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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 )
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 ...
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. Perfect hash functions may be used to implement a lookup table with constant worst-case access time.
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.
Linear probing is a component of open addressing schemes for using a hash table to solve the dictionary problem.In the dictionary problem, a data structure should maintain a collection of key–value pairs subject to operations that insert or delete pairs from the collection or that search for the value associated with a given key.
The hop information bit-map indicates that item c at entry 9 can be moved to entry 11. Finally, a is moved to entry 9. Part (b) shows the table state just before adding x. Hopscotch hashing is a scheme in computer programming for resolving hash collisions of values of hash functions in a table using open addressing.
Cryptographic hash functions (4 C, 67 P) Cyclic redundancy checks (3 P) H. Hash function (non-cryptographic) (7 P) Pages in category "Hash functions"
Minimizing hashing collisions can be achieved with a uniform hashing function. These functions often rely on the specific input data set and can be quite difficult to implement. Assuming uniform hashing allows hash table analysis to be made without exact knowledge of the input or the hash function used.