Test your understanding of hash maps and sets with this easy quiz covering key concepts like frequency counting, deduplication, two-sum problems, anagram detection, and time-space trade-offs. Perfect for beginners looking to solidify their knowledge on these essential data structures.
Which data structure is most efficient for quickly checking if a list of integers contains any duplicates?
Explanation: A set is designed to contain only unique elements, so adding each item from the list to the set and checking for existence fast reveals duplicates. A stack and queue store elements in order, not for deduplication. Arrays can store duplicates and require extra processing to check for repeats, making them less efficient for this purpose.
If you need to count how many times each character appears in the word 'banana', which data structure is best suited for this task?
Explanation: A hash map is ideal for mapping each character to its frequency, allowing fast updates and lookups. A binary tree is less straightforward and may not provide constant-time access. A list or heap doesn't naturally associate values with unique keys, requiring additional logic.
What is the average time complexity for checking if a value exists in a hash set?
Explanation: Hash sets provide constant average time complexity, O(1), for lookups because of efficient hashing. O(n) would apply if you searched each element sequentially, which doesn't use hashing. O(log n) and O(n log n) relate to binary search trees and more complex operations, not hash sets.
You are given an array of numbers and need to find if any two numbers sum up to a target value. Which structure can help check for the complement efficiently as you iterate?
Explanation: A set keeps track of values you've already seen, allowing fast check for the complement (target minus current number). Queue and stack are for ordered data processing, not lookups. Linked lists allow sequential access but do not speed up search for a specific value.
Suppose you need to store only unique user IDs from a list. Which data structure is most space efficient?
Explanation: A set naturally keeps only unique values, so each user ID is stored once, optimizing space. Arrays and queues can store duplicates, which wastes space. A heap is used for priority-based access, not for storing unique entries efficiently.
To check if two words like 'listen' and 'silent' are anagrams, which approach using a hash map is appropriate?
Explanation: Comparing the character frequencies using hash maps accurately determines if words are anagrams. Merely reversing the words or comparing lengths can’t catch rearrangements of letters. Using a set to store the words and comparing sizes doesn’t compare their actual content.
What is the primary purpose of a hash function in a hash map?
Explanation: A hash function transforms a key into an index, enabling efficient storage and fast retrieval. Encryption is unrelated to hashing in this context. Hash maps do not ensure sorted data, and hash functions don't aim to reduce data size, just distribute keys.
What is a common method to handle hash collisions in a hash map?
Explanation: Chaining stores colliding entries in linked lists at each hash bucket. Sorting or duplicating values do not relate to collision management, and stacks are unrelated to resolving hash collisions.
Which structure allows you to quickly find how many unique words are in the sentence: 'cat bat cat rat'?
Explanation: Adding each word to a set gives only the unique elements. A stack or array can contain duplicates, so you'll have to process more to find uniqueness. A priority queue is meant for prioritized access, not uniqueness.
If you want to frequently check how many times a word appears in a document, which data structure is suitable?
Explanation: A hash map associates each word with its frequency, making lookups quick. A queue or stack is data-ordered and inefficient for random access, and tuples don’t have named keys for such use.
When using a hash map to store frequencies, which trade-off are you making?
Explanation: You use more memory to store each key and its frequency, but gain very fast access in return. Increased complexity or errors is not inherent to proper hash map use. Less memory would actually slow down searches if you avoided storing data.
Do standard sets preserve the order of insertion?
Explanation: Traditional sets are unordered collections, so elements aren't stored in any particular order. Some advanced set variants may keep order, but standard sets don't. Numbers or source data structures do not affect the set’s unordered nature.
What is the result of checking membership for a non-existent value in a set, such as 'z' in {'a', 'b', 'c'}?
Explanation: Set membership checks return false when the value is absent. No error occurs unless you try to access the value directly. The answer isn't true, as the value is missing, and zero is not a typical return value for such checks.
When adding a key that already exists in a hash map with a new value, what happens to the previous value?
Explanation: Assigning a new value to an existing key replaces the old value. Hash maps cannot store multiple values for a key, nor do they ignore updates. Errors occur only in read-only implementations, which is not the default behavior.
To find the first repeated element in a list like [3, 1, 4, 1, 5], which structure helps achieve this efficiently?
Explanation: By checking if each number has already appeared in a set, you can quickly spot the first repeat. Arrays and queues don’t speed up presence checks, and 'Dictionary as a stack' isn’t a valid concept for this task.
What type of data is commonly used as a key in a hash map?
Explanation: Hash maps require immutable types as keys to ensure that hash values do not change. Lists, dictionaries, and sets are mutable and cannot be reliably hashed or used as keys.