Algo-Cast

It is a great learning project where you will find out various algo-problems having multiple different solutions in your favorite language (Javascript).

Algorithms and Data structure with interview questions

If you want to contribute, will be highly appreciated. PRs accepted. Contributor must update the README.md with every PR, with some brief overview of the problem and solutions.

Here are list of Algo problems and solutions :

1. Two-sum Three-sum

2. Merge-intervals

3. Longest Substring Without Repeating Characters

4. Longest-common-prefix

5. Product Array Puzzle

6. Reorder Data in Log Files

7. UTF-Validation

8. Union-find-connected

a.) Quick Find b.) Quick Union c.) Weighted Quick Union d.) Path Compression Union Improvement

9. Anagrams

10. Autocomplete Search

11. Capitalization

12. Chunk

13. Find Missing Positive number

14. Find Pair

15. Fizz Buzz

16. Matrix

17. Find Maximum characters

18. Min-max-without If

19. Longest Palindrome Substring

20. Palindrome

21. Find power of number

22. Pyramid

23. Roman To Int

24. Steps

25. Valid Paranthesis

26. Longest Valid Paranthesis

27. Vowels

28. Word Ladder

Reversing-Questions

1. Reverse an integer

2. Reverse a string

Searching-Algorithrms

1. Breadth First Search

2. Depth First Search

3. Binary Search Tree

4. Linear Search

Sorting-Algorithrms

First two are divide and conquer

1. Merge Sort

2. Quick Sort

3. Bubble Sort

4. Insertion Sort

5. Selection Sort

6. Use Cases

Graph

1. Number-of-islandsORclusters

2. Binary Tree Serialize

3. K Closet point to origin

DP

1. Coin Change Problem

2. Fibonacci Memoization

Linked List

1. Add-Two-Numbers-Linked-list

2. Merge two sorted list

3. MergeKSortedList

4. Reverse-linked-list

LeetCode questions

1.Find even digits in an array

2.Max Consecutive Ones

3.Duplicating Zeros

4.Merge Sorted array

5.Check If N and Its Double Exist

6.Valid Mountain Array

Space Complexity - Auxiliary space

means the space taken by the whole algorithm, not the space taken up by the inputs

1. Most primitive number( booleans, undefined,numbers, null) have O(1) constant space

2. String requires O(n) space (where n is length of the string)

3. Array and objects ( reference types) requires O(n) space (where for array n is length, number of keys for objects)

Best to Worse case performance measurement

1. O(1) - Constant - BEST

2. O(log n) - Searching Algorithm have this, Efficient Sorthing Algorithm have this & Recursion some time have space complexity in log

3. O(n)

1. O(n log(n))

1. O(n2/n3) etc- Worse

When to use objects

1. When you don't need order.
2. When you need fast access/insertion and removal

Big(O) of objects

1. Insertion - O(1)
2. Removal - O(1)
3. Searching - O(N)
4. Access - O(1)

Big(O) of objects methods

1. Object.keys - O(N)
2. Object.values - O(N)
3. Object.entries - O(N)
4. Object.hasOwnProperty - O(1)

When to use Arrays

1. When you need order.
2. When you need fast access/insertion and removal

Big(O) of Arrays

1. Insertion - It depends
2. Removal - It depends
3. Searching - O(N)
4. Access - O(1)

Big(O) of Array methods

1. push - O(1)
2. pop - O(1)
3. shift - O(N)
4. unshift - O(N)
5. concat - O(N)
6. slice - O(N)
7. splice - O(N)
8. sort - O(n log n)
9. foreach/map/filter/reduce etc - O(N)