Hashingteknikker

Hashingteknikker, or hashing techniques, refer to methods that map data of arbitrary size to fixed-size values using hash functions. They are used to speed up data retrieval, organize data in hash tables, enable checksums, and support content-addressable storage.

Hash functions can be non-cryptographic or cryptographic. Non-cryptographic hash functions aim for uniform distribution and fast computation; cryptographic hashes also provide security properties such as preimage resistance, second-preimage resistance, and collision resistance, making them suitable for integrity and authentication tasks.

Collision handling includes open addressing (linear probing, quadratic probing, double hashing) and chaining with linked data structures. The choice affects performance and memory usage; maintaining a load factor below a threshold helps.

In hash tables, operations like insert, find, and delete have average time complexity O(1) but degrade with collisions or poor hash quality; resizing or rehashing is common as the table fills.

Beyond storage, hashing is used for checksums, data deduplication, content-addressable storage, and Bloom filters, which use multiple hash functions to probabilistically test membership.

Common hash functions include MurmurHash, CityHash for non-cryptographic purposes, and SHA-256, SHA-3, BLAKE3 for cryptographic needs.

Practical considerations include selecting an appropriate hash function, managing load factor, collision resolution strategy, and security implications like hash-flooding attacks.

Hashingteknikker are foundational in computer science, enabling efficient data organization, integrity verification, and distributed systems.