Declaration of variables

In order to use a variable in C++, we must first declare it specifying which data type we want it to be. The syntax to declare a new variable is to write the specifier of the desired data type (like int, bool, float...) followed by a valid variable identifier. For example:

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int a;
float mynumber;

These are two valid declarations of variables. The first one declares a variable of type int with the identifier a. The second one declares a variable of type float with the identifier mynumber. Once declared, the variables a and mynumber can be used within the rest of their scope in the program.

If you are going to declare more than one variable of the same type, you can declare all of them in a single statement by separating their identifiers with commas. For example:

int a, b, c;

This declares three variables (a, b and c), all of them of type int, and has exactly the same meaning as:

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int a;
int b;
int c;

The integer data types char, short, long and int can be either signed or unsigned depending on the range of numbers needed to be represented. Signed types can represent both positive and negative values, whereas unsigned types can only represent positive values (and zero). This can be specified by using either the specifier signed or the specifier unsigned before the type name. For example:

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unsigned short int NumberOfSisters;
signed int MyAccountBalance;

By default, if we do not specify either signed or unsigned most compiler settings will assume the type to be signed, therefore instead of the second declaration above we could have written:

int MyAccountBalance;

with exactly the same meaning (with or without the keyword signed)

An exception to this general rule is the char type, which exists by itself and is considered a different fundamental data type from signed char and unsigned char, thought to store characters. You should use either signed or unsigned if you intend to store numerical values in a char-sized variable.

short and long can be used alone as type specifiers. In this case, they refer to their respective integer fundamental types: short is equivalent to short int and long is equivalent to long int. The following two variable declarations are equivalent:

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short Year;
short int Year;

Finally, signed and unsigned may also be used as standalone type specifiers, meaning the same as signed int and unsigned int respectively. The following two declarations are equivalent:

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unsigned NextYear;
unsigned int NextYear;

To see what variable declarations look like in action within a program, we are going to see the C++ code of the example about your mental memory proposed at the beginning of this section:

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// operating with variables

#include
using namespace std;

int main ()
{
// declaring variables:
int a, b;
int result;

// process:
a = 5;
b = 2;
a = a + 1;
result = a - b;

// print out the result:
cout << result;

// terminate the program:
return 0;
}
4

Do not worry if something else than the variable declarations themselves looks a bit strange to you. You will see the rest in detail in coming sections.

Fundamental data types

When programming, we store the variables in our computer's memory, but the computer has to know what kind of data we want to store in them, since it is not going to occupy the same amount of memory to store a simple number than to store a single letter or a large number, and they are not going to be interpreted the same way.

The memory in our computers is organized in bytes. A byte is the minimum amount of memory that we can manage in C++. A byte can store a relatively small amount of data: one single character or a small integer (generally an integer between 0 and 255). In addition, the computer can manipulate more complex data types that come from grouping several bytes, such as long numbers or non-integer numbers.

Next you have a summary of the basic fundamental data types in C++, as well as the range of values that can be represented with each one:

Name Description Size* Range*
char Character or small integer. 1byte signed: -128 to 127
unsigned: 0 to 255
short int
(short) Short Integer. 2bytes signed: -32768 to 32767
unsigned: 0 to 65535
int Integer. 4bytes signed: -2147483648 to 2147483647
unsigned: 0 to 4294967295
long int
(long) Long integer. 4bytes signed: -2147483648 to 2147483647
unsigned: 0 to 4294967295
bool Boolean value. It can take one of two values: true or false. 1byte true or false
float Floating point number. 4bytes +/- 3.4e +/- 38 (~7 digits)
double Double precision floating point number. 8bytes +/- 1.7e +/- 308 (~15 digits)
long double Long double precision floating point number. 8bytes +/- 1.7e +/- 308 (~15 digits)
wchar_t Wide character. 2 or 4 bytes 1 wide character

* The values of the columns Size and Range depend on the system the program is compiled for. The values shown above are those found on most 32-bit systems. But for other systems, the general specification is that int has the natural size suggested by the system architecture (one "word") and the four integer types char, short, int and long must each one be at least as large as the one preceding it, with char being always one byte in size. The same applies to the floating point types float, double and long double, where each one must provide at least as much precision as the preceding one.

Identifiers

Identifiers

A valid identifier is a sequence of one or more letters, digits or underscore characters (_). Neither spaces nor punctuation marks or symbols can be part of an identifier. Only letters, digits and single underscore characters are valid. In addition, variable identifiers always have to begin with a letter. They can also begin with an underline character (_ ), but in some cases these may be reserved for compiler specific keywords or external identifiers, as well as identifiers containing two successive underscore characters anywhere. In no case they can begin with a digit.

Another rule that you have to consider when inventing your own identifiers is that they cannot match any keyword of the C++ language nor your compiler's specific ones, which are reserved keywords. The standard reserved keywords are:

asm, auto, bool, break, case, catch, char, class, const, const_cast, continue, default, delete, do, double, dynamic_cast, else, enum, explicit, export, extern, false, float, for, friend, goto, if, inline, int, long, mutable, namespace, new, operator, private, protected, public, register, reinterpret_cast, return, short, signed, sizeof, static, static_cast, struct, switch, template, this, throw, true, try, typedef, typeid, typename, union, unsigned, using, virtual, void, volatile, wchar_t, while

Additionally, alternative representations for some operators cannot be used as identifiers since they are reserved words under some circumstances:

and, and_eq, bitand, bitor, compl, not, not_eq, or, or_eq, xor, xor_eq

Your compiler may also include some additional specific reserved keywords.

Very important: The C++ language is a "case sensitive" language. That means that an identifier written in capital letters is not equivalent to another one with the same name but written in small letters. Thus, for example, the RESULT variable is not the same as the result variable or the Result variable. These are three different variable identifiers.

How to Set Comment

Comments are parts of the source code disregarded by the compiler. They simply do nothing. Their purpose is only to allow the programmer to insert notes or descriptions embedded within the source code. 

C++ supports two ways to insert comments: 

1 2	// line comment /* block comment */

The first of them, known as line comment, discards everything from where the pair of slash signs (//) is found up to the end of that same line. The second one, known as block comment, discards everything between the /* characters and the first appearance of the */ characters, with the possibility of including more than one line.
We are going to add comments to our second program: 

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/* my second program in C++ with more comments */ #include using namespace std; int main () { cout << "Hello World! "; // prints Hello World! cout << "I'm a C++ program"; // prints I'm a C++ program return 0; }

Hello World! I'm a C++ program

If you include comments within the source code of your programs without using the comment characters combinations //, /* or */, the compiler will take them as if they were C++ expressions, most likely causing one or several error messages when you compile it.

Variables

Variables. Data Types.
Published by Juan Soulie
Last update on Sep 30, 2009 at 7:31am UTC
The usefulness of the "Hello World" programs shown in the previous section is quite questionable. We had to write several lines of code, compile them, and then execute the resulting program just to obtain a simple sentence written on the screen as result. It certainly would have been much faster to type the output sentence by ourselves. However, programming is not limited only to printing simple texts on the screen. In order to go a little further on and to become able to write programs that perform useful tasks that really save us work we need to introduce the concept of variable.

Let us think that I ask you to retain the number 5 in your mental memory, and then I ask you to memorize also the number 2 at the same time. You have just stored two different values in your memory. Now, if I ask you to add 1 to the first number I said, you should be retaining the numbers 6 (that is 5+1) and 2 in your memory. Values that we could now for example subtract and obtain 4 as result.

The whole process that you have just done with your mental memory is a simile of what a computer can do with two variables. The same process can be expressed in C++ with the following instruction set:

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a = 5;
b = 2;
a = a + 1;
result = a - b;


Obviously, this is a very simple example since we have only used two small integer values, but consider that your computer can store millions of numbers like these at the same time and conduct sophisticated mathematical operations with them.

Therefore, we can define a variable as a portion of memory to store a determined value.

Each variable needs an identifier that distinguishes it from the others. For example, in the previous code the variable identifiers were a, b and result, but we could have called the variables any names we wanted to invent, as long as they were valid identifiers.

Computer Science

History

Wikiversity has learning materials about computing
Main article: History of computer science
The early foundations of what would become computer science predate the invention of the modern digital computer. Machines for calculating fixed numerical tasks, such as the abacus, have existed since antiquity. Wilhelm Schickard built the first mechanical calculator in 1623.[6] Charles Babbage designed a difference engine in Victorian times[7] helped by Ada Lovelace.[8] Around 1900, punch-card machines[9] were introduced. However, all of these machines were constrained to perform a single task, or at best some subset of all possible tasks.
During the 1940s, as newer and more powerful computing machines were developed, the term computer came to refer to the machines rather than their human predecessors.[10] As it became clear that computers could be used for more than just mathematical calculations, the field of computer science broadened to study computation in general. Computer science began to be established as a distinct academic discipline in the 1950s and early 1960s.[11][12] The first computer science degree program in the United States was formed at Purdue University in 1962.[13] Since practical computers became available, many applications of computing have become distinct areas of study in their own right.
Although many initially believed it was impossible that computers themselves could actually be a scientific field of study, in the late fifties it gradually became accepted among the greater academic population.[14] It is the now well-known IBM brand that formed part of the computer science revolution during this time. IBM (short for International Business Machines) released the IBM 704 and later the IBM 709 computers, which were widely used during the exploration period of such devices. "Still, working with the IBM [computer] was frustrating...if you had misplaced as much as one letter in one instruction, the program would crash, and you would have to start the whole process over again".[14] During the late 1950s, the computer science discipline was very much in its developmental stages, and such issues were commonplace.
Time has seen significant improvements in the usability and effectiveness of computer science technology. Modern society has seen a significant shift from computers being used solely by experts or professionals to a more widespread user base.
[edit]Major achievements

This section requires expansion.


The German military used the Enigma machine during World War II for communication they thought to be secret. The large-scale decryption of Enigma traffic at Bletchley Park was an important factor that contributed to Allied victory in WWII.[15]
Despite its short history as a formal academic discipline, computer science has made a number of fundamental contributions to science and society. These include:
The start of the "digital revolution," which includes the current Information Age and the Internet.[16]
A formal definition of computation and computability, and proof that there are computationally unsolvable and intractable problems.[17]
The concept of a programming language, a tool for the precise expression of methodological information at various levels of abstraction.[18]
In cryptography, breaking the Enigma machine was an important factor contributing to the Allied victory in World War II.[15]
Scientific computing enabled advanced study of the mind, and mapping of the human genome became possible with the Human Genome Project.[16] Distributed computing projects such as Folding@home explore protein folding.
Algorithmic trading has increased the efficiency and liquidity of financial markets by using artificial intelligence, machine learning, and other statistical and numerical techniques on a large scale.[19]
[edit]Areas of computer science

As a discipline, computer science spans a range of topics from theoretical studies of algorithms and the limits of computation to the practical issues of implementing computing systems in hardware and software.[20][21] The Computer Sciences Accreditation Board (CSAB) [22] – which is made up of representatives of the Association for Computing Machinery (ACM), the Institute of Electrical and Electronics Engineers Computer Society (IEEE), and the Association for Information Systems (AIS) – identifies four areas that it considers crucial to the discipline of computer science: theory of computation, algorithms and data structures, programming methodology and languages, and computer elements and architecture. In addition to these four areas, CSAB also identifies fields such as software engineering, artificial intelligence, computer networking and communication, database systems, parallel computation, distributed computation, computer-human interaction, computer graphics, operating systems, and numerical and symbolic computation as being important areas of computer science.[20]
[edit]Theoretical computer science
The broader field of theoretical computer science encompasses both the classical theory of computation and a wide range of other topics that focus on the more abstract, logical, and mathematical aspects of computing.

Mathematical logic Automata theory Number theory Graph theory

Type theory Category theory Computational geometry Quantum computing theory
[edit]Theory of computation
According to Peter J. Denning, the fundamental question underlying computer science is, "What can be (efficiently) automated?"[11] The study of the theory of computation is focused on answering fundamental questions about what can be computed and what amount of resources are required to perform those computations. In an effort to answer the first question, computability theory examines which computational problems are solvable on various theoretical models of computation. The second question is addressed by computational complexity theory, which studies the time and space costs associated with different approaches to solving a computational problem.
The famous "P=NP?" problem, one of the Millennium Prize Problems,[23] is an open problem in the theory of computation.
P = NP ? GNITIRW-TERCES
Computability theory Computational complexity theory Cryptography
[edit]Algorithms and data structures
O(n2)
Analysis of algorithms Algorithms Data structures
[edit]Computer elements and architecture

Digital logic Microarchitecture Multiprocessing
[edit]Computational science
Computational science (or scientific computing) is the field of study concerned with constructing mathematical models and quantitative analysis techniques and using computers to analyse and solve scientific problems. In practical use, it is typically the application of computer simulation and other forms of computation to problems in various scientific disciplines.

Numerical analysis Computational physics Computational chemistry Bioinformatics
[edit]Artificial Intelligence
This branch of computer science aims to create synthetic systems which solve computational problems, reason and/or communicate like animals and humans do. This theoretical and applied subfield requires a very rigorous and integrated expertise in multiple subject areas such as applied mathematics, logic, semiotics, electrical engineering, philosophy of mind neurophysiology, and social intelligence which can be used to advance the field of intelligence research or be applied to other subject areas which require computational understanding and modelling such as in finance or the physical sciences. It all started with the grandfather of computer science and artificial intelligence, Alan Turing, who proposed the Turing Test for the purpose of answering the ultimate question... "Can computers think ?".

Machine Learning Computer vision Image Processing Pattern Recognition

Cognitive Science Data Mining Evolutionary Computation Information Retrieval

Knowledge Representation Natural Language Processing Robotics Human–computer interaction
[edit]Software Engineering
The IEEE Computer Society's Software Engineering Body of Knowledge defines "software engineering" as the application of a systematic, disciplined, quantifiable approach to the development, operation, and maintenance of software, and the study of these approaches; that is, the application of engineering to software.[24] In 2004, a newly established degree of software engineering established by both ACM and IEEE was formed to address these issues; a document called CCSE was written to explain the details. In addition those with degrees in information technology or management information systems are often found to be necessary supportive roles for both software engineering and computational work.

Operating systems Computer networks Databases Computer security

Ubiquitous computing Systems architecture Compiler design Programming languages
[edit]Relationship with other fields

Despite its name, a significant amount of computer science does not involve the study of computers themselves. Because of this, several alternative names have been proposed. Certain departments of major universities prefer the term computing science, to emphasize precisely that difference. Danish scientist Peter Naur suggested the term datalogy, to reflect the fact that the scientific discipline revolves around data and data treatment, while not necessarily involving computers. The first scientific institution to use the term was the Department of Datalogy at the University of Copenhagen, founded in 1969, with Peter Naur being the first professor in datalogy. The term is used mainly in the Scandinavian countries. Also, in the early days of computing, a number of terms for the practitioners of the field of computing were suggested in the Communications of the ACM – turingineer, turologist, flow-charts-man, applied meta-mathematician, and applied epistemologist.[25] Three months later in the same journal, comptologist was suggested, followed next year by hypologist.[26] The term computics has also been suggested.[27] In continental Europe, names such as informatique (French), Informatik (German) or informatica (Dutch), derived from information and possibly mathematics or automatic, are more common than names derived from computer/computation.
The renowned computer scientist Edsger Dijkstra stated, "Computer science is no more about computers than astronomy is about telescopes." The design and deployment of computers and computer systems is generally considered the province of disciplines other than computer science. For example, the study of computer hardware is usually considered part of computer engineering, while the study of commercial computer systems and their deployment is often called information technology or information systems. However, there has been much cross-fertilization of ideas between the various computer-related disciplines. Computer science research has also often crossed into other disciplines, such as philosophy, cognitive science, linguistics, mathematics, physics, statistics, and economics.
Computer science is considered by some to have a much closer relationship with mathematics than many scientific disciplines, with some observers saying that computing is a mathematical science.[11] Early computer science was strongly influenced by the work of mathematicians such as Kurt Gödel and Alan Turing, and there continues to be a useful interchange of ideas between the two fields in areas such as mathematical logic, category theory, domain theory, and algebra.
The relationship between computer science and software engineering is a contentious issue, which is further muddied by disputes over what the term "software engineering" means, and how computer science is defined. David Parnas, taking a cue from the relationship between other engineering and science disciplines, has claimed that the principal focus of computer science is studying the properties of computation in general, while the principal focus of software engineering is the design of specific computations to achieve practical goals, making the two separate but complementary disciplines.[28]
The academic, political, and funding aspects of computer science tend to depend on whether a department formed with a mathematical emphasis or with an engineering emphasis. Computer science departments with a mathematics emphasis and with a numerical orientation consider alignment computational science. Both types of departments tend to make efforts to bridge the field educationally if not across all research.

Computer science education

Some universities teach computer science as a theoretical study of computation and algorithmic reasoning. These programs often feature the theory of computation, analysis of algorithms, formal methods, concurrency theory, databases, computer graphics and systems analysis, among others. They typically also teach computer programming, but treat it as a vessel for the support of other fields of computer science rather than a central focus of high-level study.
Other colleges and universities, as well as secondary schools and vocational programs that teach computer science, emphasize the practice of advanced programming rather than the theory of algorithms and computation in their computer science curricula. Such curricula tend to focus on those skills that are important to workers entering the software industry. The practical aspects of computer programming are often referred to as software engineering. However, there is a lot of disagreement over the meaning of the term, and whether or not it is the same thing as programming.


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