Course Schedule IV | 3 Detailed Approaches | Leetcode 1462 | codestorywithMIK
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Hi Everyone, this is the 63rd video of our Playlist "Graphs : Popular Interview Problems".
Now we will be solving a good practice problem on Graph - Course Schedule IV | 3 Detailed Approaches | Leetcode 1462 | codestorywithMIK
Problem Name : Course Schedule IV | 3 Detailed Approaches | Leetcode 1462 | codestorywithMIK
Company Tags : will update later
My solutions on Github(C++ & JAVA) - https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/Graph/Topological Sorting/Course Schedule IV.cpp
Leetcode Link : https://leetcode.com/problems/course-schedule-iv/description/
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Video Summary :
Approach 1: Using DFS (or BFS)
The idea is to treat the problem as a graph traversal task. For each query, perform a depth-first search (DFS) starting from the source node to check if the destination node is reachable. The adjacency list represents the graph, and a visited array ensures nodes are not revisited during the traversal. This approach is straightforward but can be repetitive since we traverse the graph separately for each query.
Approach 2: Preprocessing with DFS (or BFS)
Instead of traversing the graph for every query, preprocess the graph to determine all prerequisites for each course. For every pair of nodes, perform a DFS to check if one is reachable from the other and store the results in a matrix (isPrerequisite). During query processing, simply look up the precomputed result. This reduces query time but increases preprocessing time and space usage.
Approach 3: Using Kahn's Algorithm (Topological Sort)
This approach uses topological sorting to process nodes in dependency order. While processing, maintain a mapping of each node to its prerequisites by aggregating the prerequisites of its predecessors. After building this mapping, answering queries becomes a simple lookup. This approach efficiently combines graph traversal and dependency aggregation, making it well-suited for large graphs with many queries.
✨ Timelines✨
00:00 - Introduction
0:37 - Motivation
1:14 - Problem Explanation
7:09 - Approach-1
10:49 - Coding Approach-1
16:37 - Approach-2
24:14 - Coding Approach-2
28:19 - Approach-3 (Kahn's Algorithm - Topological Sorting)
41:01 - Coding Approach-3 (Kahn's Algorithm - Topological Sorting)
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