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400+ Data Structure Interview Questions Practice Test

Data Structure Interview Questions and Answers Practice Test | Freshers to Experienced | Detailed Explanations

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A) O(1): Correct Answer Accessing an element in an array is a constant time operation, denoted as O(1). This is because arrays have contiguous memory allocation, allowing instant access to any element using its index. Unlike operations such as searching or sorting, accessing does not depend on the array's size, hence the time complexity remains constant.

B) Ordered data structure: Correct Answer Hash tables are known for fast data retrieval, efficient collision handling, and storing data in key-value pairs. However, they are not ordered data structures. The order of elements in a hash table is determined by the hash function and does not reflect any inherent sequence or ordering of the elements themselves.

In a binary search tree (BST), which of the following statements is always true?

D) All of the above: Correct Answer In a BST, every node has a left subtree that contains only nodes with values less than the node's value, and a right subtree that contains only nodes with values greater than the node's value. Furthermore, every subtree in a BST is itself a binary search tree. This property is what makes BSTs efficient for operations like searching, inserting, and deleting.

Which of the following data structures is best suited for implementing a Queue?

B) Linked List: Correct Answer While a queue can be implemented using an array or a stack, the latter is generally more efficient, especially for dynamic data. A linked list facilitates easier and more efficient insertions (enqueue operations) at the rear of the queue, as it does not require shifting elements like in an array. Stacks and trees are not typically used for implementing queues due to their LIFO (Last In, First Out) and hierarchical nature, respectively.

D) Linear Search: Correct Answer Divide and Conquer is an algorithmic paradigm where a problem is divided into smaller subproblems, solved independently, and then combined. QuickSort and MergeSort are classic examples of divide and conquer algorithms. However, Binary Search does not follow this paradigm. It operates by sequentially checking each element of the list until a match is found or the list ends, thus not dividing the problem into smaller parts as in divide and conquer. Linear Search is an example where you look at each element one by one to find a value, which is a sequential process, not a divide and conquer approach.

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