What are the performance metrics for hash tables in C++?

What are the key performance metrics for hash tables in C++?

The key performance metrics for hash tables include average case time complexity for insertions, deletions, and lookups, which is O(1). However, in the worst case, it can degrade to O(n) due to collisions.

How do collisions affect performance?

Collisions can significantly impact performance by increasing the time complexity for operations. If many keys hash to the same index, it can lead to longer chains or more probing, which slows down access times.

What strategies can be used to minimize collisions?

Common strategies include using a good hash function, resizing the hash table when it reaches a certain load factor, and implementing collision resolution techniques like chaining or open addressing.

Can you explain the load factor?

The load factor is the ratio of the number of entries in the hash table to the number of buckets. A lower load factor reduces collisions but increases space usage, while a higher load factor can lead to more collisions.