In the context of hash tables, what does a high load factor indicate?
A more efficient hash function is being used.
Faster insertion operations.
Lower memory usage.
A higher probability of collisions.
Which of the following is NOT a valid mitigation strategy against hash flooding attacks?
Employing a bloom filter to quickly identify and discard potentially malicious input.
Switching to a different data structure like a tree-based map that offers consistent performance.
Using a fixed-size hashmap to limit the maximum number of collisions.
Implementing a random salt value in the hash function to make collisions unpredictable.
You are implementing an LRU (Least Recently Used) cache with a fixed capacity. Which data structure combination would be most suitable for efficiently managing the cache?
Array + Queue
Binary Search Tree + Heap
Hashmap + Stack
Hashmap + Doubly Linked List
What security risk arises from storing sensitive data like passwords directly in a hashmap, even when hashed?
Storing any data in a hashmap increases the risk of SQL injection attacks.
Hashmaps are inherently less secure than other data structures for storing passwords.
Hash collisions could allow attackers to bypass authentication.
An attacker gaining access to the hashmap could retrieve the plaintext passwords.
Why is it generally recommended to avoid using mutable objects as keys in hash tables?
Hash tables cannot store mutable objects as keys; only immutable objects are allowed.
Mutable keys can lead to inconsistent state if their values are modified after being inserted into the hash table.
Mutable keys make the implementation of the hash table significantly more complex.
Using mutable keys increases the memory overhead of the hash table.
How can a hash flooding attack impact the performance of a web server using a hashmap to store session data?
It can cause a denial-of-service by forcing the server to handle a large number of collisions.
It can improve the efficiency of the hashmap by distributing data more evenly.
It can lead to increased memory usage and faster response times.
It has no impact on performance, as hash flooding attacks only target data integrity.
Python dictionaries use open addressing for collision resolution. Which of the following techniques helps mitigate the performance degradation caused by clustering in open addressing?
Linear Probing with a prime step size
Using a cryptographic hash function
Robin Hood Hashing
Separate Chaining
Which of the following statements accurately describes a key difference in the behavior of Python dictionaries and Java HashMaps?
Python dictionaries maintain insertion order, while Java HashMaps do not guarantee any specific order.
Java HashMaps allow null keys and values, while Python dictionaries do not.
Python dictionaries use separate chaining for collision resolution, while Java HashMaps employ open addressing.
Java HashMaps are synchronized and thread-safe, whereas Python dictionaries are not.
What is the primary advantage of using a universal hash function?
It ensures constant-time performance for all operations.
It provides better performance than any single, fixed hash function.
It makes the hash table resistant to attacks that exploit patterns in the hash function.
It eliminates the possibility of collisions entirely.
Which collision resolution strategy generally performs better in terms of cache locality?
Open Addressing
Cache locality is irrelevant to hash tables
Both perform equally well