Questions
1 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-StructuresData-Structures
Basics
Complexity Analysis
Arrays and Strings
Linked Lists
Stacks and Queues
Hash Tables
01 / 17

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

Hash Table Complexity

javascript
  1. 1

    Average-case lookup: expected O(1).

  2. 2

    Worst-case lookup: O(n) for a conventional chained or open-addressed table.

  3. 3

    Performance depends on hash quality, load factor, collision strategy, and implementation.

  4. 4

    Resizing helps maintain the expected constant-time behavior.

  5. 5

    Some modern implementations can improve pathological bucket behavior to O(log n) using balanced trees.

Difficulty: 2/10

Follow-up Questions

  • ❓Why can lookup become O(n)?
  • ❓How can implementations improve the worst case?