Questions

6 of 17

1What is the average and worst-case time complexity for lookup in a Hash Table?

2What is a Hash Collision?

3What is the difference between HashMap, TreeMap, and LinkedHashMap?

4Why is the worst-case lookup O(n)? How do modern implementations avoid this? (Tree buckets)

5What are the security implications of Hash Collision attacks (HashDoS)?

6What is the Load Factor? How does it trigger a Rehash/Resize?

7What is a Bloom Filter? When is it used? (Cache penetration, Spell check)

8What is a Hash Table? What is a Key-Value pair?

9What is a Cryptographic Hash? How does it differ from a regular hash?

10How do you design a Hash Table from scratch?

11What is a Hash Function? What makes a good hash function?

12What is the significance of Equals() and GetHashCode() in C#/Java when using objects as keys?

13What is Consistent Hashing? How is it used in Distributed Systems?

14Explain Separate Chaining. (Buckets/Linked Lists)

15Explain Open Addressing. (Linear Probing, Quadratic Probing, Double Hashing)

16Why can't we use a Hash Table efficiently for Ordered operations (e.g., find min/max)?

17Why is it bad to use a mutable object as a key in a HashMap?

Data-Structures

Data-Structures

Complexity Analysis

Arrays and Strings

Stacks and Queues

06 / 17

What is the Load Factor? How does it trigger a Rehash/Resize?

Load Factor and Resizing

javascript

1
A lower load factor generally means fewer collisions but more memory usage.
2
A higher load factor improves memory efficiency but can increase lookup cost.
3
Resizing usually allocates a larger table.
4
Existing entries must be rehashed because bucket indexes depend on table capacity.
5
A resize operation itself can take O(n).
6
Over many insertions, resizing can still preserve amortized O(1) insertion.

Difficulty: 3/10

Follow-up Questions

❓Why must entries be rehashed after resizing?
❓How does resizing affect amortized complexity?
❓What load factor would you choose and why?