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

Determine about the post conditions assertion, Determine about the Post con...

Determine about the Post conditions assertion A  post condition is an assertion which should be true at completion of an operation. For instance, a post condition of the squ

Splay trees, Addition of new records in a Binary tree structure always occu...

Addition of new records in a Binary tree structure always occurs as leaf nodes, which are further away from the root node making their access slower. If this new record is to be ac

What is algorithm, What is Algorithm A finite sequence of steps for a...

What is Algorithm A finite sequence of steps for accomplishing some computational task. An algorithm should Have steps which are simple and definite enough to be done

How to measure the algorithm efficiency, How to measure the algorithm's eff...

How to measure the algorithm's efficiency? It is logical to examine the algorithm's efficiency as a function of some parameter n showing the algorithm's input size. Instance

Find the optimal control, 1. Use the Weierstrass condition, find the (Stron...

1. Use the Weierstrass condition, find the (Strongly) minimizing curve and the value of J min for the cases where x(1) = 0, x(2) = 3. 2. The system = x 1 + 2u; where

Illustrate the visual realism applications, Illustrate the Visual realism a...

Illustrate the Visual realism applications a)   Robot Simulations : Visualization of movement of their links and joints  and end effector movement etc. b)  CNC programs ver

System defined data types, System defined data types:- These are data t...

System defined data types:- These are data types that have been defined by the compiler of any program. The C language contains 4 basic data types:- Int, float,  char and doubl

Parallel implementation of the raytracer, You are supposed to do the follow...

You are supposed to do the following: Write a parallel implementation of the raytracer using pthreads. Measure and compare the execution times for (i) the sequential ver

Define the term - array, Define the term - Array A fixed length, ord...

Define the term - Array A fixed length, ordered collection of values of same type stored in contiguous memory locations; collection may be ordered in several dimensions.

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