Algorithms/JavaAlgorithms
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Merge pull request #382 from knightcube/patch-1

Browse Source 
Update README.md
This commit is contained in:
Varun Upadhyay 2018-02-21 06:27:05 -08:00 committed by GitHub
commit 8b359c7f8f
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 25 additions and 25 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
README.md
View File

@ -37,7 +37,7 @@ __Properties__
### Merge
![alt text][merge-image]
From [Wikipedia][merge-wiki]: In computer science, merge sort (also commonly spelled mergesort) is an efficient, general-purpose, comparison-based sorting algorithm. Most implementations produce a stable sort, which means that the implementation preserves the input order of equal elements in the sorted output. Mergesort is a divide and conquer algorithm that was invented by John von Neumann in 1945.
From [Wikipedia][merge-wiki]: In computer science, merge sort (also commonly spelt mergesort) is an efficient, general-purpose, comparison-based sorting algorithm. Most implementations produce a stable sort, which means that the implementation preserves the input order of equal elements in the sorted output. Mergesort is a divide and conquer algorithm that was invented by John von Neumann in 1945.
__Properties__
* Worst case performance O(n log n)
@ -97,7 +97,7 @@ Comparing the complexity of sorting algorithms (Bubble Sort, Insertion Sort, Sel
![alt text][linear-image]
From [Wikipedia][linear-wiki]: linear search or sequential search is a method for finding a target value within a list. It sequentially checks each element of the list for the target value until a match is found or until all the elements have been searched.
Linear search runs in at worst linear time and makes at most n comparisons, where n is the length of the list.
The linear search runs in at the worst linear time and makes at most n comparisons, where n is the length of the list.
__Properties__
* Worst case performance O(n)