Open the Lock | Why BFS | Similar Pattern Problems | META | Leetcode 752 | codestorywithMIK
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This is the 47th Video of our Playlist "Graphs : Popular Interview Problems" by codestorywithMIK
In this video we will try to solve a very good and famous Graph BFS problem : Open the Lock | Why BFS | Similar Pattern Problems | META | Leetcode 752 | codestorywithMIK
I will explain the intuition so easily that you will never forget and start seeing this as cakewalk EASYYY.
We will do live coding after explanation and see if we are able to pass all the test cases.
Also, please note that my Github solution link below contains both C++ as well as JAVA code.
Problem Name : Open the Lock | Why BFS | Similar Pattern Problems | META | Leetcode 752 | codestorywithMIK
Company Tags : META
My solutions on Github(C++ & JAVA) : https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/Graph/Open%20the%20Lock.cpp
Leetcode Link : https://leetcode.com/problems/open-the-lock/
My DP Concepts Playlist : https://youtu.be/7eLMOE1jnls
My Graph Concepts Playlist : https://youtu.be/5JGiZnr6B5w
My Recursion Concepts Playlist : https://www.youtube.com/watch?v=pfb1Zduesi8&list=PLpIkg8OmuX-IBcXsfITH5ql0Lqci1MYPM
My GitHub Repo for interview preparation : https://github.com/MAZHARMIK/Interview_DS_Algo
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Approach Summary :
The provided code implements a solution to find the minimum number of turns required to reach a target combination on a dial lock, given a set of dead-end combinations. Here's a summary of the approach:
1. **Data Structures:** The solution uses a `Queue` to perform a breadth-first search (BFS) traversal of the possible combinations of the lock. A `Set` (`HashSet` in Java) is utilized to store the dead-end combinations for efficient lookup.
2. **Generating Neighbors:** The `fillNeighbors` method generates neighboring combinations of a given combination by either incrementing or decrementing each digit of the combination individually. It checks if the new combinations are not dead ends and adds them to the queue and the set of dead ends if they are not already present.
3. **BFS Search:** The `openLock` method initializes the queue with the starting combination "0000". It then performs a BFS traversal of the combinations in the queue, incrementing the level after each traversal. It continues until either the target combination is found or the queue is empty.
4. **Termination Conditions:** The search terminates when either the target combination is found, in which case the method returns the level representing the minimum number of turns required, or when all possible combinations have been explored without finding the target, in which case it returns -1.
5. **Efficiency:** By utilizing BFS, the algorithm guarantees finding the shortest path to the target combination. Additionally, the use of sets ensures constant-time lookup for dead-end combinations, leading to an efficient solution overall.
Overall, the approach efficiently explores the search space of possible combinations, leveraging BFS to find the shortest path to the target combination while avoiding dead-end combinations.
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✨ Timelines✨
00:00 - Introduction
00:27 - Problem Explanation
04:48 - Understand the Similar Pattern Qns
07:51 - Why BFS ?
12:01 - Dry Run with Example
20:09 - Finding Neighbors
25:56 - Coding it up
33:23 - Time & Space Complexity
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