Data structure means keeping the information in memory in a meaningful
format. Data model, on the other hand, shows the relational or
sequential status of data within a set; for example, while flying each
goose represents the data, geese flying in V-shape compose a kind of
data model. Data models are tools for solving problems in computer
science. Data structure and data model are two separate concepts, but
nested in each other; one is dealing with the storage format of the
data, the other focuses on the relationship and links between the data.
This book presents the concepts and implementation of data structure and
algorihtms with examples implemented using C Programming Stylies.
You will find ideas how to use data structures for different types of
data models. The book is designed for academicians, students,
researchers and those who are working as software designer in sector.
Data structure means keeping
or storing the information in memory and storage units in a significant
order. Data consisting of 1s and 0s is simply a bit array; data will not
become information, if the way of its storage is not known. The same
data will turn into different information can when the way of its
storage is changed. Data model, on the other hand, shows the status of
the data within a relational or sequential certain sets; it is a
conceptual approach to problem solving. In practice, every problem, by
its very nature, is prone to the most appropriate data model. This model
should be seen by the designer.
Data structures, in general,
can be classified into two major categories: basic data structures and
user-defined data structures. In basic data structures, expressions of
programming languages are directly declared. On the other hand,
user-defined data structures should be defined beforehand in accordance
with requirements of the data model as in the definition of function.
Character, integer, decimal and string are common examples of basic data
structures.
List or linked list, tree, graph, state machine
and database-relational data model are common data models that are used
frequently. According to the underlying data structure, each data model
has different processing time costs and memory requirements. A balance
is pursued between time and memory space costs in program development.
In general, it can be said that
time cost and memory requirement
are inversely proportional in memory where sequential accesses to memory
is available such as RAM.
Table of Contents
Foreword
About the Author
Acknowledgements
Chapter 1. Introduction
1.1. Data, Data Model and
Information
Basic Data Structures
Characters
Integer Numbers
Fractional or Real Numbers
Strings
Arrays and Matrices
1.3. User-Defined Data
Structures
Creating a Struct
Creating a Union
1.4. Summary
1.5. Questions
Chapter 2. Different Types of Data Models
2.1. Linked List Data Model
2.2. Tree Data Model
2.3. Graph Data Model
2.4. State Machine Data Model
2.5. Database Relational Data
Model
2.6. Network Data Model
2.7. Summary
2.8. Questions
Chapter 3. Algorithms for The Data Models and Problems
3.1. Search and Sort
3.2. Link List
3.3. Graph Algorithms
3.4. Trees
3.5. Finite State Machine
3.6.
Data Compression
3.7.
Artificial
Intelligence
3.8.
Summary
2.9. Questions
Bibliography
Index
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