Which of the following operations typically has a time complexity of O(n) in the worst case for a hashmap?
All of the above
Search
Deletion
Insertion
What is linear probing in the context of open addressing for collision resolution?
Resizing the hash table to accommodate more elements.
Using a different hash function to avoid collisions.
Using a linked list to store colliding elements at the same index.
Probing for an empty slot by sequentially searching from the collision index.
How are dictionaries typically implemented in programming languages?
Using hashmaps to provide fast key-value lookups.
Using linked lists for fast insertions.
Using arrays for efficient indexing.
Using binary trees for sorted key storage.
What is a real-world application of hashmaps?
Sorting a list of numbers in ascending order.
Storing and retrieving data in databases.
Performing depth-first search in a graph.
Compressing files to reduce storage space.
What is a key advantage of using a hashmap over a sorted array for searching?
Hashmaps allow duplicate keys.
Hashmaps consume less memory.
Hashmaps maintain data in sorted order.
Hashmaps offer faster search on average.
What does a hashmap store data in?
Sorted Array
Linked List
Key-Value Pairs
Binary Tree
What is the primary advantage of using a hashmap over a linear search in an array when searching for a specific value?
Hashmaps can store sorted data.
Hashmaps can handle duplicate values more efficiently.
Hashmaps use less memory.
Hashmaps offer faster search times on average.
Why are hash functions typically designed to be fast to compute?
To ensure efficient insertion, deletion, and search operations.
To minimize memory usage.
To prevent data loss during collisions.
To maintain the sorted order of keys.
In a symbol table implementation using a hashmap, what do the keys usually represent?
Memory addresses of variables.
Names of variables or identifiers.
Values of variables.
Data types of variables.
Why is a good hash function important for hashmap performance?
To ensure that keys are evenly distributed across the hash table, reducing collisions.
To minimize the number of comparisons required to find an element.
To allow for efficient resizing of the hash table.
To reduce the memory used by the hash table.