The complexity ladder, Data Structure & Algorithms

Assignment Help:

The complexity Ladder:

  • T(n) = O(1). It is called constant growth. T(n) does not raise at all as a function of n, it is a constant. For illustration, array access has this characteristic. A[i] takes the identical time independent of the size of the array A.
  • T(n) = O(log2 (n)). It is called logarithmic growth. T(n) raise proportional to the base 2 logarithm of n. In fact, the base of logarithm does not matter. For instance, binary search has this characteristic.
  • T(n) = O(n). It is called linear growth. T(n) linearly grows with n. For instance, looping over all the elements into a one-dimensional array of n elements would be of the order of O(n).
  • T(n) = O(n log (n). It is called nlogn growth. T(n) raise proportional to n times the base 2 logarithm of n. Time complexity of Merge Sort contain this characteristic. Actually no sorting algorithm that employs comparison among elements can be faster than n log n.
  • T(n) = O(nk). It is called polynomial growth. T(n) raise proportional to the k-th power of n. We rarely assume algorithms which run in time O(nk) where k is bigger than 2 , since such algorithms are very slow and not practical. For instance, selection sort is an O(n2) algorithm.
  • T(n) = O(2n) It is called exponential growth. T(n) raise exponentially.

In computer science, Exponential growth is the most-danger growth pattern. Algorithms which grow this way are fundamentally useless for anything except for very small input size.

Table 1 compares several algorithms in terms of their complexities.

Table 2 compares the typical running time of algorithms of distinct orders.

The growth patterns above have been tabulated in order of enhancing size. That is,   

  O(1) <  O(log(n)) < O(n log(n)) < O(n2)  < O(n3), ... , O(2n).

Notation

Name

Example

O(1)

Constant

Constant growth. Does

 

 

not grow as a function

of n. For example, accessing array for one element A[i]

O(log n)

Logarithmic

Binary search

O(n)

Linear

Looping over n

elements, of an array of size n (normally).

O(n log n)

Sometimes called

"linearithmic"

Merge sort

O(n2)

Quadratic

Worst time case for

insertion sort, matrix multiplication

O(nc)

Polynomial,

sometimes

 

O(cn)

Exponential

 

O(n!)

Factorial

 

 

              Table 1: Comparison of several algorithms & their complexities

 

 

 

Array size

 

Logarithmic:

log2N

 

Linear: N

 

Quadratic: N2

 

Exponential:

2N

 

8

128

256

1000

100,000

 

3

7

8

10

17

 

8

128

256

1000

100,000

 

64

16,384

65,536

1 million

10 billion

 

256

3.4*1038

1.15*1077

1.07*10301

........

 


Related Discussions:- The complexity ladder

State about the pre- and post conditions, State about the pre- and post con...

State about the pre- and post conditions Programmers can easily document other pre- and post conditions and class invariants, though, and insert code to check most value preco

Multikey file organization, what are the applications of multikey file orga...

what are the applications of multikey file organization?

Determine in brief about the boolean, Determine in brief about the Boolean ...

Determine in brief about the Boolean Carrier set of the Boolean ADT is the set {true, false}. Operations on these values are negation, conjunction, disjunction, conditional,

Algorithm to delete node from binary search tree, Normal 0 fals...

Normal 0 false false false EN-IN X-NONE X-NONE MicrosoftInternetExplorer4

Algorithms, b) The user will roll two (six-sided) dices and the user will l...

b) The user will roll two (six-sided) dices and the user will lose the game if (s)he gets a value 1 on either any of the two dices & wins otherwise. Display a message to the user w

Quick sort, This is the most extensively used internal sorting algorithm. I...

This is the most extensively used internal sorting algorithm. In its fundamental form, it was invented by C.A.R. Hoare in the year of 1960. Its popularity lies in the easiness of i

What are the objectives of visual realism applications, What are the Object...

What are the Objectives of visual realism applications After studying this unit, you should be able to know specific needs of realism, add realism to pictures by el

Explain what is stack. describe ways to execute stack. , ST AC K is ...

ST AC K is explained as follows : A stack is one of the most usually used data structure. A stack is also called a Last-In-First-Out (LIFO) system, is a linear list in

Hw7, Handout 15 COMP 264: Introduction to Computer Systems (Section 001) Sp...

Handout 15 COMP 264: Introduction to Computer Systems (Section 001) Spring 2013 R. I. Greenberg Computer Science Department Loyola University Water TowerCampus, Lewis Towers 524 82

#title., Ask quapplication of data structure estion #Minimum 100 words acce...

Ask quapplication of data structure estion #Minimum 100 words accepted#

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd