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Introduction to Data Structure and Algorithm Presented By: Pratik Mota
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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

### Transcript of Introduction to datastructure and algorithm

• 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), (n), (n), (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 (n) average-case (n) worst-case O(n) Input instance size o(n) (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 ]