* Update to index.md + code fix
Before this commit, the js and c++ versions of the code had the O(n) modification with the flag but the Java, Python, Swift ones did not. Also, Bubble sort is originally O(n^2) for all cases and the flag is a modification to it, as far as I know. I updated the code to reflect the same in the first section, and added a new section explaining the modification with examples in 3 languages. Hope this is alright.
* fix: corrected code block syntax
* Completed c++ implemetation
c++ implementation contained only merge function(by the name of merge sort). Completed the implementation by providing both divide and merge functions.
* fix: add triple backticks for c# code
* fix: changed csharp to cpp
Add text "### Application
1. To find all connected components in a given graph
2. To find the shortest path between two nodes of any weighted or unweighted graph
3. To find all nodes within an individual connected components" to article.
* Update index.md
I have changed the spelling such as missing letters and missing punctuation and while scanning the page, I have also adjusted a few links or coding in and out of brackets.
* Update index.md
* fix: replace imgur with s3 for files with potential conflict
(cherry picked from commit 4ec62c0e29a64b0288eade45fb510f25c622945a)
* fix/remote extra link
Co-Authored-By: Randell Dawson <5313213+RandellDawson@users.noreply.github.com>
* fix: revert change
* fix: imgur to s3 for englsh guide without conflict
(cherry picked from commit 9c9f15abf4e755feab79ef7090dacdcf497ea7b6)
* fix: revert unrelated changes
Time Analysis Of AVL Tree:
AVL tree is binary search tree with additional property that difference between height of left sub-tree and right sub-tree of any node can’t be more than 1.
Algorithm Average Worst case
Space O ( n ) {\displaystyle O(n)} O(n) O ( n ) {\displaystyle O(n)} O(n)
Search O ( log n ) {\displaystyle O(\log n)} O(\log n) O ( log n ) {\displaystyle O(\log n)} O(\log n)
Insert O ( log n ) {\displaystyle O(\log n)} O(\log n) O ( log n ) {\displaystyle O(\log n)} O(\log n)
Delete O ( log n ) {\displaystyle O(\log n)} O(\log n) O ( log n ) {\displaystyle O(\log n)} O(\log n)
* fix: replace sh with shell
fix replace terminal with shell
fix replace node with js
fix replace output with shell
fix replace cs with csharp
fix replace c++ with cpp
fix replace c# with csharp
fix replace javasctipt with js
fix replace syntax with js
fix replace unix with shell
fix replace linux with shell
fix replace java 8 with java
fix replace swift4 with swift
fix replace react.js with jsx
fix replace javascriot with js
fix replace javacsript with js
fix replace c++ - with cpp
fix: corrected various typos
fix: replace Algorithm with nothing
fix: replace xaml with xml
fix: replace solidity with nothing
fix: replace c++ with cpp
fix: replace txt with shell
fix: replace code with json and css
fix: replace console with shell
* Adding Time Analysis for B-Trees
Time Analysis for B-Tree:
Suppose a B-tree has n elements and M is the maximum number of children a node can have. What is the maximum depth the tree could have? What is the minimum depth the tree could have?
The worst-case depth (maximum depth) of a B-tree is: logM/2 n.
The best-case depth (minimum depth) of a B-tree is: logM n.
Worst-Case Times for B-Trees:
Adding or removing an element in a B-tree with n elements is O(log n).
* fix: removed duplicate info
