Lecture1 data structure(introduction)

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Introduction to Data

Structures

Lecture 1

Khalid Khankan and Abdisalam Issa-Salwe

Taibah University

College of Computer Science & Engineering

Computer Science Department

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Outline

1. Choosing Data Structures

2. Selecting Data Structure

3. Data Structure Philosophy

4. Abstract Data Types

5. Logical vs. Physical Form

6. Programs

7. Algorithm Properties

8. References

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Data Structures

A data structure is a scheme

for organizing data in the

memory of a computer.

Some of the more commonly

used data structures include

lists, arrays, stacks, queues,

heaps, trees, and graphs.

Binary Tree

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Data Structures

The way in which the data is

organized affects the

performance of a program

for different tasks.

Computer programmers

decide which data structures

to use based on the nature

of the data and the

processes that need to be

performed on that data.

Binary Tree

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The Need for Data Structures

Data structures organize data

more efficient programs.

More powerful computers more complex applications.

More complex applications demand more calculations.

Complex computing tasks are unlike our everyday experience.

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More powerful computers more complex applications.

More complex applications demand more calculations.

Complex computing tasks are unlike our everyday experience.

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Example: A Queue

A queue is an example of commonly used simple data

structure. A queue has beginning and end, called the

front and back of the queue.

Data enters the queue at one end and leaves at the other.

Because of this, data exits the queue in the same order in

which it enters the queue, like people in a checkout line at

a supermarket.

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Example: A Binary Tree

A binary tree is another

commonly used data

structure. It is organized like

an upside down tree.

Each spot on the tree, called

a node, holds an item of data

along with a left pointer and

a right pointer. Binary Tree

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Example: A Binary Tree

The pointers are lined up

so that the structure forms

the upside down tree, with

a single node at the top,

called the root node, and

branches increasing on the

left and right as you go

down the tree. Binary Tree

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Choosing Data Structures

By comparing the queue with

the binary tree, you can see

how the structure of the data

affects what can be done

efficiently with the data.

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A queue is a good data structure

to use for storing things that need

to be kept in order, such as a set

of documents waiting to be

printed on a network printer.

.

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The jobs will be printed in the

order in which they are received.

Most network print servers

maintain such a print queue.

.

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A binary tree is a good data

structure to use for searching

sorted data.

The middle item from the list is

stored in the root node, with

lesser items to the left and greater

items to the right.

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A search begins at the root. The

computer either find the data, or

moves left or right, depending on

the value for which you are

searching.

Each move down the tree cuts the

remaining data in half.

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Items can be located very quickly in a tree.

Telephone directory assistance information is stored in a tree, so that a name and phone number can be found quickly.

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For some applications, a queue is the best data structure to use.

For others, a binary tree is better.

Programmers choose from among many data structures based on how the data will be used by the program.

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More powerful computers more complex

applications.

More complex applications demand more

calculations.

Complex computing tasks are unlike our

everyday experience.

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Selecting a Data Structure

Select a data structure as follows:

1. Analyze the problem to determine the resource

constraints a solution must meet.

2. Determine the basic operations that must be

supported. Quantify the resource constraints

for each operation.

3. Select the data structure that best meets these

requirements.

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Data Structure Philosophy

Each data structure has costs and benefits.

Rarely is one data structure better than

another in all situations.

A data structure requires:

space for each data item it stores,

time to perform each basic operation,

programming effort.

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Data Structure Philosophy

Each data structure has costs and benefits.

Rarely is one data structure better than

another in all situations.

A data structure requires:

space for each data item it stores,

time to perform each basic operation,

programming effort.

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Abstract Data Types

Abstract Data Type (ADT): a definition for a data type solely in terms of a set of values and a set of operations on that data type.

Each ADT operation is defined by its inputs

and outputs. Encapsulation: Hide implementation details.

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Data Structure

A data structure is the physical implementation of an ADT. Each operation associated with the ADT is

implemented by one or more subroutines in the implementation.

In a OO language such as C++, an ADT and its implementation together make up a class.

Data structure usually refers to an organization for data in main memory.

File structure: an organization for data on peripheral storage, such as a disk drive.

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Abstract data types

we also looked at how to use an array to model a list

we call a list an abstract data type it has defined operations

add to the end of the list

find an item in the list

delete an item from the list etc.

it can be implemented in different ways array, piece of paper, tree, linked list

the operations have the same effect no matter how the list is implemented

other examples of abstract data types set, queue, stack, map

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Sets

a set is an unordered

group of elements

duplicates are not

allowed

otherwise how would

you tell them apart?

the set of "foods I

like" contains the

elements

cereal, chicken, chips,

tomato soup, orange

juice and chocolate

Cereal

Chicken

Chocolate

set of foods I like

Chips

Orange

juice Tomato

soup

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Lists

a list is a group of elements arranged in some order so we can talk about

the first element in the list

the last element in the list

element 3

the order could be meaningful alphabetical

by size

by time

or it could simply be the order the elements were added

duplicates are allowed they are distinguished by their position

Things I ate today

(in chronological order)

1. cereal

2. orange juice

3. chocolate

4. tomato soup

5. chocolate

6. chicken

7. chips

8. chocolate

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Queue

a queue is a a group of items arranged in order of arrival

new items can only be added to the back of the queue

items can only be removed from the front of the queue shoppers at supermarket check-out

taxis in rank

computer processes awaiting execution

first-in, first-out (FIFO)

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Stacks

a stack is a group of items

arranged in order

new items can only be

added to the top of the stack

items can only be removed

from the top of the stack

stack of chairs or books

plates in cafeteria

temporary data storage in

CPU

last in, first out (LIFO)

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Maps

A map is a collection of

key/element pairs

each element is stored in

a position determined by

its key

can look up an element

using its key

also known as a

dictionary

key is the word

element is the definition

algorithm

confusion

university

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Data Structure

A data structure is the physical implementation of an ADT. Each operation associated with the ADT is implemented by one

or more subroutines in the implementation.

In a OO language such as C++, an ADT and its implementation together make up a class.

Data structure usually refers to an organization for data in main memory.

File structure: an organization for data on peripheral storage, such as a disk drive.

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Labeling collections of objects

Humans deal with complexity by assigning a

label to an assembly of objects. An ADT

manages complexity through abstraction.

Hierarchies of labels

Ex1: transistors gates CPU.

In a program, implement an ADT, then think only

about the ADT, not its implementation.

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Logical vs. Physical Form

Data items have both a logical and a physical form.

Logical form: definition of the data item within an ADT. Ex: Integers in mathematical sense: +, -

Physical form: implementation of the data item within a data structure. Ex: 16/32 bit integers, overflow.

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Data Type

ADT:

Type

Operations

Data Items:

Logical Form

Data Items:

Physical Form

Data Structure:

Storage Space

Subroutines

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Problems, Algorithms and Programs

Programmers deal with:

problems,

algorithms and

computer programs.

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Problems

Problem: a task to be performed.

Best thought of as inputs and matching

outputs.

Problem definition should include constraints

on the resources that may be consumed by

any acceptable solution.

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Problems (cont)

Problems mathematical functions

A function is a matching between inputs (the domain) and outputs (the range).

An input to a function may be single number, or a collection of information.

The values making up an input are called the parameters of the function.

A particular input must always result in the same output every time the function is computed.

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Algorithms and Programs

Algorithm: a method or a process followed to solve a problem. A recipe: The algorithm gives us a “recipe” for solving

the problem by performing a series of steps, where each step is completely understood and doable.

An algorithm takes the input to a problem

(function) and transforms it to the output. A mapping of input to output.

A problem can be solved by many algorithms.

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A problem can have many algorithms

For example, the problem of sorting can be solved

by the following algorithms:

Insertion sort

Bubble sort

Selection sort

Shell sort

Merge sort

Others

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Algorithm Properties

An algorithm possesses the following properties: It must be correct.

It must be composed of a series of concrete steps.

There can be no ambiguity as to which step will be performed next.

It must be composed of a finite number of steps.

It must terminate.

A computer program is an instance, or concrete representation, for an algorithm in some programming language.

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Programs

A computer program is a concrete

representation of an algorithm in some

programming language.

Naturally, there are many programs that

are instances of the same algorithms,

since any modern programming language

can be used to implement any algorithm.

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References

Michael Main, Data Structures and Other

Objects Using Java (Third Edition)

Education

Lecture1 data structure(introduction)