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Given a BST, which traversal method would allow you to turn it into a min heap using N heap insertions calls in O(N) worst case runtime? Draw an example of this process. First, draw a BST with 4 nodes and height of 3. You can pick the integer values in your BST. Then show the resulting traversal order, and a drawing of the values inserted into a min heap using N heap insertions. Redraw the heap after each insertion.
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- Given a BST, which traversal method would allow you to turn it into a min heap using N heap insertions calls in O(N) worst case runtime? Draw an example of this process. First, draw a BST with 4 nodes and height of 3. You can pick the integer values in your BST. Then show the resulting traversal order, and a drawing of the values inserted into a min heap using N heap insertions. Redraw the heap after each insertion.Create a more efficient HeapVector that just keeps its values in order when necessary: When values are added to the heap, they are appended to the end of the existing heap and the nonHeap flag is set to true. When values are removed, the nonHeap flag is checked, and the Vector, if necessary, is heapified. What are the worst-case and best-case add and delete operation times?Design a more efficient version of HeapVector that keeps its values in order only when necessary: When values are added, they are appended to the end of the existing heap and a nonHeap flag is set to true. When values are removed, the nonHeap flag is checked and the Vector is heapified if necessary. What are the worst-case and best-case running times of the add and remove operations?
- The bounded-buffer solution in the below code uses a last-in-first-out strategy (LIFO).Change the code to implement a FIFO (First-in-First-out) strategy. You may use the (in,out) pointer method(using semaphores to test if the queue is full or empty shouldalleviate the problem of only using up N-1 locations) or implement a FIFO queue. Usethe correct counting semaphore implementation. C code below ******************************************************************************************************************************* #include <stdio.h>#include <stdlib.h>#include <pthread.h>#include <semaphore.h>#define SIZE 5#define NUMB_THREADS 6#define PRODUCER_LOOPS 2typedef int buffer_t;buffer_t buffer[SIZE];int buffer_index;pthread_mutex_t buffer_mutex;/* initially buffer will be empty. full_semwill be initialized to buffer SIZE, which meansSIZE number of producer threads can write to it.And empty_sem will be initialized to 0, so noconsumer can read from buffer until a…Assume we have k heaps, each with a maximum of n items. These are to be combined into a single heap. Each of the following sub-parts provides a different method for merging the heaps, and you are required to calculate the large O running time for each method. We build a new linked list, L, that is empty. We continually remove the highest priority element from each of the k piles hi and insert it at the beginning of L, until hi is empty. The items of L are then transferred to an array and the array is heapified. What is the worst-case running time for a huge O?an application has a huge number of find the maximum operations, but a relatively small number of insert and remove the maximum operations. Which priority- queue implementation do you think would be most effective: heap, unordered array, or ordered array? Explain your Answer.
- Consider a list L = {387, 690, 234, 435, 567, 123, 441}. Here, the number ofelements n = 7, the number of digits l = 3 and radix r = 10. This means that radixsort would require 10 bins and would complete the sorting in 3 passes. illustrates the passes of radix sort over the list. It is assumed that each key is thrown into the bin face down. At the end of each pass, when the keys are collected from each bin in order, the list of keys in each bin is turned upside down to be appended to the output listGiven a BST, which traversal method would allow you to turn it into a min heap using N heap insertions calls in O(N) worst ca se runtime? Implement the process described above in as-close-to-Java code/no English, write the method "changeBSTintoMinHeap" which takes in a BSTNode (i.e. root) and returns a minHeap. You may use helper methods.The school cafeteria offers circular and square sandwiches at lunch break, referred to by numbers 0 and 1 respectively. All students stand in a queue. Each student either prefers square or circular sandwiches. The number of sandwiches in the cafeteria is equal to the number of students. You are given two integer arrays students and sandwiches where sandwiches[i] is the type of the ith sandwich in the stack (i = 0 is the top of the stack) and students[j] is the preference of the jth student in the initial queue (j = 0 is the front of the queue). Part 1: Modify the code given and make it more efficient. You can try to implement your own stack or your own Queue. Or you can use the sandwiches array as a stack without making a separate Stack class. Same with the students array. Part 2: After modifying the code, explain how it works, and why it is more efficient than the solution that you started with. (Or, if it turns out that the change you made is not more efficient, try to…
- Given a BST, which traversal method would allow you to turn it into a min heap using N heap insertions calls in O(N) worst case runtime? Implement the process described above in as-close-to-Java code/no English, write the method "changeBSTintoMinHeap" which takes in a BSTNode (i.e. root) and returns a minHeap. You may use helper methods. You can use code from slides to help you. You must cite all the sources you used. You cannot simply copy and paste code from other resources (besides slides). Your work must be your own.Design a efficient version of HeapVector that keeps its valuesin order only when necessary: When values are added, they are appended tothe end of the existing heap and a nonHeap flag is set to true. When valuesare removed, the nonHeap flag is checked and the Vector is heapified if necessary. What are the worst-case and best-case running times of the add andremove operations?You can implement a queue data structure (DS) using a list/array or a Linked List DS. Nonetheless, the performance (in O(..) factor) can be drastically different depending on your data manipulation pattern. Which of the following Queue implementation is more efficient in terms of O(x) factor? Which data structure (MyQ1, or MyQ2) is better for the following situations (Use big O factor with explanations)? class MyQ1: (using the doubly linked list implementation) class MyQ2: (using the list append (ele) and pop (0) implementation) (a) Most of the data are adding and removing activities in the front of the queue Ans: (b) Most of the data are adding and removing activities at the rear of the queue Ans: