The hottest Hashing Substack posts right now

XOR is an involution: applying the same XOR twice cancels it out, so adding and removing an element use the same operation and let you update combined hashes in O(1).
Zobrist hashing leverages XOR to update a chessboard hash with only a few XORs per move, enabling fast transposition-table lookups and huge search speedups; collisions are possible but usually acceptable or verifiable.
More generally, pick the algebraic tool that matches your needs — use involutions like XOR for O(1) incremental updates when collisions are tolerable, rolling linear hashes for sliding windows, or Merkle trees when cryptographic integrity is required.

The problem discussed involves finding if one string contains a permutation of another string.
The solution includes using concepts like hashing and working with strings.
The provided examples help understand the problem statement better.

A valid Sudoku board needs to follow specific rules like no repetition of digits in rows, columns, and 3x3 sub-boxes.
Validation of a Sudoku board only requires checking the filled cells and not necessarily solving the board.
Ensure to keep your skills sharp to navigate through challenging situations like layoffs in the tech industry.

Valid Sudoku requires rows, columns, and sub-boxes of a 9x9 grid to have digits 1-9 without repetition.
A partially filled Sudoku board could be valid but not necessarily solvable.
Ensure that each digit from 1-9 appears just once in each row, column, and sub-box of the Sudoku board.

Hashing efficiently maps data to integers for quick searches and insertions.
Design choices in hashing involve handling collision, with options like separate chaining and open probing.
Rolling hash enables efficient substring searches within larger strings by computing hashes incrementally.

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The post discusses a problem of finding all occurrences of a substring in a given string by providing an example scenario.
The problem involves working with strings, hashing, and math concepts.
The author encourages readers to subscribe for more content and mentions a 7-day free trial for access to full post archives.

The post discusses finding all occurrences of a substring in a given string, emphasizing the need to identify starting indices.
Devansh, the author, shares a personalized message and requests feedback from the readers by asking about their university experiences.
Subscribers are encouraged to participate in a survey, fill out forms to support the newsletter, and explore additional content on different platforms of the author.

When solving problems, start with a simple solution even if it's not optimal. It's better to have a working brute-force solution than no solution at all.
Optimizing code involves identifying and eliminating redundant parts. For instance, in string matching problems, consider using techniques like hashing to improve efficiency.
The Rabin-Karp algorithm is a rolling hash function used for string searching. It involves using hashes to compare substrings efficiently, reducing false positives and improving overall performance.

Hash tables allow for efficient storage and retrieval of key-value pairs using hash functions.
Real-world applications of hash tables include dictionaries, caching systems, database indexing, and symbol tables in compilers.
Good hash functions must be efficient, deterministic, and ensure a uniform distribution of generated keys to avoid collisions.

Password hashes should be hashed, not encrypted, for security reasons
Designing a password hashing scheme involves balancing security with user experience
A hash-then-encrypt design can enhance security by making offline password cracking ineffective