Data Structure Skills Quiz! Trivia

The code defines a recursive function called "my_recursive_function" that takes an integer parameter "n". If "n" is equal to 0, the function returns. Otherwise, it prints the value of "n" and then calls itself with the parameter "n-1".

In the main function, "my_recursive_function" is called with the argument 10. This means that the function will be called recursively 10 times, each time printing the value of "n" and then calling itself with "n-1".

Therefore, the output of the code will be a sequence of numbers from 10 to 1, with each number separated by a space.

The Tower of Hanoi problem involves moving a stack of disks from one peg to another, following specific rules. A stack is a suitable data structure for this problem because it follows the Last-In-First-Out (LIFO) principle, which aligns with the rules of the Tower of Hanoi problem. By using a stack, we can easily keep track of the disks and their order, allowing us to move them according to the problem's constraints.

The recursive function is called 11 times because it is called recursively until the base case is reached, which is when n becomes 0. In this case, the function is initially called with n = 10, and then it is called again with n = 9, 8, 7, 6, 5, 4, 3, 2, 1, and finally 0. So, the function is called a total of 11 times.

The given piece of code is a function that returns the element at the front of a queue. It first checks if the queue is empty using the isEmpty() function. If the queue is empty, it returns -999 as a placeholder value. Otherwise, it assigns the value at the front of the queue to the variable 'high' and returns it. Therefore, the correct answer is "return the front statement".

The code is implementing a recursive search function called recursive_search_num. It takes an array, a number to search for, the current index, and the length of the array as parameters.

In the main function, an array arr is initialized with values {-11,2,-3,0,3,5,-6,7}, and the number to search for is -2. The length of the array is 8.

The recursive_search_num function is called with the array, the number, the initial index 0, and the length 8.

Inside the recursive_search_num function, it checks if the current index is equal to the length of the array. If it is, it means the number was not found in the array, so it returns -1.

If the current element at the index is equal to the number, it means the number was found, so it returns the current index.

If neither of the above conditions is true, it calls the recursive_search_num function again with the incremented index.

In this case, the number -2 is not present in the array arr, so the function will go through all the elements and reach the end of the array without finding the number. Therefore, the output will be "Index of -2 is -1".

The time complexity of inserting a node in a doubly linked list is O(n). This is because in order to insert a node, we need to traverse the list to find the correct position for insertion. This traversal takes a linear amount of time, proportional to the number of nodes already present in the list. Therefore, the time complexity is O(n).

The space complexity of the post-order traversal in the recursive fashion is O(d). This is because in a post-order traversal, the recursive function calls are made for each node in the tree, and the maximum depth of the recursion is equal to the depth of the tree. Therefore, the space required for the recursive function calls is proportional to the depth of the tree, resulting in a space complexity of O(d).

In order to iterate through the linked list and find the maximum value, a condition needs to be added to the while loop to ensure that the loop continues until the end of the linked list is reached. The condition "temp->next!=0" checks if the next pointer of the current node is not NULL, indicating that there is still a node to iterate to. This ensures that the loop continues until the end of the linked list is reached.

A dynamic array is a variable size data structure that allows for the allocation of memory at runtime. It is different from a static array, which has a fixed size. With a dynamic array, the memory can be reallocated whenever new elements need to be added, making it flexible and efficient for managing changing amounts of data.