What is collision resolution in hashing?

Collision resolution in hashing refers to the process of handling situations where two or more keys are mapped to the same hash value or index in a hash table. This occurrence is known as a collision.

There are various methods for resolving collisions in hashing, including:

1. Separate Chaining: In this method, each hash table index contains a linked list or some other data structure to store multiple elements with the same hash value. When a collision occurs, the new key-value pair is simply appended to the linked list at the corresponding index.

2. Open Addressing: In this approach, when a collision occurs, the algorithm searches for the next available or "open" slot in the hash table to place the key-value pair. There are different techniques within open addressing, such as linear probing (checking the next slot sequentially), quadratic probing (checking slots in a quadratic manner), and double hashing (using a second hash function to determine the next slot).

3. Robin Hood Hashing: This method aims to minimize the variance in the lengths of the linked lists in separate chaining. When a collision occurs, the algorithm compares the distance (or "probe length") between the current slot and the ideal slot for the key-value pair. If the distance is greater than the existing element in the slot, the elements are swapped, ensuring that elements with longer probe lengths are closer to their ideal slots.

4. Cuckoo Hashing: This technique involves using multiple hash functions and multiple hash tables. When a collision occurs, the algorithm checks the other hash tables to find an empty slot. If an empty slot is found, the key-value pair is moved to that table. This process continues until a cycle is detected or a maximum number of rehashing attempts is reached.

The choice of collision resolution method depends on factors such as the expected number of collisions, the desired performance, and the specific requirements of the application. Each method has its advantages and disadvantages, and the selection should be based on the trade-offs between memory usage, search time, and insertion time.