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A perfect hash function for the four names shown A minimal perfect hash function for the four names shown. In computer science, a perfect hash function h for a set S is a hash function that maps distinct elements in S to a set of m integers, with no collisions. In mathematical terms, it is an injective function.
The code above uses OCaml's default hash function Hashtbl.hash, which is defined automatically for all types. To use a modified hash function, use the functor interface Hashtbl.Make to create a module, such as with Map. Finally, functional maps (represented as immutable balanced binary trees): #
A mid-squares hash code is produced by squaring the input and extracting an appropriate number of middle digits or bits. For example, if the input is 123 456 789 and the hash table size 10 000, then squaring the key produces 15 241 578 750 190 521, so the hash code is taken as the middle 4 digits of the 17-digit number (ignoring the high digit ...
hash HAS-160: 160 bits hash HAVAL: 128 to 256 bits hash JH: 224 to 512 bits hash LSH [19] 256 to 512 bits wide-pipe Merkle–Damgård construction: MD2: 128 bits hash MD4: 128 bits hash MD5: 128 bits Merkle–Damgård construction: MD6: up to 512 bits Merkle tree NLFSR (it is also a keyed hash function) RadioGatún: arbitrary ideal mangling ...
The FNV-0 hash differs from the FNV-1 hash only by the initialisation value of the hash variable: [9] [13] algorithm fnv-0 is hash := 0 for each byte_of_data to be hashed do hash := hash × FNV_prime hash := hash XOR byte_of_data return hash. The above pseudocode has the same assumptions that were noted for the FNV-1 pseudocode.
MurmurHash is a non-cryptographic hash function suitable for general hash-based lookup. [1] [2] [3] It was created by Austin Appleby in 2008 [4] and, as of 8 January 2016, [5] is hosted on GitHub along with its test suite named SMHasher. It also exists in a number of variants, [6] all of which have been released into the public domain. The name ...
The lookup3 function consumes input in 12 byte (96 bit) chunks. [9] It may be appropriate when speed is more important than simplicity. Note, though, that any speed improvement from the use of this hash is only likely to be useful for large keys, and that the increased complexity may also have speed consequences such as preventing an optimizing compiler from inlining the hash function.
The algorithm can be described by the following pseudocode, which computes the hash of message C using the permutation table T: algorithm pearson hashing is h := 0 for each c in C loop h := T[ h xor c ] end loop return h The hash variable (h) may be initialized differently, e.g. to the length of the data (C) modulo 256.