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Mastering the 'Find First Occurrence' Problem with Rolling Hash in Strings | Leetcode #28 Explained

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"Mastering the 'Find First Occurrence' Problem with Rolling Hash in Strings | Leetcode #28 Explained"
Summary: This video covers an in-depth solution to Leetcode's Problem #28, "Find the Index of the First Occurrence in a String." Learn how to implement a rolling hash technique for substring searching to find the first occurrence of a "needle" string within a "haystack." We’ll explore examples, edge cases, and hashing intricacies to handle collisions, ensuring efficient substring matching even for large inputs.
Key Highlight:
Discover the rolling hash method to optimize substring search.
Learn to handle hash collisions accurately for precise substring matching.
Walkthrough of practical examples and edge cases to strengthen your understanding.
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Problem Summary:
Objective: Compress a string by using the count of repeated characters. The original array should be modified in-place with the new length of the string.
Input: An array of characters.
Output: The new length of the array after compression.
Key Approach to Solve the Problem:
Initialize Pointers and Counter:
Use two pointers: one (read) to iterate over the array and another (write) to update the array with compressed characters.
Initialize a counter to track the frequency of each character.
Iterate and Count Characters:
As you iterate, count the occurrences of each character.
When a different character is encountered or the end of the array is reached, proceed to compression.
Compress and Update:
Write the character and its count (if greater than 1) to the write pointer's position.
Update the write pointer accordingly.
Handle Single Characters:
If a character occurs only once, just write the character without the count.
Return New Length:
The write pointer's final position indicates the new length of the compressed string.
This problem requires careful manipulation of pointers and in-place array modifications to ensure space efficiency. The challenge lies in correctly handling the compression logic and updating the array without additional space for the compressed version.
Summary: This video covers an in-depth solution to Leetcode's Problem #28, "Find the Index of the First Occurrence in a String." Learn how to implement a rolling hash technique for substring searching to find the first occurrence of a "needle" string within a "haystack." We’ll explore examples, edge cases, and hashing intricacies to handle collisions, ensuring efficient substring matching even for large inputs.
Key Highlight:
Discover the rolling hash method to optimize substring search.
Learn to handle hash collisions accurately for precise substring matching.
Walkthrough of practical examples and edge cases to strengthen your understanding.
#######################
Problem Summary:
Objective: Compress a string by using the count of repeated characters. The original array should be modified in-place with the new length of the string.
Input: An array of characters.
Output: The new length of the array after compression.
Key Approach to Solve the Problem:
Initialize Pointers and Counter:
Use two pointers: one (read) to iterate over the array and another (write) to update the array with compressed characters.
Initialize a counter to track the frequency of each character.
Iterate and Count Characters:
As you iterate, count the occurrences of each character.
When a different character is encountered or the end of the array is reached, proceed to compression.
Compress and Update:
Write the character and its count (if greater than 1) to the write pointer's position.
Update the write pointer accordingly.
Handle Single Characters:
If a character occurs only once, just write the character without the count.
Return New Length:
The write pointer's final position indicates the new length of the compressed string.
This problem requires careful manipulation of pointers and in-place array modifications to ensure space efficiency. The challenge lies in correctly handling the compression logic and updating the array without additional space for the compressed version.
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