visualization:




.…--. |

| 2 A |3 B| |

| - '+--' |

| .…----------. .…----------------------. .------------. |

| | .…--. | ‡ .…--. | | 0 1 +. | |

| | 4 5 |ABC| | | 2 A |3 B| | | 1 0 | |

| | '---' | | - '+--' | '’-----------' |

| '----------' | .…----------. | |

| | | .…--. | 2 A | |

| | | 4 5 |ABC| | - | |

| | | '---' | | |

| | '----------' | |

| '----------------------' |



Now we will show some programs in APL, its description and use (Programs in APL are of two types - functions and operators).


18) The following text is the definition of a function which calculates the polynomial in points x (it can be a vector) with coefficients (the line numeration is not necessary):


[0] r„a Pol x

[1] r„(,[]x)ƒa


Using of this function is much more flexible than in classical programming languages:


1 0 1 Pol 0.0110 Calculate 2+1 in points 0.01,0.02,...,0.1

1.0001 1.0004 1.0009 1.0016 1.0025 1.0036 1.0049 1.0064 1.0081 1.01


ΠPol ΠCalculate polynomial with coefficients and points inputted from keyboard:


1 2 3 Input points


1 0 1 Input coefficients

2 5 10


19)User defined operator to find the numerical (with increment ) derivative of function f in points x:

[0] r„(‘ Diff f)x

[1] r„((f x+‘)-f x)‘


Example of use:


 0.001 Diff Sin 3.14 0 1.57

0.9999993614 0.9999998333 0.0002963267782


Note that in APL, analogous as in mathematics, function of function is called operator. The similarity of operators in APL and in mathematics is more stronger. Operator applied to the function generates other function (we mean function as a mapping data into data). For example, the expression 0.001 Diff Sin is the name of some function (numerical approximation of cosine), which can be used as any other function name, say, we can differentiate it:


 0.001 Diff (0.001 Diff Sin) 3.14 0 1.57

0.0005926535057 0.0009999997501 0.9999998959


It is possible to differentiate more complex functions. Here is an example of numerical derivation (with increment 0.001) of polynomials x2+1 in points 0.01,0.02..., 0.1:

0.001 Diff (1 0 1Pol) 1 2 3

2.001 4.001 6.001


20)Here is the user function which calculates the coefficients of trigonometric interpolation (up to m-th) of an arbitrary set of points, given by their coordinates on a plane (spectral analysis).


[0] rm Furmin xy;x;y

[1] x yxy

[2] ry}1,(2x.׼m),1x.׼m


21) Newton method for solution of the system of algebraic equations . The names of a vector function F and matrix function DF (Jacobian) are the operands of APL-operator Newton. Initial approximation is x0, halt parameters are N and E.


[0] x„NE(F Newton DF)x0;n;N;E;w

[1] Newton method for the system F(x)=0 with Jacobian DF

[2] initial point x0;max number of iterations N; accuracy E

[3] N E„NE Halt parameters

[4] n„0   Iterations counter

[5] x„x0

[6] lOOP: x0„x

[7] x„x0-(F x0)ŽDF x0 Iteration

[8] …((N<n„n+1)(E<0.5*w+.w„x-x0))/nOT lOOP

[9] …0

[10]nOT:x„ If the method converges


As the F and DF functions are formal operands, it is possible to use any name of permissible function. Here, for example, is the calculation of a solution of equation x2-1=0, using the function Pol, described above:


20 0.001 (1 0 1Pol) Newton (2 0Pol) 2



If we use an APL-operator for calculating Jacobian:

[0] J„(‘ Jacobian F)x

[1] J„‡‘J.=J„x

[2] J„(†(F(›x)+J)-›F x)‘

, then we can solve nonlinear algebraic system of arbitrary dimension. For example:


50 .01 F42 Newton (.000001 Jacobian F42) 0.1 0 0 0

2.136559765 10.14085331 2.048642888 0.05293643388


Here F42 is an APL function which describes one nonlinear algebraic system with four variables (see [3], p.112).

The above mentioned operations (equation solution or interpolation) are certainly presented in standard software. But in our case they are completely open for modifications and are rather flexible, for example, they can be used as operands for other operations.

22) Here is an example of description and research of a mathematical model of an stochastic process, known as birth and death process:


[0] r„Nn BirthDeath lambda;i;n;N

[1] Birth-Death process with Poisson distribution

[2] N n„Nn

[3] r„,n

[4] :For i :In N

[5] r„r,n„+/n Poisson lambda 20

[6] :EndFor


The function which generates n random numbers distributed by Poisson law with parameter lambda is described as:


[0] r„n Poisson par;P;k;w;q;lambda

[1] Generates n random numbers distributed approximately by Poisson with parameter lambda

[2] q is the maximal value of random value

[3] lambda q„par

[4] P„+\(*-lambda)(lambda*k)!k„0,q

[5] w„0.000001?n/1000000 n equidistributed random values

[6] r„1+q-(+/w.<P)


Our APL-model is not only concise, but (and it is more important) it is very convenient for experiments. Its result, which is a vector of N numbers, may be investigated in interactive mode:


Calculation of a trajectory of birth and death process and of its average:

0.1+/Œ„10 100 BirthDeath 1.01

100 112 114 115 114 105 100 107 120 145 142



Calculation of other trajectory and increments of this trajectory:

1‡T-1Œ„T„10 100 BirthDeath 1.01

100 99 85 89 93 93 93 69 76 72 79

1 14 4 4 0 0 24 7 4 7


Though APL is especially attractive for applied mathematicians and modellers, it is universal language permitting to create modern graphics applications, network or databases.

Conclusion Is the text of real APL-program, which print the following:

'We should not overestimate the value of classical programming languages for courses of computer science. APL is good alternative.'


[1] Naughton, Patrick The JAVA Handbook, Osborn, McGraw-Hill,1996

[2]Perminov, O.N. Programming in Pascal, Moscow, 1988 (in Russian)

[3]Monastyrnyi,P.I.(ed.) Collection of Exercises in Calculation Methods, Moscow, 1994 (in Russian)