Programming

• Translation

Development of software as if in the worst side differs from other disciplines of computer science.

Several years ago I studied algorithms and complexity. A delightfully clean area where each concept is well defined, each result built on previous evidence. When you know a fact in this area, you can rely on it, because mathematics itself deduced it. Even imperfect results like approximation and probabilistic algorithms have a rigorous analysis of their imperfection. Other disciplines of computer science, such as network topology and cryptography, have similarly satisfactory status.

And now I work in software development, and this is an unbearably slippery topic. No concept is precisely defined. Results are graded with characteristics of "usually" or "in general". Today's research may or may not help tomorrow's work. New approaches often refute previous methods, and they themselves burn brightly for a short time, and then go out of fashion when their limitations surface. We believed in structured programming. Then they began to believe in fourth-generation languages, then in object-oriented methods, then in extreme programming and now maybe open source.

But programming is where the tire-to-asphalt contact occurs. Few people care whether it really equals, purely for the sake of the beauty of the question. Computer area deals with computers. It is writing programs to solve real human problems and running those programs on real machines. According to the Church-Turing thesis, everything computer equipment is essentially equivalent. So while computer architecture is cool, the real limitation in computer science is software development. We need programs that can be assembled in a reasonable amount of time and at a reasonable cost, that work approximately the way the designers intended, and work without errors.

With this goal in mind, I have always been preoccupied with one question (like many other researchers): Why can't programmers get more rigorous results, as in other areas of computer science? To put it differently, "What part of software architecture and design can be made formal and demonstrable?" The answer to this question is in Figure 1.

Figure 1: The Bright Line in Computer Science

Topics above this line belong to software development. The areas of study below this line are basic computer science subjects. The latter have clear, formal results. For open problems in this area, we expect new results to be obtained, which will be formally formulated. These topics are based on each other: cryptography on complexity, and compilers on algorithms, for example. Moreover, we believe that proven results in these areas will remain so 100 years from now.

So what is this bright line, and why isn't there any programming topic below it? Line is a quality called direct human participation. Software development has this quality, but traditional computer science does not. Results from disciplines below the line can be used by humans, but these results are not directly affected. influence people.

Software development has an inherent human component. For example, the operational reliability of software is the ability to understand, find and fix defects by humans. software system... The operational reliability can be influenced by some formal concepts of computer science - perhaps the cyclomatic complexity of the software control graph. But operational reliability is critically dependent on people and their ability to comprehend meaning and purpose. source code... The question of whether a particular software system has high operational reliability cannot be answered simply by mechanically examining the software.

It's the same with security. The researchers used some formal methods to find out the impact of the software system on people's health and property. But no discussion about software security can be considered complete without addressing the human component of the system under study. Likewise for requirements development. We can design any survey techniques to get specific stakeholder requirements, and we can create various systems to record them. But no amount of research in this area will change the fact that demand gathering often involves talking or observing people. Sometimes these people tell us correct information and sometimes not. Sometimes people lie, perhaps for good reasons. Sometimes people honestly try to convey the correct information, but they cannot.

This observation leads to Connell's Thesis:

Software development will never be a rigorous discipline with proven results, since it involves human activities.

This is an extra-mathematical statement about the boundaries of formal systems. I have no evidence for or against. But the fact is, human issues remain central to software development:

• What should this program do? (requirements, usability, security)
• What should the program look like inside so that it is easy to fix and modify? (architecture, design, scalability, portability, extensibility)
• How long will it take to write it? (grade)
• How should we design it? (coding, testing, measuring, configuring)
• How should the team work effectively? (management, process, documentation)

All of these problems revolve around people.

My thesis explains why software development is so difficult and so slippery. The proven methods of one team of programmers do not work for other teams. An exhaustive analysis of past projects may not be helpful for a good assessment of the next one. Each of the revolutionary development tools helps a little bit and then falls short of its great promises. The reason is that people are too soft, frustrating, and unpredictable.

Before moving on to the implications of my statement, consider three likely objections:

The thesis realizes itself. If some area of ​​software development is suddenly decided strictly, then you can simply change the definition software development to eliminate this problem from it.

In some ways this objection is correct, but not in all. I argue that the set of disciplines commonly referred to as software engineering will continue to defy rigorous decision in essence. Narrow aspects of some problems may lend themselves to a formal approach, but their success will only be on the periphery of key development problems.

Statistical results in programming already disprove this thesis.

These methods generally solve the scoring problem and include Function Point Counting, COCOMO II, PROBE, and others. Despite their mathematical form, these methods are not proofs or formal results. Such statistics are simply an attempt to quantify the subjective human experience from past software projects and extrapolate it to future projects. Sometimes it works. But the seemingly strict formulas in these schemes are pig with lipstick, to use the modern expression. For example, one of the formulas in COCOMO II looks like this:, where, and is a set of five scaling factors such as "development flexibility" and "team cohesion". The formula itself looks strict, but it is dominated by an indicator made up of human factors.

Formal development processes such as the clean room method gradually find rigorous, demonstrable methods. They bring up a bright line to bring previously blurred themes underneath.

Indeed, researchers of formal processes are showing progress in solving different problems... But they can be caught in violation of the very first objection on this list: they define software development too narrowly to lend themselves to a rigorous decision. Formal methods are just comfortable interpreting any problem that is based on human participation and interpretation. For instance, key element formal design methods is the creation of rigorous, unambiguous specifications. These specifications are then used to guide (and prove) subsequent development steps. Of course, a formal method can contain an unambiguous semantic notation scheme. But no formal method contains an exact recipe for how to unambiguously translate people's vague thoughts about what the program should do.

Contrary to these objections, I declare that software development is fundamentally different from traditional software development, formal informatics... The first depends on people, and the second does not. This brings us to Connell's Conclusion:

We should stop trying to prove fundamental results in software development and recognize that significant advances in this area will only be general recommendations.

For example, David Parnas in 1972 wrote a wonderful scientific article "On the criteria for decomposing a system into modules." She describes a simple experiment that Parnas conducted with alternative software design strategies, one with information hiding and the other with global data visibility. Then, based on this little experiment, he drew several conclusions and made recommendations. Nothing in the article is proven, and Parnas does not guarantee that following the recommendations everyone will get the same result. But the article contains wise advice and has greatly influenced the popularity of object-oriented programming languages.

Another example is the massive work of the Software Engineering Institute at Carnegie Mellon University known as CMMI. CMMI started out as a software development process model and has now expanded to include other types of projects as well. CMMI is approximately 1,000 pages long - not counting examples, interpretations, and training materials - and represents over 1,000 man-years of work. Many large organizations have used it and have made significant progress in their software development processes and products. But in CMMI there is not a single firmly proven result. It is simply a collection of (well-researched) suggestions for how to organize a software project based on methods that have been effective for other organizations in the past. In fact, the Software Engineering Institute states that CMMI is not even a process, but rather a meta-process, the details of which are filled in by each organization.

Other areas of research in this vein are design patterns, architecture styles, questionable refactoring, agile development, and data visualization. These disciplines may contain proven results in part, but are generally aimed at systems that inherently involve human participation. To be clear, the core computer science topics (below the bright line) are vital tools for any developer. Knowledge of algorithms is essential when designing high-performance applications. Queuing theory helps design the operating system kernel. The clean room methodology is also useful in some situations. Analyzing statistics can come in handy when planning similar projects with a similar group of participants. But formalism is simply a necessary, not a sufficient condition for good design. Let's take construction and architecture (i.e. houses and buildings) as an example.

Imagine a brilliant civil engineer, the world's best expert on building materials, stress versus strain, load distribution, shear wind and earthquake protection, and more. This guy is listed in notebooks architects in all countries to call him for advice on each construction project. Will this mythical civil engineer be as good at designing the buildings he is analyzing? Not at all. He can get lost in conversations with clients, is unable to design pleasant places to live, his imagination is not enough to come up with solutions to new problems, and he is boring as hell. Building techniques are useful for real architects, but not enough for good project... Successful architecture requires creativity, concept, interdisciplinary thinking, and humanism.

In the same way, classical computer science is useful in software development, but it will never be enough. Designing good software also requires creativity, concept, interdisciplinary thinking, and humanism. This observation frees researchers of the software development process. They can spend time learning about successful methods - accumulating a body of collective knowledge for future practitioners. We shouldn't squeeze software development into the mathematical expansion of computer science. This will not work and may distract us from useful discoveries that are still waiting for their time.

Acknowledgments
Thanks to Steve Homer for the discussion that sparked my interest in this issue.

The manual contains a presentation of the basic concepts in the field of computer science and the basics of programming, as well as practical examples.
The manual is intended for students of the following specialties: - "Management", "Management of organizations", "Human Resources", "Commerce", "Marketing", " World economy"," Anti-crisis management "," Accounting, analysis and audit "," Finance and credit "," Linguistics "," Taxes and taxation "," Psychology ".

Informatics in a broad sense is understood as a set of various branches of science, technology and production related to the processing of information. In a narrow sense, computer science can be represented as a set of the following interrelated parts:
1) technical means (hardware);
2) software;
3) algorithmic tools (brainware).
It is characteristic that informatics in both broad and narrow sense can be viewed from different positions:
- as a branch of the national economy;
- as a fundamental science;
- as an applied discipline.
The term "information" comes from latin word"Informatio", which means clarification, information, presentation. Informatics considers information as conceptually related information, data, concepts that change our ideas about a phenomenon or object of the surrounding world. Along with information in computer science, the concept of data is often used. Data can be viewed as signs or recorded observations that in this moment not used but stored. When data is used, it turns into information.

Table of contents
Credits 5
1. Informatics 7
1.1. Information and informatization of society 8
1.2. Measurement and presentation of information 9
1.3. Technical means implementation information processes 10
1.4. Software implementation of information processes 14
1.5. Programming technologies 15
2. Algorithmization of data processing 21
2.1. Basic concepts and definitions 22
2.2. Algorithm Display Tools 23
2.3. Characterization and data classification 24
3. Basic language constructions Pascal programming 29
3.1. The main elements of the program Pascal 30
3.2. Language operators 32
3.3. Conditional operator and its use for branching 34
3.4. Managing Branches with the Case Statement 35
3.5. Organization of cyclic processes 37
3.6. Processing character information 41
3.7. Organization of program execution in DELPHI environment 43
4. Software processing structural types 49
4.1. Organization of information in the form of arrays 50
4.2. Organizing information in the form of records 52
4.3. Organizing Information as a Set 55
4.4. Processing features economic information organized as an array of 58 records
5. Modular programming 65
5.1 Organization of the modular structure of the program 66
5.2. Using procedures 68
5.3. Using functions 72
5.4. Procedures and functions without parameters 77
5.5. Organization external modules 80
Themes laboratory work 89
Glossary 90
Recommended reading list 94

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To write applications different levels complexity, you first need to gain knowledge of how to do it. And it is desirable to start with the very basics of algorithms and programming. Here we will talk about them within the framework of the article.

This is the name of a complex technical science, the task of which is to systematize the methods of creating, processing, transferring, storing and reproducing data using it.It also includes the principles of functioning and management methods that help to achieve the goal. The term "informatics" itself is of French origin and is a hybrid of the word "information" and "automation". It arose thanks to the development and dissemination of new technologies for collecting, processing and transmitting data, which were associated with their fixation on computer media. This is the origin of computer science. The basics of algorithmization and programming are one of the most important areas of this science.

What does she do?

Informatics has the following tasks:

1. Hardware and software support computing technology.
2. Means of ensuring the interaction of a person and computer components with each other.

The term "interface" is often used to refer to the technical part. Here we have a free program. The basics of algorithms and programming are always used when creating products mass distribution that "should" reach a wide audience. Indeed, for popularity, the developed application must work and look optimally.

Algorithm presentation

They can be written in a significant number of ways. The most popular are the following:

1. Verbal and formulaic description. This implies the placement of text and specific formulas that will explain the features of interaction in all individual cases.
2. Block diagram. Presence is implied graphic symbols, which make it possible to understand the peculiarities of the interaction of the program within itself and with other applications or the hardware component of the computer. Each of them can be responsible for a separate function, procedure or formula.
3. Creation is implied separate ways descriptions for specific cases, which show the features and sequence of tasks.
4. Operator schemes. This implies creation of a prototype - it will show the interaction based on the paths that individual operands will take.

Pseudocode. A sketch of the backbone of the program.

Algorithm record

How to start creating your own prototype of a program, function or procedure? To do this, it is enough to use such general recommendations:

1. Each algorithm should have its own name that explains its meaning.
2. Be sure to take care of the presence of a beginning and an end.
3. Input and output data should be described.
4. You should specify the commands with which certain actions will be performed on specific information.

Recording methods

Algorithm views can be as many as five. But there are only two ways to write:

1. Formal and verbal. It is characterized by the fact that the description is made mainly using formulas and words. The content, as well as the sequence of execution of the stages of the algorithm in this case, is written in a natural professional language in any form.
2. Graphic. Most common. It uses block symbols or algorithm schemes. The connection between them is shown using special lines.

We develop a software structure

There are three main types:

1. Linear. With this structure, all actions are performed sequentially in turn order and only once. The diagram looks like a sequence of blocks arranged from top to bottom, depending on the order in which they are executed. Received primary and intermediate data cannot influence the direction computing process.
2. Branching. Found wide application in practice, when solving difficult tasks... So, if it is necessary to take into account the initial conditions or intermediate results, then the necessary calculations are performed in accordance with them and the direction of the computational process can change depending on the result obtained.

Cyclical. To make it easier for yourself to work with many tasks, some areas program code it makes sense to repeat it many times. In order not to prescribe how many times and what needs to be done, use a cyclic structure. It provides for a sequence of commands that will be repeated until a given condition is met. The use of loops can significantly reduce the complexity of writing a program.

Programming

It is important on which programs will be created. It should be noted that many of them are "sharpened" for specific working conditions (for example, in a browser). In general, programming languages ​​are divided into two groups:

1. Functional.
2. Operator:

Not procedural;

Procedural.

Can you guess which of them are most often used? Operator-procedural is the answer. They can be machine oriented or independent. The former include assemblers, autocodes, symbolic encoding... Independents divide based on their orientation:

• procedural;
• problematic;
• object.

Each of them has its own scope. But for writing programs ( useful applications or games), object-oriented languages ​​are most commonly used. Of course, you can use others, but the fact is that they are the most developed for creating final consumer products for the masses. Yes, and if you don’t have a clear vision of where to start, I suggest you pay attention to the basics of algorithmization and object-oriented programming. Now it is a very popular destination where you can find a lot of teaching material... In general, the basics of algorithmicization and programming languages ​​are now needed due to the fact that there is a lack of qualified developers, and their importance will only grow in the future.

Conclusion

When working with algorithms (and subsequently with programs), one should strive to think through all the details, down to the smallest. In the subsequent identification of each unprocessed piece of code will only lead to additional work, increase in development costs and task completion times. Careful planning and elaboration of all the nuances will significantly save time, effort and money. Well, now they can say that after reading this article you have a concept about the basics of algorithms and programming. It remains only to apply this knowledge. If you want to study the topic in more detail, I can recommend the book "Fundamentals of Algorithmization and Programming" (Semakin, Shestakov) 2012.

MINISTRY OF EDUCATION OF THE RUSSIAN FEDERATION

MOSCOW STATE UNIVERSITY

ECONOMY, STATISTICS AND INFORMATICS

N. V. Komleva, A. A. Smirnov informatics and programming Tutorial

Moscow, 2006

Komleva N.V., Smirnov A.A. Informatics and programming: Textbook / Moscow State University of Economics, Statistics and Informatics.-M., 2006.-

The manual contains an exposition of the basic concepts in the field of informatics and the basics of programming, as well as practical examples.

The manual is intended for students of the following specialties:

- "Management", "Management of Organizations", "Personnel Management", "Commerce", "Marketing", "World Economy", "Anti-Crisis Management", "Accounting, Analysis and Audit", "Finance and Credit", "Linguistics "," Taxes and Taxation "," Psychology ".

1. Informatics.

1.2. Measurement and presentation of information.

1.3. Technical means for the implementation of information processes.

1.4. Software for the implementation of information processes.

1.5. Programming technologies.

2. Algorithmization of data processing processes.

2.1. Basic concepts and definitions.

2.2. Algorithm imaging tools.

2.3. Characterization and classification of data.

3. Basic constructions of the programming language Pascal.

3.1. The main elements of a Pascal program.

3.2. Language operators.

3.3. The conditional operator and its use for branching.

3.4. Branch control with the Case statement.

3.5. Organization of cyclical processes.

3.6. Counter loop operator.

3.7. Processing of symbolic information.

3.8. Organization of program execution in the DELPHI environment.

4. Programmatic processing of structural types.

4.1. Organization of information in the form of arrays.

4.2. Programmatic processing of information presented in the form of records.

4.3. Features of processing economic information, organized in the form of an array of records.

4.4.Presentation of economic information in the form of a set.

5. Modular programming.

5.1. Organization of the modular structure of the program.

5.2. Using procedures

5.3. Using functions

5.4. Procedures and functions without parameters.

5.5. Organization of external modules.

6. Literature and INTRNET-resources

7. Glossary

1. Informatics.

1.1. Information and informatization of society.

The term information comes from the Latin word "Informatio", which means clarification, informing, presentation. Informatics considers information as conceptually related information, data, concepts that change our ideas about a phenomenon or object of the surrounding world. Along with information in computer science, the concept of data is often used. Data can be thought of as indications or recorded observations that are not currently being used, but are stored. In the event that data begins to be used, then the data turns into information.

Information can be converted into knowledge. Information received from specialists only becomes knowledge if it is structured, presented in a special way, thoroughly tested and has the ability to develop. Knowledge, when using logical inference, allows you to generate new knowledge.

Economic information is a collection of information reflecting socio-economic processes, designed to control the processes and collectives of people in the production and non-production spheres.

Informatics, in a broad sense, is understood as a set of various branches of science, technology and production related to information processing. In a narrow sense, computer science can be represented as a set of the following interrelated parts:

First, hardware;

Secondly, software;

Third, algorithmic tools (brainware).

It is characteristic that informatics, both in a broad sense and in a narrow sense, can be viewed from different positions:

First, as a branch of the national economy;

Second, as a fundamental science;

Third, as an applied discipline.

The introduction of computers, modern means of processing and transmission of information in various fields of activity was the beginning of a new process called "informatization".

The informatization of society is understood as an organized socio-economic, scientific and technical process of creating optimal conditions for meeting the information needs of government bodies and citizens based on the use of information resources. Modern material production and other spheres of activity are increasingly in need of information services, processing of a huge amount of information. An informational society is called a society in which most of the workers are engaged in the production, storage and processing of information.

The textbook reveals the content of information processing methods based on computer technology, which allows you to get an idea of ​​the technological and software components of informatics. The book includes practical tasks and control exercises, the implementation of which will allow you to get acquainted with the basics of MS DOS, gain skills in using a shell program Norton Commander, as well as methods of working in graphic operating environments Windows family, master the techniques of drawing up programs and go to the independent preparation of programs. To do this, the manual studies specific texts program constructions and assignments for independent work are given.
For university and college students enrolled in the specialization "Information Technologies of Management", as well as for everyone who wants to independently master the basics of programming.

Informatics is an area of ​​scientific and practical knowledge that allows you to manage various objects and systems based on information processing. In this sense, it enriches Scientific research and practical activities in various subject areas starting from the management of small teams, expanding all known forms of human activity, having a significant impact on the successful implementation of space projects.
One of the important areas of informatics is the use of new methods of information processing and computer technology in the management of organizational and economic systems.
Training of specialists for management organizational structures involves not only learning how to actively use information technologies(IT), but also the study of methods and ways of applying them to optimize and develop the organization's management system.

Table of contents
Introduction
Foreword
Chapter 1. The main components of computer technology
1.1. Computer techologies and informational space 17
1.2. Computer: structure and parameters 18
1.2.1. Structural scheme computer 19
1.2.2. Additional devices information input-output 22
1.2.3. Computer classification 24
1.2.4. Data networks 26
1.3. Computer software 27
1.3.1. Software classification 27
1.3.2. File system information storage 29
1 4 Disk operating system MS DOS .31
1.4.1. Composition and Purpose of MS DOS .31
1.4.2. Memory allocation in MS DOS 32
1 4.3. File structure disc 33
1.4.4. MS DOS Utilities 34
1.4.5. Device Drivers in MS DOS 39
1.5. Executing MS DOS Commands. 40
1.6. Norton Commander Wrapper, Workshop; work in MS DOS environment. 50
Chapter 2. Graphic operating room WINDOWS system XP 51
2.1 Desktop of the operating system
2.1.1. Basic elements of the desktop 55
2.1.2. Desktop Decoration 66
2.1 3. Managing Objects on the Desktop 70
2.2. Control panel 71
2.3. Formatting a Disk 76
2.4. Customizing the taskbar 76
2.5. Customizing the Start Button Menu 77
2.6. Application File Explorer 80
2.7. Application Cart 84
2.8. Application Portfolio 85
2.9. Notepad application 87
2.10. Appendices Scheduled Tasks & Date & Time 87
2.11. Paint application 89
2.11.1. Basic elements of the graphic Paint editor 90
2.11.2. System menu graphic editor Paint 91
2.11.3. Graphics editor tools Paint 95
2 11.4. Inserting Graphics 99
Practicum: work in graphic operating system Windows 100 family
Chapter 3. Basics of programming in Turbo Pascal 7.0
3.1. Programming Process 115
3.2. Turbo Pascal 118 integrated tooling
3.2.1. Main Menu Options 118
3.2.2. Appointment function keys 125
3.2.3. Text editor 127
3.2.4. Operations 127
3.3. Turbo Pascal 7.0 128 programming language
3.3.1. Language vocabulary 128
3.3.2. Language grammar 132
3 4. Operators 133
3.4.1. Data Input and Output Operators 134
3.4.2. Simple Transition Operator Goto 136
3.4.3. Structured Operators 137
3.5. Data Types 145
3.5.1 Simple types data 145
3 5.2. Structured types data 148
3.6. Procedures and Functions - 166
3.7. Module in Turbo Pascal 173
3.7.1. Library standard module SP 176
3.7.2. Librarian standard module Graph 184
3.7.3. System 211 Library Standard Module
3.8. Development of information systems for business practice 215
Workshop: programming in Turbo Pascal 226
Chapter 4. Assignments for independent work
4.1. Using Norton Commander 318
4 2 Working in the graphic environment Paint 320
4.3. Basic commands integrated environment Turbo Pascal 320
4.4. Windowed Interface in User Programs 324
4.5. Linear Structure Programs 324
4.6. Forking Structure Programs 325
4.7. Looping 326
4.8. Treatment multidimensional arrays data 326
4.9. Processing Character Data 327
4.10. Processing string data 327
4.11. Processing of data of the Record type "328
4.12. Typed and text files 328
4.13. Procedures and Functions 329
4.14. Processing arrays of data 329
4.15. Lines and Records 330
Chapter 5. Information service Internet 331
5.1. Structure global network 331
5.1.1. Information services network 331
5.1.2 Network protocols 333
5.2. Document viewers information networks 335
5.2.1. Netscape Communicator 336 Browser Window Interface
5.2.2. MS Browser Window Interface Internet Explorer 341
5.3. Email 346
5.3.1. Installation mailbox 346
5.3.2. Editing the settings file 350
5.3.3. Structure email 350
5.3.4. Treatment mail messages 356
5 3.5. Work with the address book 359
Workshop: application technology Email 361
5.4. Working with Web Documents 364
5.4.1. Methods for Accessing Web Documents 364
5.4.2. Installing the Search Page 372
5 4 3. Copying Web Pages 372
5.b. Participation in teleconferences 374
5.5.1. Service structure 374
5.5.2. Reading news 375
5 5.3. Reading newsgroup articles 377
5 5.4. Viewing teleconference documents 379
5 5.5. Sending documents to teleconference 380
5.6. Search engines and resource directories 381
5 6 1. Yellow Pages of the Russian Segment of the Internet 382
5 6.2. Science and technology 384
5 6 3. Education 385
5 6.4. Online store 389
5.6.5. Virtual Libraries 390
5.7. Internet Association of Information Networks of Russia 392
5.7.1. National ISPs 393
5.7.2. Informational resources Internet 395
Workshop: Searching and Processing Information on the Internet 395
Chapter 6. HTML - Hypertext Markup Language
6.1. The structure of HTML-language 401
6.1.1. HTML document tag 403
6.1.2. 403 Document Title
6.1.3. 404 document body
6.2. Writing the text of a 404 web document
6.2.1. Beginning of paragraph and end of line 405
6.2.2. Heading Styles 405
6 2.3. Physical Styles 406
6.2.4. Logic Styles 407
6.2.5. Preformatted text 407
6.2.6. Lists 408
6.2.7. Special symbols 409
6.3. Organization of hypertext links 410
6.3 1.forming pointers 411
6 3 2. Creating a Table of Contents Using Index Names 411
6.3 3. Using hyperlinks to form the table of contents of the current web document 412
Workshop - shaping the text of a web document 412
6.4. Text color and background images 416
6 5. Installation of tabular elements 418
6.5.1 Basic Table Tags 418
6.5.2. Placing Complex Tables 421
6.5.3. Combining text and table on the document field 423
Workshop: Lists and Tables in the Field of Web Pages 425
6.6. Placing Graphics 429
6 6.1 Horizontal lines 429
6 6.2. Graphic images 430
6 6.3. Reference Pointers 433
6 6.4. Graphic elements in the margins of tables 433
6 7 Image maps in the field of a web document 436
6.8 Organizing Web Pages Using Frames 439
Workshop: Using Graphics and Frames to Organize Web Documents
Glossary of Terms 445
Literature 458