Time Complexity of HashSet

• Insertion, lookup, and deletion operations typically run in O(1) time on average because the hash function computes an index directly.
• In the worst case, operations degrade to O(n) if multiple elements collide and are stored in a single bucket, requiring a linear search.
• The best-case scenario remains O(1) when elements are evenly distributed across the table.
• HashSets perform efficiently as long as collisions are minimized and the load factor is maintained.

Space Complexity of HashSet

• HashSets require O(n) space in an average case, where n is the number of stored elements.
• If resizing occurs due to high load factor, temporary space usage may increase to O(n + m), where m is the new table size after rehashing.

When to Use a HashSet?

• Fast lookups: Checking if an element exists is O(1) on average.
• Removing duplicates: Perfect for filtering out repeated values.
• Unordered collections: When order does not matter.
• Unique storage: Best for storing distinct items.

In the next section, we will solve some problems related to HashSets.