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This is a list of hash functions, including cyclic redundancy checks, checksum functions, and cryptographic hash functions. This list is incomplete ; you can help by adding missing items . ( February 2024 )
Here a first-level hash function g is also used to map elements onto a range of r integers. An element x ∈ S is stored in the Bucket B g(x). [4] Then, in descending order of size, each bucket's elements are hashed by a hash function of a sequence of independent fully random hash functions (Φ 1, Φ 2, Φ 3, ...), starting with Φ 1. If the ...
A universal hashing scheme is a randomized algorithm that selects a hash function h among a family of such functions, in such a way that the probability of a collision of any two distinct keys is 1/m, where m is the number of distinct hash values desired—independently of the two keys. Universal hashing ensures (in a probabilistic sense) that ...
The following tables compare general and technical information for a number of cryptographic hash functions. See the individual functions' articles for further information. This article is not all-inclusive or necessarily up-to-date. An overview of hash function security/cryptanalysis can be found at hash function security summary.
The following pseudocode is an implementation of an open addressing hash table with linear probing and single-slot stepping, a common approach that is effective if the hash function is good. Each of the lookup, set and remove functions use a common internal function find_slot to locate the array slot that either does or should contain a given key.
Furthermore, a deterministic hash function does not allow for rehashing: sometimes the input data turns out to be bad for the hash function (e.g. there are too many collisions), so one would like to change the hash function. The solution to these problems is to pick a function randomly from a family of hash functions.
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In computer science, dynamic perfect hashing is a programming technique for resolving collisions in a hash table data structure. [1] [2] [3] While more memory-intensive than its hash table counterparts, [citation needed] this technique is useful for situations where fast queries, insertions, and deletions must be made on a large set of elements.