SyllabusSyllabus

Introduction to Data Structures

Algorithm and Complexity

Array

Stack

Queue

Linked List

Graph and Tree

Ashish Gupta, Data Structures @ JUET, Guna

Recommended BooksRecommended Books

TexT Books:

1. Seymour Lipschutz, “Data Structure”, Schaum’s Outlines, Tata McGraw Hill

2. Sartaj Sahni, “Data Structures, Algorithms”, Tata Mc Graw Hill, New York

3. Preiss, Bruno R., “Data Structures and Algorithms: With Object-Oriented Design Patterns

in C++ “, John Wiley & Sons, New York

4. R.S. Salaria, “Data structure and algorithms using C”

RefeRence Books:

1. Kruse, Tonso, Leung, “Data Structures and Program Design in C”

2. Langsam, Augestein, Tanenbaum, “Data Structures using C and C++”

3. Weiss, “Data Structures and Algorithm Analysis in C/C++”

4. Carrano and Prichard, “Data Abstraction and Problem solving with C++”

5. Corman at el, “Introduction to Algorithms”

Ashish Gupta, Data Structures @ JUET, Guna

Marks DistributionMarks Distribution

Ashish Gupta, Data Structures @ JUET, Guna

Component & Nature

Duration Marks / Weightage

Test-1 1 hrs 15 Test-2 1 hrs 30 min. 25Test-3 2 hrs 35

Tutorials 10Attendance 05

Quiz & Assignments

10

Total 100

Prerequisite KnowledgePrerequisite Knowledge

1. Basic programming constructs from C programming like

data types, operators, decision control, loops, string and

functions etc.

2. Dynamic memory allocation

3. Pointers

Ashish Gupta, Data Structures @ JUET, Guna

Preface of Data structurePreface of Data structure

Data Structure ?

• In general, any representation of data which follow a structure is data structure.

• But by definition, data structure is a way of organizing the data in computer memory

which makes the basic operations on data more efficient.

Basic operation –

• Traversing – Accessing and processing record exactly once

• Insertion – Adding new record to data structure

• Deletion – Removing particular record from the data structure

• Searching – Finding the location of the record in data structure

Special operation –

• Sorting – Arranging the record in some specific order

• Merging – Combining the records from different data structures to single data structure

Ashish Gupta, Data Structures @ JUET, Guna

EfficiencyEfficiency

An algorithm or program is said to be efficient if it solves a problem within provided

resources.

Generally, following two parameters are used to find out the efficiency of algorithm –

1. Space

2. Time

Therefore, we can say

More efficient Program = Less complex program

Complexity – Behavior of algorithm

1. Time Complexity: Behavior of algorithm over the time

2. Space Complexity: Behavior of algorithm over the memory space

Ashish Gupta, Data Structures @ JUET, Guna

Cost Cost

Cost of data structure or algorithm is always calculated in terms of following

parameters –

1. Time Complexity: Time required to perform a basic operation on data

2. Space Complexity: Memory space required to store the data items of data

structure

3. Programming efforts to write code for basic operations.

Ashish Gupta, Data Structures @ JUET, Guna

Type of data structuresType of data structures

1. Array

2. Stack

3. Queue

4. Linked list

5. Tree

6. Graph

7. Heap etc.

Ashish Gupta, Data Structures @ JUET, Guna

Selection of data structureSelection of data structure

Organization of data in memory affects the performance of algorithm

So, selection of data structure plays important role to make algorithm efficient

But, it depends on the nature of problem and operations to be supported.

Typically, following steps are to be followed to select an efficient data structure –

1. Analyze the problem very carefully and estimate the resources a solution must

meet.

2. Determine the basic operation to be supported

3. Select the best data structure which meets the above requirements.

Ashish Gupta, Data Structures @ JUET, Guna

Floor Function –

d denotes the greatest integer which does not exceed value of d and it is called

as floor of d.

Example: 2.4 = 2, 3.5 = 3, 3.9 = 3, -8.2 = -9 and 5 = 5 etc.

Ceiling Function –

d denotes the least integer which is not less the value of d and it is called as

ceiling of d. Example: 2.4 = 3, 3.5 = 4, -8.2 = -8, and 5 = 5 etc.

Therefore, if d is integer then,

d = d ,

Otherwise d + 1 = d

Basic Mathematical NotationsBasic Mathematical Notations

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Basic Mathematical Notations (Cont…)Basic Mathematical Notations (Cont…)

Let k be any integer and let M be a positive integer. Then,

r = k (mod M), r is remainder and 0 <= r < M,

Therefore, k = Mq + r, where q is quotient.

Integer value of d is denoted by INT(d)

INT(3.2) = 3, INT(6.7) = 6, INT(-8.2) =-8

Ashish Gupta, Data Structures @ JUET, Guna

Data types (Recollect)Data types (Recollect)

Ashish Gupta, Data Structures @ JUET, Guna

Data types (Cont…)Data types (Cont…)

Abstract Data Type (ADT) –

A data type can be considered abstract when it is defined in terms of operations on

it, and its implementation is hidden.

Atomic Data Type –

Generally, data structure is represented by memory block which has two parts:

1. Data storage

2. Address storage

Ashish Gupta, Data Structures @ JUET, Guna

Data Address Data Address Data NULL

Data types vs. Data StructuresData types vs. Data Structures

A data type is a well-defined collection of data with a well-defined set of

operations on it. Examples – int, char, float, array etc.

A data structure is an actual implementation of a particular ADT.

Ashish Gupta, Data Structures @ JUET, Guna

SummarySummary

Data structure overview

Need of data structure and how to select relevant data structure

for given problem

Basic C data types and ADT

Comparison between data types and data structures

Ashish Gupta, Data Structures @ JUET, Guna