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Test: Searching and Sorting - 1 - Software Development MCQ


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10 Questions MCQ Test - Test: Searching and Sorting - 1

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Test: Searching and Sorting - 1 - Question 1

Which of the following is an example of a linear search algorithm?

Detailed Solution for Test: Searching and Sorting - 1 - Question 1

Linear search, also known as sequential search, checks each element of the list one by one until the target element is found or the end of the list is reached.

Test: Searching and Sorting - 1 - Question 2

Which sorting algorithm has the best average-case time complexity?

Detailed Solution for Test: Searching and Sorting - 1 - Question 2

Merge sort has a time complexity of O(n log n) in the average case, making it more efficient than other sorting algorithms.

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Test: Searching and Sorting - 1 - Question 3

Which of the following is an example of an in-place sorting algorithm?

Detailed Solution for Test: Searching and Sorting - 1 - Question 3

Quick sort is an in-place sorting algorithm, meaning it doesn't require additional memory to perform the sorting operation.

Test: Searching and Sorting - 1 - Question 4

Which of the following is an advantage of quick sort over merge sort?

Detailed Solution for Test: Searching and Sorting - 1 - Question 4

Quick sort has a smaller memory footprint compared to merge sort as it uses in-place partitioning to sort the elements.

Test: Searching and Sorting - 1 - Question 5

Which sorting algorithm is preferred when the data is already partially sorted?

Detailed Solution for Test: Searching and Sorting - 1 - Question 5

Insertion sort performs well when the data is already partially sorted because it efficiently places elements in their correct positions by comparing and shifting adjacent elements.

Test: Searching and Sorting - 1 - Question 6

Which sorting algorithm has the worst-case time complexity of O(n2)?

Detailed Solution for Test: Searching and Sorting - 1 - Question 6

Bubble sort has a worst-case time complexity of O(n2), where n is the number of elements in the array. It occurs when the array is in reverse order.

Test: Searching and Sorting - 1 - Question 7

What is the time complexity of merge sort in the worst case scenario?

Detailed Solution for Test: Searching and Sorting - 1 - Question 7

Merge sort has a time complexity of O(n log n) in the worst-case scenario. It divides the array into halves recursively and then merges them, resulting in a logarithmic time complexity.

Test: Searching and Sorting - 1 - Question 8

Which of the following is an example of an unstable sorting algorithm?

Detailed Solution for Test: Searching and Sorting - 1 - Question 8

Bubble sort is an example of an unstable sorting algorithm. Unstable sorting algorithms may change the relative order of equal elements during the sorting process, while stable sorting algorithms preserve the order.

Test: Searching and Sorting - 1 - Question 9

The time complexity of binary search is:

Detailed Solution for Test: Searching and Sorting - 1 - Question 9

Binary search has a time complexity of O(log n), where n is the number of elements in the sorted array.

Test: Searching and Sorting - 1 - Question 10

What will be the output of the following code?
#include <iostream>
using namespace std;

void insertionSort(int arr[], int n) {
    for (int i = 1; i < n; i++) {
        int key = arr[i];
        int j = i - 1;
        while (j >= 0 && arr[j] > key) {
            arr[j + 1] = arr[j];
            j--;
        }
        arr[j + 1] = key;
    }
}

int main() {
    int arr[] = {5, 2, 4, 6, 1, 3};
    int n = sizeof(arr) / sizeof(arr[0]);
    insertionSort(arr, n);
    for (int i = 0; i < n; i++) {
        cout << arr[i] << " ";
    }
    return 0;
}

Detailed Solution for Test: Searching and Sorting - 1 - Question 10

The code implements the insertion sort algorithm, which sorts the array in ascending order. The sorted array will be {1, 2, 3, 4, 5, 6}.

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