Quiz: Data Structures & Algorithms

Stacks are best suited for LIFO access patterns. Queues are best suited for FIFO (First In, First Out) access patterns.

O(1) represents constant time complexity. It means the algorithm always takes the same amount of time to run, regardless of the input size.

To calculate the length of a singly linked list, you must traverse every node from head to tail, resulting in O(n) time complexity.

In a balanced BST, the average time complexity for lookup is O(log n) because each level allows the search space to be halved.

Merge Sort always operates with a worst-case complexity of O(n log n) as it repeatedly splits the array in half and merges the sorted subarrays.

BFS uses a Queue to explore nodes level by level, processing nodes in a breadth-first manner (by “row”).

Depth-First Search (DFS) is typically used to detect cycles in a graph by maintaining a recursion stack to track visited nodes.

Heap Sort maintains a worst-case time complexity of O(n log n), as it builds a heap and repeatedly extracts the maximum element.

Hash tables have an average time complexity of O(1) for accessing elements, assuming a good hash function that minimizes collisions.

The primary operations of a stack are Push (add element), Pop (remove element), and Peek (view the top element without removing it).

Dijkstra’s Algorithm is frequently used for finding the shortest path in graphs with non-negative edge weights. It employs a priority queue to determine the shortest distance efficiently.

AVL Trees and Red-Black Trees are types of self-balancing trees, which ensure that the tree remains balanced after each insertion or deletion.

A base case is necessary in a recursive function to stop the recursive calls when a specific condition is met, preventing infinite recursion.

The two primary operations in a queue are Enqueue (add an element to the back) and Dequeue (remove an element from the front).

Topological sorting can be performed on a graph if it is directed and acyclic (DAG). This type of ordering is useful in task scheduling problems.

The naive recursive implementation of the Fibonacci series has a time complexity of O(2^n) due to the extensive repeated calculations for each Fibonacci number.

A priority queue is most often implemented using a heap because it allows efficient extraction of the highest or lowest priority element.

In-order, Pre-order, and Post-order are the three common techniques to traverse binary trees, each with a different order of visiting nodes.

In a min-heap, the root is always the smallest element, and the height of the tree is O(log n), making insertion and extraction efficient.

Bubble Sort is a stable sorting algorithm as it preserves the relative order of equal elements during sorting.