Robert Bosch Hash Tables Quiz 2

Explanation: While hash tables are commonly used in database indexing, spell checking, and symbol table implementation, they are not typically used as the primary data structure for sorting algorithms. Sorting algorithms often rely on other data structures such as arrays or linked lists.

Explanation: When two elements have the same hash value in a hash table, they are typically stored at the same slot using separate chaining. Separate chaining allows multiple elements with the same hash value to be stored in a linked list or another data structure within the slot.

Explanation: The worst-case time complexity of searching for an element in a hash table is O(n). This occurs when all elements have the same hash value, resulting in a linear search within the slot where they are stored.

Explanation: Inefficient insertion and deletion are not disadvantages of using a hash table. Hash tables provide efficient insertion and deletion operations on average. However, they do have limitations in supporting ordered operations and can suffer from collisions and increased memory usage.

Explanation: A hash table handles collisions by storing the colliding elements in separate slots using separate chaining or probing techniques. Separate chaining uses linked lists or other data structures within each slot, while probing involves searching for the next available slot.

Explanation: A drawback of using separate chaining for collision resolution is increased memory usage. Each slot in the hash table needs to store additional data structures (e.g., linked lists) to handle collisions, which can lead to higher memory requirements.

Explanation: The primary disadvantage of using linear probing for collision resolution is slower search performance. Linear probing can lead to clustering, which increases the average probe sequence length and slows down the search operation.

Explanation: Bubble sort method is not a common hash function used in hash tables. It is a sorting algorithm that operates on arrays or lists.

Explanation: The purpose of a hash function in a hash table is to map keys to values and determine the slot where an element should be stored. The hash function calculates an index based on the key and maps it to a specific slot in the hash table.

Explanation: While a good hash function should be deterministic, uniform distribution, and reversible (if necessary), it does not necessarily need to be collision-free. Collisions can occur in hash functions, and the hash table should have a mechanism to handle them.