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D. Basic Programming Concepts

This appendix attempts to define some of the basic concepts and terms that are used throughout the rest of this Web page. As this Web page is specifically about awk, and not about computer programming in general, the coverage here is by necessity fairly cursory and simplistic. (If you need more background, there are many other introductory texts that you should refer to instead.)

D.1 What a Program Does  The high level view.
D.2 Data Values in a Computer  A very quick intro to data types.
D.3 Floating-Point Number Caveats  Stuff to know about floating-point numbers.

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D.1 What a Program Does

At the most basic level, the job of a program is to process some input data and produce results.

+------+         /       \         +---------+
| Data | -----> < Program > -----> | Results |
+------+         \_______/         +---------+

The "program" in the figure can be either a compiled program(66) (such as ls), or it may be interpreted. In the latter case, a machine-executable program such as awk reads your program, and then uses the instructions in your program to process the data.

When you write a program, it usually consists of the following, very basic set of steps:

+----------------+           / More \  No       +----------+
| Initialization | -------> <  Data  > -------> | Clean Up |
+----------------+    ^      \   ?  /           +----------+
                      |       +--+-+
                      |          | Yes
                      |          |
                      |          V
                      |     +---------+
                      +-----+ Process |

These are the things you do before actually starting to process data, such as checking arguments, initializing any data you need to work with, and so on. This step corresponds to awk's BEGIN rule (see section The BEGIN and END Special Patterns).

If you were baking a cake, this might consist of laying out all the mixing bowls and the baking pan, and making sure you have all the ingredients that you need.

This is where the actual work is done. Your program reads data, one logical chunk at a time, and processes it as appropriate.

In most programming languages, you have to manually manage the reading of data, checking to see if there is more each time you read a chunk. awk's pattern-action paradigm (see section Getting Started with awk) handles the mechanics of this for you.

In baking a cake, the processing corresponds to the actual labor: breaking eggs, mixing the flour, water, and other ingredients, and then putting the cake into the oven.

Clean Up
Once you've processed all the data, you may have things you need to do before exiting. This step corresponds to awk's END rule (see section The BEGIN and END Special Patterns).

After the cake comes out of the oven, you still have to wrap it in plastic wrap to keep anyone from tasting it, as well as wash the mixing bowls and other utensils.

An algorithm is a detailed set of instructions necessary to accomplish a task, or process data. It is much the same as a recipe for baking a cake. Programs implement algorithms. Often, it is up to you to design the algorithm and implement it, simultaneously.

The "logical chunks" we talked about previously are called records, similar to the records a company keeps on employees, a school keeps for students, or a doctor keeps for patients. Each record has many component parts, such as first and last names, date of birth, address, and so on. The component parts are referred to as the fields of the record.

The act of reading data is termed input, and that of generating results, not too surprisingly, is termed output. They are often referred to together as "Input/Output," and even more often, as "I/O" for short. (You will also see "input" and "output" used as verbs.)

awk manages the reading of data for you, as well as the breaking it up into records and fields. Your program's job is to tell awk what to with the data. You do this by describing patterns in the data to look for, and actions to execute when those patterns are seen. This data-driven nature of awk programs usually makes them both easier to write and easier to read.

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D.2 Data Values in a Computer

In a program, you keep track of information and values in things called variables. A variable is just a name for a given value, such as first_name, last_name, address, and so on. awk has several pre-defined variables, and it has special names to refer to the current input record and the fields of the record. You may also group multiple associated values under one name, as an array.

Data, particularly in awk, consists of either numeric values, such as 42 or 3.1415927, or string values. String values are essentially anything that's not a number, such as a name. Strings are sometimes referred to as character data, since they store the individual characters that comprise them. Individual variables, as well as numeric and string variables, are referred to as scalar values. Groups of values, such as arrays, are not scalars.

Within computers, there are two kinds of numeric values: integers, and floating-point. In school, integer values were referred to as "whole" numbers--that is, numbers without any fractional part, such as 1, 42, or -17. The advantage to integer numbers is that they represent values exactly. The disadvantage is that their range is limited. On most modern systems, this range is -2,147,483,648 to 2,147,483,647.

Integer values come in two flavors: signed and unsigned. Signed values may be negative or positive, with the range of values just described. Unsigned values are always positive. On most modern systems, the range is from 0 to 4,294,967,295.

Floating-point numbers represent what are called "real" numbers; i.e., those that do have a fractional part, such as 3.1415927. The advantage to floating-point numbers is that they can represent a much larger range of values. The disadvantage is that there are numbers that they cannot represent exactly. awk uses double-precision floating-point numbers, which can hold more digits than single-precision floating-point numbers. Floating-point issues are discussed more fully in Floating-Point Number Caveats.

At the very lowest level, computers store values as groups of binary digits, or bits. Modern computers group bits into groups of eight, called bytes. Advanced applications sometimes have to manipulate bits directly, and gawk provides functions for doing so.

While you are probably used to the idea of a number without a value (i.e., zero), it takes a bit more getting used to the idea of zero-length character data. Nevertheless, such a thing exists. It is called the null string. The null string is character data that has no value. In other words, it is empty. It is written in awk programs like this: "".

Humans are used to working in decimal; i.e., base 10. In base 10, numbers go from 0 to 9, and then "roll over" into the next column. (Remember grade school? 42 is 4 times 10 plus 2.)

There are other number bases though. Computers commonly use base 2 or binary, base 8 or octal, and base 16 or hexadecimal. In binary, each column represents two times the value in the column to its right. Each column may contain either a 0 or a 1. Thus, binary 1010 represents 1 times 8, plus 0 times 4, plus 1 times 2, plus 0 times 1, or decimal 10. Octal and hexadecimal are discussed more in Octal and Hexadecimal Numbers.

Programs are written in programming languages. Hundreds, if not thousands, of programming languages exist. One of the most popular is the C programming language. The C language had a very strong influence on the design of the awk language.

There have been several versions of C. The first is often referred to as "K&R" C, after the initials of Brian Kernighan and Dennis Ritchie, the authors of the first book on C. (Dennis Ritchie created the language, and Brian Kernighan was one of the creators of awk.)

In the mid-1980's, an effort began to produce an international standard for C. This work culminated in 1989, with the production of the ANSI standard for C. This standard became an ISO standard in 1990. Where it makes sense, POSIX awk is compatible with 1990 ISO C.

In 1999, a revised ISO C standard was approved and released. Future versions of gawk will be as compatible as possible with this standard.

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D.3 Floating-Point Number Caveats

As mentioned earlier, floating-point numbers represent what are called "real" numbers; i.e., those that have a fractional part. awk uses double-precision floating-point numbers to represent all numeric values. This section describes some of the issues involved in using floating-point numbers.

There is a very nice paper on floating-point arithmetic by David Goldberg, What Every Computer Scientist Should Know About Floating-point Arithmetic, ACM Computing Surveys 23, 1 (1991-03), 5-48.(67) This is worth reading if you are interested in the details, but it does require a background in Computer Science.

Internally, awk keeps both the numeric value (double-precision floating-point) and the string value for a variable. Separately, awk keeps track of what type the variable has (see section Variable Typing and Comparison Expressions), which plays a role in how variables are used in comparisons.

It is important to note that the string value for a number may not reflect the full value (all the digits) that the numeric value actually contains. The following program (`values.awk') illustrates this:

   $1 = $2 + $3
   # see it for what it is
   printf("$1 = %.12g\n", $1)
   # use CONVFMT
   a = "<" $1 ">"
   print "a =", a
   # use OFMT
   print "$1 =", $1

This program shows the full value of the sum of $2 and $3 using printf, and then prints the string values obtained from both automatic conversion (via CONVFMT) and from printing (via OFMT).

Here is what happens when the program is run:

$ echo 2 3.654321 1.2345678 | awk -f values.awk
-| $1 = 4.8888888
-| a = <4.88889>
-| $1 = 4.88889

This makes it clear that the full numeric value is different from what the default string representations show.

CONVFMT's default value is "%.6g", which yields a value with at least six significant digits. For some applications, you might want to change it to specify more precision. On most modern machines, most of the time, 17 digits is enough to capture a floating-point number's value exactly.(68)

Unlike numbers in the abstract sense (such as what you studied in high school or college math), numbers stored in computers are limited in certain ways. They cannot represent an infinite number of digits, nor can they always represent things exactly. In particular, floating-point numbers cannot always represent values exactly. Here is an example:

$ awk '{ printf("%010d\n", $1 * 100) }'
-| 0000051579
-| 0000051579
-| 0000051580
-| 0000051582

This shows that some values can be represented exactly, whereas others are only approximated. This is not a "bug" in awk, but simply an artifact of how computers represent numbers.

Another peculiarity of floating-point numbers on modern systems is that they often have more than one representation for the number zero! In particular, it is possible to represent "minus zero" as well as regular, or "positive" zero.

This example shows that negative and positive zero are distinct values when stored internally, but that they are in fact equal to each other, as well as to "regular" zero:

$ gawk 'BEGIN { mz = -0 ; pz = 0 
> printf "-0 = %g, +0 = %g, (-0 == +0) -> %d\n", mz, pz, mz == pz
> printf "mz == 0 -> %d, pz == 0 -> %d\n", mz == 0, pz == 0
> }'
-| -0 = -0, +0 = 0, (-0 == +0) -> 1
-| mz == 0 -> 1, pz == 0 -> 1

It helps to keep this in mind should you process numeric data that contains negative zero values; the fact that the zero is negative is noted and can affect comparisons.

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