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Software Development Exam  >  Software Development Test  >  DSA in C++  >  Test: Priority Queue - Software Development MCQ

Priority Queue - Free MCQ Practice Test with solutions, Software Development


MCQ Practice Test & Solutions: Test: Priority Queue (15 Questions)

You can prepare effectively for Software Development DSA in C++ with this dedicated MCQ Practice Test (available with solutions) on the important topic of "Test: Priority Queue". These 15 questions have been designed by the experts with the latest curriculum of Software Development 2026, to help you master the concept.

Test Highlights:

  • - Format: Multiple Choice Questions (MCQ)
  • - Duration: 30 minutes
  • - Number of Questions: 15

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Test: Priority Queue - Question 1
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Which of the following data structure is used to implement a priority queue efficiently?

Detailed Solution: Question 1

A heap is a specialized tree-based data structure that satisfies the heap property. It is commonly used to implement a priority queue efficiently.

Test: Priority Queue - Question 2
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What is the time complexity of inserting an element into a priority queue implemented using a binary heap?

Detailed Solution: Question 2

Inserting an element into a priority queue implemented using a binary heap takes O(log n) time complexity in the worst case, where n is the number of elements in the heap.

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Test: Priority Queue - Question 3
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In a priority queue, the element with the highest priority is always placed at the:

Detailed Solution: Question 3

In a priority queue, the element with the highest priority is always placed at the front (or top) of the queue.

Test: Priority Queue - Question 4
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Which of the following operations can be performed on a priority queue?

Detailed Solution: Question 4

A priority queue supports both insertion and deletion operations efficiently. Elements are inserted based on their priority, and the element with the highest priority can be removed efficiently.

Test: Priority Queue - Question 5
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Which of the following is NOT a valid application of a priority queue?

Detailed Solution: Question 5

Priority queues are not typically used in depth-first search (DFS) traversals of graphs. DFS uses a stack-based approach rather than a priority-based approach.

Test: Priority Queue - Question 6
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What will be the output of the following code?
#include <iostream>
#include <queue>

int main() {
    std::priority_queue<int> pq;
    pq.push(10);
    pq.push(5);
    pq.push(15);
    pq.push(3);
    std::cout << pq.top();
    return 0;
}

Detailed Solution: Question 6

The code creates a priority queue and pushes elements 10, 5, 15, and 3 into it. The 'top()' function retrieves the element with the highest priority, which is 10 in this case.

Test: Priority Queue - Question 7
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What will be the output of the following code?
#include <iostream>
#include <queue>

int main() {
    std::priority_queue<int, std::vector<int>, std::greater<int>> pq;
    pq.push(10);
    pq.push(5);
    pq.push(15);
    pq.push(3);
    std::cout << pq.top();
    return 0;
}

Detailed Solution: Question 7

This code creates a priority queue with a custom comparator function 'std::greater<int>', which makes the queue a min heap instead of the default max heap. So, the 'top()' function retrieves the smallest element, which is 3 in this case.

Test: Priority Queue - Question 8
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What will be the output of the following code?
#include <iostream>
#include <queue>

int main() {
    std::priority_queue<int> pq;
    pq.push(10);
    pq.push(5);
    pq.push(15);
    pq.push(3);
    
    while (!pq.empty()) {
        std::cout << pq.top() << " ";
        pq.pop();
    }
    return 0;
}

Detailed Solution: Question 8

The code creates a priority queue and pushes elements 10, 5, 15, and 3 into it. Then it uses a loop to repeatedly print the top element and remove it from the queue. The elements are printed in descending order because the priority queue is implemented as a max heap.

Test: Priority Queue - Question 9
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What will be the output of the following code?
#include <iostream>
#include <queue>

int main() {
    std::priority_queue<std::pair<int, int>> pq;
    pq.push({1, 5});
    pq.push({2, 3});
    pq.push({3, 7});
    pq.push({4, 1});
    
    while (!pq.empty()) {
        auto p = pq.top();
        std::cout << "(" << p.first << ", " << p.second << ") ";
        pq.pop();
    }
    return 0;
}

Detailed Solution: Question 9

The code creates a priority queue of pairs of integers. Each pair represents an element with its associated priority. The pairs (1, 5), (2, 3), (3, 7), and (4, 1) are pushed into the queue. The 'top()' function retrieves the pair with the highest priority, which is (1, 5) in this case.

Test: Priority Queue - Question 10
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What will be the output of the following code?
#include <iostream>
#include <queue>

int main() {
    std::priority_queue<int> pq;
    pq.push(10);
    pq.push(5);
    pq.push(15);
    pq.push(3);
    pq.push(10);
    
    std::cout << pq.size();
    return 0;
}

Detailed Solution: Question 10

The code creates a priority queue and pushes elements 10, 5, 15, 3, and 10 into it. The 'size()' function returns the number of elements in the queue, which is 5 in this case.

Test: Priority Queue - Question 11
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What is the time complexity of finding the maximum element in a priority queue implemented using a binary heap?

Detailed Solution: Question 11

Finding the maximum element in a priority queue implemented using a binary heap takes O(log n) time complexity because it involves traversing the heap's height.

Test: Priority Queue - Question 12
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Which of the following operations can be performed in constant time on a priority queue?

Detailed Solution: Question 12

A priority queue supports finding the minimum element in constant time. The minimum element is always at the front (or top) of the queue.

Test: Priority Queue - Question 13
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Which of the following data structures can be used to implement a priority queue other than a binary heap?

Detailed Solution: Question 13

AVL trees, Red-Black trees, and B-trees can be used to implement a priority queue. However, binary heaps are more commonly used due to their simplicity and efficiency.

Test: Priority Queue - Question 14
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What will be the output of the following code?
#include <iostream>
#include <queue>

int main() {
    std::priority_queue<int> pq;
    pq.push(10);
    pq.push(5);
    pq.push(15);
    pq.push(3);
    
    pq.pop();
    std::cout << pq.top();
    return 0;
}

Detailed Solution: Question 14

The code creates a priority queue and pushes elements 10, 5, 15, and 3 into it. After that, the 'pop()' function removes the element with the highest priority (which is 15), and the 'top()' function retrieves the new highest priority element, which is 10.

Test: Priority Queue - Question 15
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Which of the following is NOT a valid implementation of a priority queue?

Detailed Solution: Question 15

AVL trees are self-balancing binary search trees and are not commonly used to implement a priority queue. Binary heaps, Fibonacci heaps, and hash maps are often used for priority queue implementations.

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About this Software Development Practice Test

This test contains 15 MCQs on Priority Queue with detailed solutions for each question. It is part of the DSA in C++ course on EduRev, designed to align with the current Software Development syllabus. Each solution explains not just the correct answer but also gives you an understanding of the topic — not just to attempt the question but also help you prepare for the exam with practice.

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