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

Tree traversal, Q. What do you understand by the tree traversal? Write down...

Q. What do you understand by the tree traversal? Write down the procedure for traversing a binary tree in preorder and execute it on the following tree.    Ans: Th

Explain the representations of graph, Explain the representations of graph....

Explain the representations of graph. The different ways of representing a graph is: Adjacency list representation : This representation of graph having of an array Adj of

Sorting algorithm for singly linked lists, Q. Which sorting algorithm can b...

Q. Which sorting algorithm can be easily adaptable for singly linked lists? Explain your answer as well.        Ans: The simple Insertion sort is sim

Which sorting algorithm is adaptable to singly linked list, Which sorting a...

Which sorting algorithm is easily adaptable to singly linked lists? Simple Insertion sor t is easily adabtable to singly linked list.

Multiple queue, algorithm for multiple queue with example program

algorithm for multiple queue with example program

Determine about the unreachable code assertion, Determine about the unreach...

Determine about the unreachable code assertion An unreachable code assertion is an assertion that is placed at a point in a program that shouldn't be executed under any circum

Nested for loop, nested for loop for (i = 0; i for (j = 0; j seq...

nested for loop for (i = 0; i for (j = 0; j sequence of statements } } Here, we observe that, the outer loop executes n times. Every time the outer loop execute

What is a range - a structured type in ruby, Range: A Structured Type in Ru...

Range: A Structured Type in Ruby Ruby has a numerous structured types, comprising arrays, hashes, sets, classes, streams, and ranges. In this section we would only discuss rang

Single pointer pointing to the tail of the queue, Can a Queue be shown by c...

Can a Queue be shown by circular linked list with only single pointer pointing to the tail of the queue? Yes a Queue can be shown by a circular linked list with only single p

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