Sorting Algorithms: Difference between revisions

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=Sorting Algorithms=
=Sorting Algorithms=
==Key Comparison Sorting==


* [[Insertion Sort#Overview|Insertion sort]]
* [[Insertion Sort#Overview|Insertion sort]]

Revision as of 00:39, 10 August 2018

Internal

Overview

Many programs use sorting as an intermediate step, and that is why sorting is considered a fundamental operation in computer science.

The sorting problem if formally defined as follows: given a sequence of n numbers (a1, a2, ... an) provided as input, the algorithm must produce as output a permutation (reordering) (a'1, a'2, ... a'n) of the input sequence such that a'1 ≤ a'2 ≤ ... ≤ a'n. A specific input sequence is called an instance of the sorting problem. Although conceptually we are sorting a sequence, the input comes to the sorting function as an array with n elements.

The numbers we wish to sort are also known as keys. In practice, it is rarely the case when the keys exist in isolation. Usually they are part of a larger structure called record, which also contains satellite data.

A sorting algorithm may compare keys, and in this case it is said to be a key comparison algorithm. It can be demonstrated that a key comparison algorithm cannot perform better than n lg n. The worst-case running time of comparison sort algorithms is Ω(n lgn).

Non-comparison sort.

Sorting algorithms characteristics:

  • in place: a sorting algorithm is said to sort the input numbers "in place" if it rearranges the numbers within the input array, while at most a constant number of elements are stored outside the array at any time.
  • stability

Sorting Algorithms

Key Comparison Sorting