admin, Author at SimpleTechTalks

Hashing Explained With Simple Example

Hashing is a technique used to search an specific item in large group of items. Hashing uses hash table to perform search in an constant O(1) time. Hashing uses hash functions to fill items in a hash table. To search, each key is passed into the same hash function which computes an index which provides the corresponding value location.

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Maximum Heap Explained With Simple Example

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A Maximum Heap is a binary tree which has following properties:

Binary tree MUST be a complete binary tree which means all leaf nodes are present in either at height “h” or “h-1”.
Key stored in each node is smaller than or equal to keys in the node’s children.

Before going ahead, have a look into Binary Tree.

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Minimum Heap Explained With Simple Example

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A minimum heap is a binary tree which has following properties:

Binary tree MUST be a complete binary tree which means all leaf nodes are present in either at height “h” or “h-1”.
Key stored in each node is smaller than or equal to keys in the node’s children.

Before going ahead have a look into Binary Tree.

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Find the frequency of characters in order of occurrence in string

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Given an input string of characters write a function that returns another string that has the frequency of each consecutive character followed by the character itself.
eg:
aabbbbbzzzzzzzzzz
2a5b10z
abcdefgh
a1b1c1d1e1f1g1h1

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Replace every character by character that is N positions down the alphabet of the String

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Given a string ‘s’ and a number ‘n’, write a function that returns a string with each character in s replaced with another character that is ‘n’ positions down the alphabet.
For example:

If n is 1, A is replaced with B, B is replaced with C and so on.
If n is 2, A is replaced with C, B is replaced with D and so on.
If n is 3, X is replaced with A, Y is replaced with B and so on.

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Priority Queue Explained With Simple Example

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A Priority Queue is an abstract data type similar to Queue which has following properties

Every element in the Priority Queue has a priority associated with it.
An element with high priority will be dequeued first.
If two element has same priority then they are dequeued based on normal Queue basis (FIFO).

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Find Maximum Repeating Element and Maximum Occurrence in Array

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Given an array of sizen, the array contains numbers in range from 0 to k-1 wherekis a positive integer and k <= n.
Find the maximum repeating number in this array.

For example:
Input arr = [1,3,4,5,6,7,4]
Maximum occurence element = 4
Maximum occurence = 2

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Find Missing Number And Duplicate Elements In An Array

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Given an unsorted array of size n. Array elements are in range from 1 to n.
One number from set {1, 2, …n} is missing and one number occurs twice in array.
Find these two numbers.

For example:

Input arr = [1,3,4,5,6,7,4]
Missing Item = 2
Duplicate Item = 4

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AVL Tree Deletion Of Node Explained With Simple Example

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An AVL (Adelson-Velskii and Landis) Tree is a self balancing Binary Search Tree which has the following properties.

For any node “A”, the height of the left subtree of “A” and height of the right subtree of “A” differ by 1 at max.

In case of Binary search Trees worst case search complexity is O(n) in cases when the Binary Search Tree is skewed. In AVL tree, since heights of left and right subtree are balanced, hence search complexity improves to O(log n). Before going ahead have a look into AVL Tree Basics.

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AVL Tree Insertion Of Node Explained With Simple Example

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An AVL (Adelson-Velskii and Landis) Tree is a self balancing Binary Search Tree which has the following properties.

For any node “A”, the height of the left subtree of “A” and height of the right subtree of “A” differ by 1 at max.

In case of Binary search Trees worst case search complexity is O(n) in cases when the Binary Search Tree is skewed. In AVL tree, since heights of left and right subtree are balanced, hence search complexity improves to O(log n). Before going ahead have a look into AVL Tree Basics.

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