Sorting Algorithms
Internal
Overview
Many programs use sorting as an intermediate step, and that is why sorting is considered a fundamental operation in computer science.
Sorting Problem
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.
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 Algorithms
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 Sorting Algorithms
These algorithm have in common the fact that they do not compare elements to one another, but they "stare at the guts of an element" to decide what do do next. This implies that you are willing to make assumption on what the data is, in which case you can bypass lower bound.