Explain what is meant by the terms closed bucket, collision, and load factor in the context of hash tables.

Closed Bucket:

A closed bucket, also known as a closed hash table or static hash table, is a data structure that uses a fixed-size array to store key-value pairs. Each bucket in the array represents a range of key values, and all key-value pairs with keys falling within that range are stored in the corresponding bucket. The bucket can be implemented using various data structures such as linked lists, trees, or arrays.

Collision:

In a closed bucket hash table, a collision occurs when two or more keys hash to the same bucket. Since each bucket has a fixed capacity, collisions can lead to conflicts in storing the key-value pairs. To resolve collisions, different collision resolution techniques can be employed, such as chaining, linear probing, and quadratic probing.

Load Factor:

The load factor of a closed bucket hash table is defined as the ratio of the number of key-value pairs stored in the hash table to the total number of buckets available. It indicates the level of utilization of the hash table. A higher load factor signifies a denser hash table, which can lead to more collisions and decreased performance. Typically, a load factor close to 0.7-0.8 is considered to be a good balance between space utilization and performance.

The relationship between closed bucket, collision, and load factor can be summarized as follows:

• Collision: Collisions occur when two or more keys map to the same bucket, causing conflicts in storing the key-value pairs.
• Closed Bucket: A closed bucket hash table uses a fixed-size array to store key-value pairs, leading to collisions when multiple keys hash to the same bucket.
• Load Factor: A high load factor increases the likelihood of collisions, as more key-value pairs are squeezed into a limited number of buckets.

To mitigate collisions and maintain efficient hash table performance, collision resolution techniques are employed. These techniques aim to distribute the key-value pairs evenly across the buckets, reducing conflicts and improving the overall performance of the hash table.