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Due to their usefulness, they were later included in several other implementations of the C++ Standard Library (e.g., the GNU Compiler Collection's (GCC) libstdc++ [2] and the Visual C++ (MSVC) standard library). The hash_* class templates were proposed into C++ Technical Report 1 (C++ TR1) and were accepted under names unordered_*. [3]
Here the index can be computed as some range of bits of the hash function. On the other hand, some hashing algorithms prefer to have the size be a prime number. [19] For open addressing schemes, the hash function should also avoid clustering, the mapping of two or more keys to consecutive slots. Such clustering may cause the lookup cost to ...
When the hash function is chosen randomly, the cuckoo graph is a random graph in the Erdős–Rényi model. With high probability, for load factor less than 1/2 (corresponding to a random graph in which the ratio of the number of edges to the number of vertices is bounded below 1/2), the graph is a pseudoforest and the cuckoo hashing algorithm ...
find the value (if any) that is bound to a given key. The argument to this operation is the key, and the value is returned from the operation. If no value is found, some lookup functions raise an exception, while others return a default value (such as zero, null, or a specific value passed to the constructor).
Perfect hash functions may be used to implement a lookup table with constant worst-case access time. A perfect hash function can, as any hash function, be used to implement hash tables, with the advantage that no collision resolution has to be implemented. In addition, if the keys are not in the data and if it is known that queried keys will be ...
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 ...
GLib provides advanced data structures, such as memory chunks, doubly and singly linked lists, hash tables, dynamic strings and string utilities, such as a lexical scanner, string chunks (groups of strings), dynamic arrays, balanced binary trees, N-ary trees, quarks (a two-way association of a string and a unique integer identifier), keyed data lists, relations, and tuples.
When creating concurrent hash tables, the functions accessing the table with the chosen hashing algorithm need to be adapted for concurrency by adding a conflict resolution strategy. Such a strategy requires managing accesses in a way such that conflicts caused by them do not result in corrupt data, while ideally increasing their efficiency ...