Introduction to data structure and algorithm -Basics of Data Structure and Algorithm -Practical Examples of where Data Structure Algorithms is used -Asymptotic Notations [ O(n), o(n), θ(n), Ω(n), ω(n) ] -Calculation of Time and Space Complexity -GNU gprof basic

1. Introduction to
Data Structure and Algorithm
Presented By: Pratik Mota

2. Objectives
 Basics of Data Structure and Algorithm
 Practical Examples of where Data Structure Algorithms is used
 Asymptotic Notations [ O(n), o(n), θ(n), Ω(n), ω(n) ]
 Time and Space Complexity
 GNU gprof basic

3. Basics of Data structure and Algorithm
 Data structure is a particular way of storing and organizing data in a computer so that it can be
used efficiently.
 Some Well-know Data structure
1) Array
2) List [Singly and Doubly Linked List]
3) Tree [ Binary,AVL, Red Black..etc ]
4) B+ Tree
5) Heap [ Max and Min Heap ]
6) Hashing
7) Graph [ BFS, DFS,..etc ]

4. Basics of Data structure and Algorithm
Algorithm is a step-by-step procedure for calculations OR you can tell it is sequence of
program instructions designed to compute a particular result.
 Examples:- Sorting, Searching, Shortest Path, Dynamic Programming, Numerical Algorithms
etc..
Sort
INPUT
sequence of numbers
a1, a2, a3,….,an
b1,b2,b3,….,bn
OUTPUT
a permutation of the
sequence of numbers
2 5 4 10 7 2 4 5 7 10
Sorting Algorithm

5. Use of Data Structure and Algorithm

6. Practical Examples (Cont.)

7. Practical Examples (Cont.)

8. Asymptotic Notations
1n
2n
3n
4n
5n
6n
Runningtime
1 2 3 4 5 6 7 8 9 10 11 12 …..
best-case Ω(n)
average-case θ(n)
worst-case O(n)
Input instance size
o(n)
ω(n)

9. Basics of Complexity
O(1) < O(log n ) < O(n) < O(n log n ) < O(n^2) < ….. < O(n^k) < O(2^n)
O( n^2 + n + 1 ) => O(n^2)  MAX ( f(n), g(n) )
 O(N + a)^b  O(N^b)
Time Complexity :- Amount of time taken by an algorithm to run.
Space Complexity:- Extra/Temporary Space use by algorithm .

10. Time and Space Complexity
O(n) O(n^2) O( log n )

11. GNU gprof
 Gprof is a profiling program which collects performance statistics of our programs.
 For Performance analysis -pg option needed for GCC / g++ Compiler.
Ex:- g++ -pg gprof_test.cpp -o gprof_test
 After running ./gprof_test , It generates gmon.out file.
 gmon.out file contain Performance analysis statistics, which can be analyze using
gprof tool. Ex:- gprof gprof_test gmon.out > analysis.txt
 It provides mainly two type of Performance Analysis
1) Flat Profile [ Total amount of time your program spent executing each function ]
2) Call graph [ How much time was spent in each function and its children ]