Count the Number of Complete Components | Multiple Approaches | Leetcode 2685 | codestorywithMIK

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Disjoint Set Union -    • Disjoint Set Union | DSU | Graph Concepts ...  
Disjoint Set Union By Rank and Path Compression -    • Disjoint Set Union By Rank and Path Compre...  
Disjoint Set Union By SIZE and Path Compression -    • Disjoint Set Union By SIZE and Path Compre...  

Hi Everyone, this is the 71st video of our Playlist "Graphs : Popular Interview Problems".
Now we will be solving a good Graph practice problem - Count the Number of Complete Components | Multiple Approaches | Leetcode 2685 | codestorywithMIK

We will focus on why this is a Graph based problem and why Topological Sort is the ideal approach for this problem.


Problem Name : Count the Number of Complete Components | Multiple Approaches | Leetcode 2685 | codestorywithMIK
Company Tags : AMAZON
My solutions on Github(C++ & JAVA) - https://github.com/MAZHARMIK/Intervie...
Leetcode Link : https://leetcode.com/problems/count-t...


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Video Summary :
DFS Approach: This method uses Depth-First Search to traverse the graph and count the number of vertices and edges in each connected component. It then checks if the component forms a complete subgraph by verifying the number of edges.

BFS Approach: This method replaces DFS with Breadth-First Search using a queue. It explores each component level by level, tracking the number of vertices and edges. The completeness condition is checked similarly to the DFS approach.

DSU Approach: This method utilizes Disjoint Set Union (Union-Find) to group connected components efficiently. After forming components, it counts edges within each set and verifies if they satisfy the complete graph condition.


✨ Timelines✨
00:00 - Introduction
0:27 - Motivation
0:52 - Problem Explanation
5:04 - What is Complete Graph ?
9:15 - Approach-1 (DFS)
18:32 - Coding DFS
22:40 - Approach-2 (BFS)
24:32 - Coding BFS
26:37 - Approach-3 (DSU by Size)
40:31 - Coding DSU by Size

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