Unit – 1

General introduction to database systems

1.1 General introduction to database systems, Approaches to building a database

Database

The database is a set of interrelated data used to efficiently retrieve, insert and remove data. It is also used in the form of a table, schema, views, and reports to organize the data, etc.

You can conveniently retrieve, attach, and delete information using the database.

Database management system (DBMS)

A DBMS is a programme that enables database creation, specification and manipulation, allowing users to easily store, process and analyse information.

DBMS provides one with an interface or a tool to conduct different operations, such as building databases, storing data in them, updating data, creating database tables, and much more.

The DBMS also provides databases with privacy and security. In the case of multiple users, it also ensures data consistency.

Some Example of DBMS:

●      MySQL

●      Oracle

●      SQL Server

●      IBM DB2

Advantages of DBMS

●       Controls database redundancy: It can control data redundancy because it stores all the data in one single database file and that recorded data is placed in the database.

●       Data sharing: In DBMS, the authorized users of an organization can share the data among multiple users.

●       Easily Maintenance: It can be easily maintainable due to the centralized nature of the database system.

●       Reduce time: It reduces development time and maintenance need.

●       Backup: It provides backup and recovery subsystems which create automatic backup of data from hardware and software failures and restores the data if required.

●       Multiple user interface: It provides different types of user interfaces like graphical user interfaces, application program interfaces

Disadvantages of DBMS

●       Cost of Hardware and Software: It requires a high speed of data processor and large memory size to run DBMS software.

●       Size: It occupies a large space of disks and large memory to run them efficiently.

●       Complexity: Database system creates additional complexity and requirements.

●       Higher impact of failure: Failure is highly impacted the database because in most of the organization, all the data stored in a single database and if the database is damaged due to electric failure or database corruption then the data may be lost forever.

Purpose of Database Systems

It is a set of tools that allows a user to construct and manage databases. In other words, it is general-purpose software that enables users to define, construct, and manipulate databases for a variety of applications.

Database systems are made to handle massive amounts of data. Data management entails both the creation of structures for storing data and the provision of methods for manipulating data. Furthermore, despite system crashes or efforts at illegal access, the database system must preserve the security of the information stored. If data is to be shared across multiple users, the system must avoid any unexpected outcomes.

Fig 1: Process of transforming data

The figure above depicts the process of transforming data into information, knowledge, and action in a database management system.

The file system was used as the foundation for the database applications.

The goal of a database management system (DBMS) is to transform the following:

1. Data into information.

2. Information into knowledge.

3. Knowledge of the action.

Uses of DBMS

The main uses of DBMS are as follows −

●      Data independence and efficient access of data.

●      Application Development time reduces.

●      Security and data integrity.

●      Uniform data administration.

●      Concurrent access and recovery from crashes.

Characteristics of DBMS

●      It stores and manages information in a digital repository hosted on a server.

●      It can provide a logical and transparent picture of the data manipulation process.

●      Automatic backup and recovery mechanisms are included in the DBMS.

●      It has ACID qualities, which keep data healthy in the event of a failure.

●      It has the ability to simplify complex data relationships.

●      It's utilized to help with data manipulation and processing.

●      It is used to ensure data security.

●      It can examine the database from several perspectives depending on the user's needs.

Challenges in building a DBMS

Conflicting goals, such as adherence to design standards (design elegance), processing speed, and information requirements, force database designers to make design tradeoffs.

Design standards

Design guidelines must be followed when creating a database. As a result of these standards, you've been able to create logical structures that reduce data redundancy and, as a result, the chance of destructive data anomalies. You've also learned how to avoid nulls as much as feasible according to standards. In a nutshell, design standards allow you to work with well-defined components and evaluate their interactions with precision. It is practically impossible to establish a suitable design process, analyse an existing design, or trace the expected logical consequence of design modifications without design standards.

Processing speed

High processing speeds are often a major priority in database architecture in many organisations, particularly those that generate huge quantities of transactions. Minimal access time is achieved by reducing the quantity and complexity of logically desirable relationships, which can be achieved by increasing processing speed. For example, a "ideal" design might eliminate nulls by utilising a 1:1 relationship, whereas a better transaction-speed design might combine the two tables to minimise the need for an additional relationship and avoid nulls by using dummy entries. If data retrieval speed is a priority, you may be required to include derived attributes in the design.

Information requirements

The desire of real-time data could be the goal of database design. Complex data requirements may necessitate data transformations, as well as an increase in the number of entities and characteristics in the design. To ensure maximal information creation, the database may have to trade some of its "clean" design structures and/or part of its high transaction performance.

An important goal is to create a design that fits all logical requirements and design norms. However, if this flawless design fails to match the customer's transaction speed and/or information needs, the designer will not have done a good job in the eyes of the end user. In the real world of database design, compromises are unavoidable.

Even as the designer concentrates on the entities, characteristics, relationships, and constraints, end-user requirements like as performance, security, shared access, and data integrity should be considered. The designer must take into account processing needs and ensure that all update, retrieval, and deletion options are available. Finally, a design is worthless unless the finished product can meet all of the required query and reporting criteria.

Last but not least, document, document, document! Make a list of all design activity. Then go over what you've written again. Documentation not only keeps you on track during the design process, but it also allows you (or anyone who follow you) to pick up where you left off when it's time to make changes. Despite the obvious need for documentation, one of the most frustrating aspects of database and systems analysis work is that the "put it in writing" criterion is not always followed throughout the design and implementation stages. The creation of organisational documentation standards is a critical component of assuring data compatibility and consistency.

Key takeaway

DBMS provides one with an interface or a tool to conduct different operations, such as building databases, storing data in them, updating data, creating database tables, and much more.

1.2 Database-DBMS distinction

Difference between Database and DBMS:

1.3 Data models

The modeling of the data description, data semantics, and consistency constraints of the data is the Data Model. It offers conceptual resources at each level of data abstraction to explain the architecture of a database.

Data models are used to describe the design of a database at the logical level.

Some of the data models are: -

1. Entity-Relationship Model

2. Relational Model

4. Network Model

5. Object Relational Model

Entity-relationship model

●       The logical structure of a database can be expressed by an E-R diagram.

●       Relationships are defined in this database model by dividing the object of interest into an entity and its characteristics into attributes.

●       Using relationships, various entities are related.

●       To make it easier for various stakeholders to understand, E-R models are established to represent relationships in pictorial form.

The Main Components of ER Diagram are: -

a) Rectangles - Entity Sets

b) Ellipses - Attributes

c) Diamond - Relation among entity sets

d) Lines - Connects attributes to entity sets and entity sets to relationships.

Fig 2: E-R relationship

The above E-R diagram has two entities: Teacher and Department

Teacher entity has three attributes:

Teacher_id

Teacher_name

Teacher_Subject

Department entity has two attributes: -

Dept_id

Dept_name

Relation Teaches in gives relationship between Teacher, Department.

Relationship can be of the type:

1:1 → One to one

1:M   → One to many

M:1   → Many to one

M:M   → Many to many

Key takeaway:

-         The logical representation of data as objects and relations among them is an ER model.

-         These objects are known as entities, and an interaction between these entities is an association.

Network model

●       Network model uses two different data structures: -

a) A record type is used to represent as entity set.

b) A set type is used to represent a directed relationship between two record types.

●       This is the Hierarchical model's extension. Data is arranged more like a graph in this model, and is allowed to have more than one parent node.

●       Data is more linked in this database model as more relationships are formed in this database model. Also, as the data is more linked, it is also simpler and quicker to access the information. To map many-to-many data relationships, this database model was used.

●       This was the most commonly used database architecture prior to the advent of the Relational Model.

Fig 3: Network model

Key takeaway:

-         Network model is the Hierarchical model's extension

-         Data is arranged more like a graph in this model, and is allowed to have more than one parent node.

Relational and object-oriented data models

Relational model

●       Relational model uses a collection of tables to represent both data and the relationships among those data.

●       This model is useful for constructing a database that can then be converted into relational model tables.

●       Data is arranged in two-dimensional tables in this model and the relationship is preserved by storing a common field.

●       In the relational model, the basic structure of data is tables. In the rows of that table, all information relating to a specific category is stored.

Therefore, in the relational model, tables are also known as relations.

Sample relational database

A. Teacher Table

B.   Department Table

C.    Teaches in table

Object oriented data model

The object-oriented database derivation is the integrity of object-oriented

Programming language systems and consistent systems. The power of the object-oriented databases comes from the cyclical treatment of both consistent data, as found in databases, and transient data, as found in executing programs.

Fig 4: Object-oriented model

Object-oriented databases use small, recyclable separated of software called objects. The objects themselves are stored in the object-oriented database. Each object contains of two elements:

1. Piece of data (e.g., sound, video, text, or graphics).

2. Instructions, or software programs called methods, for what to do with The data.

There are two types of ORM: -

a. Object-Oriented Data Model (OODM)

b. Object-Relational Data Model (ORDM)

These models are used to handle objects:

1) To provide support for complex objects.

2) To provide user extensibility for data types operators and access methods.

3) There should be mechanism to support:

a) Abstract data type.

b) Data of type ‘procedure’.

c) Rules.

Key takeaway:

●       The logical structure of a database can be expressed by an E-R diagram.

●       Relational model uses a collection of tables to represent both data and the relationships among those data.

●       Object-oriented databases use small, recyclable separated of software called objects.

1.4 Three-schema architecture of a database

The architecture of a database management system influences its design. When dealing with a large number of PCs, web servers, database servers, and other networked elements, the same client/server architecture is used.

A client/server architecture is made up of several PCs and a workstation that are all linked by a network.

The design of a database management system is determined by how users link to the database in order to complete their requests.

Fig 5: Types of architecture

A single tier or multi-tier database architecture can be seen. However, database design can be divided into two categories: 2-tier architecture and 3-tier architecture.

1-tier Architecture:

The database is directly accessible to the user in this architecture. It means that the user can sit on the DBMS and use it directly. Any modifications made here will be applied directly to the database. It does not provide end users with a useful tool.

For the creation of local applications, a 1-tier architecture is used, in which programmers can interact directly with the database for fast responses.

Fig 6: 1-tier architecture

2-tier Architecture:

The 2-tier architecture is similar to the basic client-server architecture. Client-side applications can interact directly with the database on the server side in a two-tier architecture. APIs such as ODBC and JDBC are used for this interaction.

The client-side runs the user interfaces and application programs. The server side is in charge of providing features such as query processing and transaction management. The client-side application creates a link with the server side in order to communicate with the DBMS.

Fig 7: 2-tier architecture

3-tier Architecture:

Between the client and the server is another layer in the 3-tier architecture. The client cannot communicate directly with the server in this architecture. The client-side program communicates with an application server, which in turn communicates with the database system.

Beyond the application server, the end user is unaware of the database's presence. Aside from the submission, the database has no knowledge about any other users.

In the case of a wide web application, the 3-tier architecture is used.

Fig 8: 3-tier architecture

Key takeaway

The architecture of a database management system influences its design. When dealing with a large number of PCs, web servers, database servers, and other networked elements, the same client/server architecture is used.

1.5 Various components of a DBMS

You may split the database management system into five main components, which are

1. Hardware
2. Software
3. Data
4. Procedure
5. Database Access Language

In order to see how they all work together to form a database management system, let's have a basic diagram.

Fig 9: Component of DBMS

1. Hardware

When we say hardware, before any data is successfully stored in the memory, we mean computers, hard discs, I/O channels for data, and any other physical part involved.

When we run Oracle or MySQL on our personal computer, the hard disc of our computer, the keyboard we use to type all the commands, the RAM of our computer, the ROM, all become part of the hardware of the DBMS.

2. Software

As this is the software that governs everything, this is the key part. More like a wrapper around the physical database, the DBMS programme gives us an easy-to-use interface for storing, accessing and upgrading data.

The DBMS programme is able to understand and translate the Database Access Language into actual database commands in order to execute them on the DB.

3. Data

Data is the resource for which the DBMS is intended. The motive behind the creation of DBMS was to store and use information.

Data saved by the user is present in a standard database and meta data is stored.

Metadata is data about knowledge. To better understand the data contained in it, this is information stored by the DBMS.

4.  Procedure

Procedures refer to general instructions for using a method to handle a database. This includes procedures for setting up and installing a DBMS, logging in and logging out of the DBMS programme, database maintenance, backups, report creation, etc.

5. Database Access language

Database Access Language is a basic language designed to access, attach, update and delete data stored in any database by writing commands.

In the Database Access Language, a user can write commands and send them to the DBMS for execution, which is then interpreted and executed by the DBMS.

The user can use the access language to build new databases, tables, insert data, fetch stored data, update data and remove data.

Key takeaway:

Hardware means computers, hard discs, I/O channels for data, and any other physical part involved.

Software that governs everything, this is the key part.

Data is the resource for which the DBMS is intended.

Procedures refer to general instructions for using a method to handle a database.

In the Database Access Language, a user can write commands and send them to the DBMS.

1.6 Data Abstraction

The technique of hiding undesirable or irrelevant elements from the end user is known as data abstraction. It offers a unique perspective and aids in the attainment of data independence, which is utilized to improve data security.

Database systems are made up of complex data structures and relationships. These difficulties are hidden from users so that they can simply access the data, and just the relevant section of the database is made visible to them through data abstraction.

Levels of abstraction for DBMS

Complex data structures are present in database systems. Reduce complexity in terms of user usability when retrieving data, and developers utilize levels of abstraction to hide extraneous elements from users to make the system efficient. The use of abstraction levels makes database design easier.

The following are the three levels of abstraction for database management systems:

●      Physical or Internal Level

●      Logical or Conceptual Level

●      View or External Level

Fig 10: Three levels of abstraction

Physical or Internal Level

It is the lowest level of abstraction for DBMSs, defining how data is actually stored, data-structures for storing data, and database access mechanisms. Developers or database application programmers, in fact, decide how to store data in the database.

So, in general, the complete database is specified at the physical or internal level. It is a difficult level to comprehend. Customer information, for example, is stored in tables, and data is stored in blocks of storage such as bytes, gigabytes, and so on.

Logical or Conceptual Level

The logical level is the next higher level or intermediate level. It explains what data is stored in the database and how those data are related to one another. It seeks to explain the full or entire data by describing what tables should be constructed and what the linkages between those tables should be.

It's not as complicated as the physical level. Developers and database administrators use the logical level (DBA). Tables (fields and attributes) and relationships among table attributes make up the logical level.

View or External Level

It is the most advanced level. There are various tiers of views at the view level, and each view only defines a portion of the whole data. It also facilitates user engagement by providing a variety of views or numerous views of the same database.

All users (all tiers' users) can use the view level. This level is the simplest and most straightforward.

For example, a user can interact with a system using a view-level GUI and enter details at the GUI or screen, but the user has no idea how or what data is kept because that information is hidden from the user.

Key takeaway

The technique of hiding undesirable or irrelevant elements from the end user is known as data abstraction. It offers a unique perspective and aids in the attainment of data independence, which is utilized to improve data security.

1.7 Data Independence

In addition to users' data, a database system usually includes a lot of data. For instance, to easily locate and retrieve data, it stores information about data, known as metadata. Modifying or modifying a collection of metadata once it is placed in the database is very difficult. But when a DBMS expands, in order to fulfill the users' requirements, it needs to evolve over time. It will become a boring and highly complicated job if the entire data is based.

Metadata itself follows a layered model, such that it does not impact the data at another level when we modify data on one layer. This data is independent, but is mapped to one another.

Types of data independences

●      Physical data independence

Physical Data Independence is defined as the ability to make adjustments without affecting the higher-level schemas in the structure of the lowest level of the Database Management System (DBMS). Therefore, the Physical level adjustment does not result in any adjustments to the Conceptual or View levels.

●      Logical data independence

Logical Data Independence is defined as the ability to make improvements to the Database Management System (DBMS) middle level structure without affecting the schema or application programmes at the highest level. Changes to the conceptual level should also not result in any changes to the view levels or programmes of the application.

Fig 11: Data independence

1.8 E/R Data model

●      The Entity-Relationship model (ER model) is a type of entity-relationship model. It's a data model at a high level. The data elements and relationships for a given system are described using this model.

●      It creates a database's conceptual architecture. It also creates a very convenient and easy-to-design data view.

●      The database structure is depicted as a diagram called an entity-relationship diagram in ER modeling.

Let's say we're creating a database for a school. The student will be an object in this database, with attributes such as address, name, id, age, and so on. There will be a relationship between the address and another entity with attributes such as city, street name, pin code, and so on.

Fig 12: Example of ER

Component of ER model -

The following components are composed of an ER Diagram:

1. Entity
2. Attributes
3. Relationships

Fig 13: Component of ER model

1.Entity

The object, location, person, or event that stores data in the database may be an entity. In an object-relationship diagram, a rectangle represents an entity.

Examples of an individual include a student, course, boss, employee, patient, etc.

Fig 14: Entity

Entity type:

A list or a set of entities having certain common attributes is an entity type. In a database, a name and a list of attributes define each type of entity.

Entity set:

It is a set (or collection) of entities of the same kind that share attributes or related properties.

For example, it is possible to describe the category of individuals who are lecturers at a university as an entity-set lecturer. Similarly, the collection of students of the organization could represent the community of all university students.

2.Attribute

In an Entity-Relationship Model, an attribute defines an entity's properties or characteristics. It is represented in the ER diagram by an oval or ellipse shape. Each oval shape represents one attribute and is directly linked to the person that is in the shape of the rectangle.

For instance, the attributes defining the Employee form of entity are employee id, employee name, gender, employee age, salary, and mobile no.

Fig 15: Different attributes of employee

In the ER model, the following categories can be defined by an attribute:

1.Simple attribute:

A simple attribute is called an attribute which contains an atomic value and can not be divided further. The gender and salary of a worker, for instance, is also depicted by an oval.

Fig 16: Simple attribute

2. Key attribute:

A key attribute is called an attribute that can uniquely identify an entity in an entity set. It represents a primary key in the ER diagram. In an Entity Relationship diagram, the key attribute is denoted by an oval with an underlying line. For example, for each employee, the employee id would be unique.

Fig 17: Key attributes

3. Composite attribute:

An attribute that is a combination of two or more basic attributes is called a composite attribute. It is defined by an ellipse in an Entity-Relationship diagram, and that ellipse consists of other ellipses. For example, an employee entity type's name attribute consists of first name, second name, and last name.

Fig 18: Composite attribute

4.Derived attribute:

A derived attribute is considered an attribute which can be derived from other attributes. In an entity-relationship diagram, a dashed oval shape is used to represent these attributes. Employee age is, for example, a derived attribute since it varies over time and can be derived from another DOB attribute (Date of birth).

Fig 19: Derived attribute

5.Multivalued attributes:

An attribute which for a given entity contains more than one value. For instance, there may be more than one mobile number and email address for an employee.

Fig 20: Multivalued attribute

3.Relationship

In the Entity-Relation Model, a relationship is used to define the relationship between two or more entities. In the ER diagram, it is illustrated by a diamond shape.

For example, in college student studies, employees work in a department. Here, the links are 'research in' and 'works in'.

Degree of Relationship

A partnership is called the degree of a relationship in which a variety of different individuals participate.

Degree of relationship can be categorized into the following types:

1. Unary Relationship:

A relationship in which a single group of individuals is involved is referred to as a unary relationship. For instance, in a company, an employee manages or supervises another employee.

Fig 21: Unary relationship

2. Binary Relationship: When a relationship includes two people, it is considered a binary relationship.

3. Ternary Relationship: When a relationship contains three individual sets, a ternary relationship is called.

Fig 22: Ternary relationship

4. N-nary Relationship:

If a relationship includes more than three entity sets, an n-ary relationship is named.

Key takeaway:

1. The object, location, person, or event that stores data in the database may be an entity.
2. In an Entity-Relationship Model, an attribute defines an entity's properties or characteristics.
3. Attributes are represented in the ER diagram by an oval or ellipse shape.
4. In the Entity-Relation Model, a relationship is used to define the relationship between two or more entities.

1.9 SQL Concept

Structured Query Language (SQL) is a database query language which is used to store, retrieve and modify data in the relational database. SQL comes in different versions and forms. All of these versions are based upon the ANSI SQL.

Currently, MySQL is the most common programme for database management systems used for relational database management. It is an open-source, Oracle Company - supported database programme. In comparison to Microsoft SQL Server and Oracle Database, the database management system is fast, scalable, and easy to use. It is widely used for building efficient and interactive server-side or web-based business applications in combination with PHP scripts.

Characteristics of SQL

●      It is quick to learn SQL.

●      For accessing data from relational database management systems, SQL is used.

●      SQL will perform database queries against it.

●      To describe data, SQL is used.

●      SQL is used in the database to describe the data and manipulate it when appropriate.

●      To build and drop the database and the table, SQL is used.

●      SQL is used in a database to construct a view, a stored procedure, a function.

●      SQL allows users to set tables, procedures, and display permissions.

Advantages of SQL

●      SQL is easy to learn and use.

●      SQL is a non-procedural language. It means we have to specify only what to retrieve and not the procedure for retrieving data.

●      SQL can be embedded within other languages using SQL modules, pre-compilers.

●      Allows creating procedure, functions, and views using PL-SQL.

●      Allows users to drop databases, tables, views, procedure and cursors.

●      Allows users to set access permissions on tables, views and procedures.

SQL data types

In order to describe the values that a column can hold, SQL Datatype is used.

Each column is needed in the database table to have a name and data type.

Fig 23: SQL data types

1. Binary data types

Three kinds of binary data types are given below:

2.     Numeric data types

The subtypes are given below:

3.     Extract numeric data types

The subtypes are given below:

4.     Character String data types

5.     Date and Time  data types

Literals

Literals are notes or the concept of representing/expressing a meaning that does not change. Literals are equivalent to constants in MySQL. When declaring a variable or executing queries, we may use a literal one.

We will explain the various forms of literal statements in this section and how they can be used in MySQL statements.

The following are the literal forms:

Key takeaway:

1. MySQL is the most common programme for database management systems used for relational database management.
2. Structured Query Language (SQL) is a database query language which is used to store, retrieve and modify data in the relational database.
3. SQL comes in different versions and forms.
4. Literals are equivalent to constants in MySQL. When declaring a variable or executing queries, we may use a literal one.
5. Literals are notes or the concept of representing/expressing a meaning that does not change

Types of SQL Commands

The Structured Query Language (SQL), as we all know, is a database language that allows one to perform certain operations on existing databases as well as build new databases. To complete the tasks, SQL employs commands such as Create, Drop, and Insert.

These SQL commands are primarily divided into four groups:

DDL:

DDL stands for Data Definition Language, and it is a part of SQL that allows a database user to build and restructure database objects, such as tables.

The following are some of the most basic DDL commands that will be addressed in the coming hours:

CREATE TABLE

ALTER TABLE

DROP TABLE

CREATE INDEX

ALTER INDEX

DROP INDEX

CREATE VIEW

DROP VIEW

DML:

DML, or Data Manipulation Language, is a part of SQL that allows you to manipulate data within relational database objects.

DML commands are divided into three categories:

INSERT

UPDATE

DELETE

DQL:

Data Query Language (DQL) is the most focused subject of SQL for modern relational database users, despite having only one instruction.

The following is the base command:

SELECT

A query is a request for information from a database. A query to the database is normally sent to it through an application interface or a command line prompt.

DCL:

In SQL, you can use data control commands to limit who has access to data in the database. These DCL commands are typically used to build objects related to user access and to manage privilege distribution among users.

The following are some data access commands:

ALTER PASSWORD

GRANT

REVOKE

CREATE SYNONYM

TCL:

Only DML commands like INSERT, DELETE, and UPDATE can be used with TCL commands. Since these operations are automatically committed to the database, they can't be used to create or drop tables.

Here are some examples of TCL commands:

COMMIT Saves database transactions

ROLLBACK Undoes database transactions

SAVEPOINT Creates points within groups of transactions in which to ROLLBACK

SET TRANSACTION Places a name on a transaction

SQL Operators and Their Procedure

An operator is a reserved word or character that is used in the WHERE clause of a SQL statement to perform operations like comparisons and arithmetic operations. These Operators are used to define conditions in SQL statements and to function as conjunctions for multiple conditions in a single statement.

●       Arithmetic operators

●       Comparison operators

●       Logical operators

●       Operators used to negate conditions

Arithmetic operator

Assume that 'variable a' and 'variable b' exist. In this case, 'a' has 20 and 'b' has 10.

Comparison operator:

Assume that 'variable a' and 'variable b' exist. In this case, 'a' has 20 and 'b' has 10.

Logical operator:

Assume that 'variable a' and 'variable b' exist. In this case, 'a' has 20 and 'b' has 10.

References:

1. Silberschatz A., Korth H., Sudarshan S. “Database System Concepts”, 6th edition, Tata McGraw Hill Publisher
2. Ramkrishna R., Gehrke J. “Database Management Systems”, 3rd edition, McGraw Hill
3. Rab P., Coronel C. “Database Systems Design, Implementation and Management”, 5th edition, Thomson Course Technology, 2002