DSA: Hash Table – Expanded Questions

DSA: Hash Table – Expanded Questions.

Basic Conceptual Questions

1. What is a Hash Table? Explain with an example.

• Describe the fundamental concept of a hash table.
• Explain how keys are mapped to values using a hashing function.
• Provide a simple example to illustrate how data is stored and retrieved.

2. What is a Hash Function, and why is it important in a Hash Table?

• Explain the role of a hash function.
• Discuss properties of a good hash function (e.g., fast computation, uniform distribution).
• Give examples of commonly used hash functions.

3. What are the common uses of Hash Tables in real-world applications?

• Discuss scenarios where hash tables are used (e.g., caching, indexing, dictionary implementations).
• Explain how hash tables can improve the performance of such applications.

Implementation Questions:

4. How would you implement a Hash Table from scratch in your preferred language?

• Provide a step-by-step explanation of implementing a hash table.
• Include methods like insert(), get(), delete(), and resize().
• Discuss handling collisions in your implementation.

5. What are the different ways to handle collisions in Hash Tables?

• Explain techniques like separate chaining, open addressing, linear probing, quadratic probing, and double hashing.
• Discuss the pros and cons of each method.
• Provide examples or code snippets for each technique.

5. What is Separate Chaining in Hash Tables? How does it work?

• Describe the method of handling collisions using linked lists or other data structures.
• Explain how elements with the same hash are stored in a bucket.
• Discuss how retrieval and deletion work with separate chaining.

6. What is Open Addressing in Hash Tables, and how does it differ from Separate Chaining?

• Define open addressing and describe methods like linear probing, quadratic probing, and double hashing.
• Compare open addressing with separate chaining.
• Discuss how open addressing deals with clustering issues.

Performance and Complexity Questions:

7. What is the time complexity of operations in a Hash Table?

• Discuss the average and worst-case time complexity for insert(), search(), and delete() operations.
• Explain how the time complexity is affected by collisions and load factor.

8. What is a Load Factor in Hash Tables, and how does it affect performance?

• Define load factor and its formula.
• Explain why maintaining an appropriate load factor is crucial.
• Discuss how resizing affects performance and when to resize a hash table.

9. Why might a Hash Table perform poorly, and how can you optimize it?

• Identify factors like poor hash functions, high load factor, and clustering.
• Suggest ways to improve performance, such as better hash functions, resizing, or using different collision resolution strategies.

Advanced and Scenario-Based Questions:

10. How would you design a Hash Table that supports dynamic resizing?

• Explain how to handle resizing operations when the load factor crosses a threshold.
• Discuss strategies for resizing (e.g., doubling the size).
• Address how to rehash all elements during resizing.

11. How do Hash Tables handle duplicate keys, and what happens when you try to insert a duplicate key?

• Describe how hash tables manage keys that map to the same value.
• Explain different strategies like overwriting the existing value or storing multiple values.

12. Can you explain Double Hashing and when it is used?

• Define double hashing and its formula.
• Describe how double hashing reduces clustering.
• Provide an example of its implementation.

13. How would you use a Hash Table to find duplicates in an array?

• Write an algorithm that uses a hash table to detect duplicates in an array.
• Discuss time and space complexity.
• Explain how this approach compares to other methods like sorting.

What are the limitations of Hash Tables?

• Discuss scenarios where hash tables might not be the best choice.
• Talk about the high memory consumption, the impact of hash collisions, and difficulties in implementing custom hash functions.
• Compare hash tables to other data structures like binary search trees or arrays in terms of their use cases.

Real-World Problem-Solving Questions:

13. How would you use a Hash Table to implement a LRU (Least Recently Used) Cache?

• Explain the design of an LRU cache using a hash table and a doubly-linked list.
• Discuss the time complexity for get() and put() operations.
• Provide code for an LRU cache implementation.

14. How can Hash Tables be used for solving the Two Sum problem?

• Write a solution for the Two Sum problem using a hash table.
• Explain how using a hash table makes the solution more efficient than a brute-force approach.
• Analyze the time complexity of the solution.

15. Describe how a Hash Table is used in a spell checker application.

• Explain how words can be stored in a hash table.
• Describe how the spell checker can quickly look up words.
• Discuss the impact of hash collisions on the speed of spell checking.

16. How would you handle serialization and deserialization of a Hash Table?

• Explain the process of converting a hash table to a format that can be stored or transmitted.
• Discuss the challenges in handling collisions during deserialization.
• Provide a basic example of serialization and deserialization logic.

17. What is the difference between a Hash Map and a Hash Set? When would you use each?

• Define the purpose of both data structures.
• Discuss scenarios where a HashMap is suitable versus where a HashSet would be more appropriate.
• Provide examples of typical use cases for each.

These questions cover the core concepts, implementation, and practical use cases of hash tables, providing a comprehensive understanding that is valuable for interviews or further study in data structures and algorithms.