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

Test: Priority Queue - Software Development MCQ


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15 Questions MCQ Test DSA in C++ - Test: Priority Queue

Test: Priority Queue for Software Development 2024 is part of DSA in C++ preparation. The Test: Priority Queue questions and answers have been prepared according to the Software Development exam syllabus.The Test: Priority Queue MCQs are made for Software Development 2024 Exam. Find important definitions, questions, notes, meanings, examples, exercises, MCQs and online tests for Test: Priority Queue below.
Solutions of Test: Priority Queue questions in English are available as part of our DSA in C++ for Software Development & Test: Priority Queue solutions in Hindi for DSA in C++ course. Download more important topics, notes, lectures and mock test series for Software Development Exam by signing up for free. Attempt Test: Priority Queue | 15 questions in 30 minutes | Mock test for Software Development preparation | Free important questions MCQ to study DSA in C++ for Software Development Exam | Download free PDF with solutions
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 for Test: Priority Queue - 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 for Test: Priority Queue - 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 for Test: Priority Queue - 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 for Test: Priority Queue - 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 for Test: Priority Queue - 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 for Test: Priority Queue - 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 for Test: Priority Queue - 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 for Test: Priority Queue - 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 for Test: Priority Queue - 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 for Test: Priority Queue - 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 for Test: Priority Queue - 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 for Test: Priority Queue - 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 for Test: Priority Queue - 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 for Test: Priority Queue - 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 for Test: Priority Queue - 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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