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Such hashing is commonly used to accelerate data searches. [10] Producing fixed-length output from variable-length input can be accomplished by breaking the input data into chunks of specific size. Hash functions used for data searches use some arithmetic expression that iteratively processes chunks of the input (such as the characters in a ...
In the programming language C++, unordered associative containers are a group of class templates in the C++ Standard Library that implement hash table variants. Being templates, they can be used to store arbitrary elements, such as integers or custom classes.
A hash table uses a hash function to compute an index, also called a hash code, into an array of buckets or slots, from which the desired value can be found. During lookup, the key is hashed and the resulting hash indicates where the corresponding value is stored. A map implemented by a hash table is called a hash map.
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 ...
Comparison of supported cryptographic hash functions. Here hash functions are defined as taking an arbitrary length message and producing a fixed size output that is virtually impossible to use for recreating the original message.
algorithm fnv-1 is hash := FNV_offset_basis for each byte_of_data to be hashed do hash := hash × FNV_prime hash := hash XOR byte_of_data return hash. In the above pseudocode, all variables are unsigned integers. All variables, except for byte_of_data, have the same number of bits as the FNV hash. The variable, byte_of_data, is an 8-bit ...
gperf is an open source C and C++ perfect hash generator (very fast, but only works for small sets) Minimal Perfect Hashing (bob algorithm) by Bob Jenkins; cmph: C Minimal Perfect Hashing Library, open source implementations for many (minimal) perfect hashes (works for big sets) Sux4J: open source monotone minimal perfect hashing in Java
Several hash table implementations are based on universal hashing. In such applications, typically the software chooses a new hash function only after it notices that "too many" keys have collided; until then, the same hash function continues to be used over and over.