Create a data type that allows you to insert, delete the maximum, and delete the minimum (all in logarithmic time), as well as find the maximum and find the minimum (both in constant time). Tip: Use two heaps.
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Create a data type that allows you to insert, delete the maximum, and delete the minimum (all in logarithmic time), as well as find the maximum and find the minimum (both in constant time). Tip: Use two heaps.
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- Design a data type that supports the following operations: insert, delete the maximum, and delete the minimum (all in logarithmic time); andfind the maximum and find the minimum (both in constant time). Hint: Use two heapsThe implementation of a queue in an array, as given in this chapter, uses the variable count to determine whether the queue is empty or full. You can also use the variable count to return the number of elements in the queue. On the other hand, class linkedQueueType does not use such a variable to keep track of the number of elements in the queue. Redefine the class linkedQueueType by adding the variable count to keep track of the number of elements in the queue. Modify the definitions of the functions addQueue and deleteQueue as necessary. Add the function queueCount to return the number of elements in the queue. Also, write a program to test various operations of the class you defined.I. TRUE OR FALSE. Write the word TRUE if the statement is true or FALSE if the statement is false. Write your answers on the space provided at the end of each numbers. 5. Heapify is the procedure for maintaining the heap property when one of the elements of the heap is changed. 6. A hash function can result in a many-to-one mapping (causing collision). 7. Collisions can be avoided or prevented by using a "good" hash function. 8. When the key is a string, it must be converted to an integer. One of these string conversions is option #1. The probiem with this technique is that anagrams will map to the same index. 9. Radix is a hash function that converts the base-10 integer key into a binary value. 10. Linear probing is the best collision resolution technique. One of the reasons is that clustering of data can be prevented. .
- Implementing a Double Linked List with a Single PointerThe Problem: How can you implement a doubly linked list using only a single pointer for each link?In PriorityQueue.java, write code for the following new functions:1. public boolean add( PriorityQueueNode x )This function adds a new node x to the priority queue. The node is added tothe heap by comparison of the rating attribute. It involves the “percolateup” process and returns true when finished. 2. public PriorityQueueNode remove( )This function removes the minimum element of the priority queue and returnsit. It involves a call to percolateDown( int hole ). 3. private void percolateDown( int hole )This function takes the position of the next available hole in the priority queueand uses it to bubble the elements through the heap until the heap property isrestored. 4. public void display( )This function prints out a formatted tree representation of the priority queueshowing only the rating of each node. The output should resemble that of atree. Tip: you may use the StringBuilder class and the Stringformat( ) method. Empty nodes in the tree can be replaced with “--”.Example output…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.
- In C++, Implement a Priority Queue(PQ) using an UNSORTED LIST. Use an array size of 20 elements. Use a circular array: Next index after last index is 0. Add the new node to next available index in the array. When you add an element, add 1 to index (hit max index, go to index 0). Test if array in full before you add. When you remove an element, from the list, move the following elements to the left to fill in the blank, etc ( Like prior program done with LISTS ) Create a class called Node: Have a Name and Priority. Data set - 1 is the highest priority, 10 is lowest priority. Enqueue and dequeue in the following order. Function Name, Priority Enqueue Joe, 3 Enqueue Fred, 1 Enqueue Tuyet, 9 Enqueue Jose, 6 Dequeue Enqueue Jing, 2 Enqueue Xi, 5 Enqueue Moe, 3 Dequeue Enqueue Miko, 7 Enqueue Vlady, 8 Enqueue Frank, 9 Enqueue Anny, 3 Dequeue Enqueue Xi, 2 Enqueue Wali, 2 Enqueue Laschec, 6 Enqueue Xerrax, 8 Dequeue Dequeue Dequeue Dequeue Dequeue Dequeue Dequeue Dequeue Dequeue Dequeue…using c++ concepts of data structure Make a doubly linked list, take n inputs. Print it.Now, swap any two nodes (picked by the user), and print the list again. The node will be pickedon the basis of their value.Note: You have to swap the Node, by managing the links between them. NOT JUST THEVALUE INSDE THEM.Make a data type that enables you to discover the maximum and minimum, as well as insert, remove, and delete the maximum and minimum (all in logarithmic time). As a hint, use two heaps.
- s is an initially empty circular array-based STACK of size 8, where top has a value of -1 at creation and when the data structure becomes empty. Please go through the lectures where we discussed Stack, where top is used to maintain the location of the most recently inserted element. After each statement on left has been evaluated, please enter the resulting value of the top on right: ArrayStack S = new ArrayStack(8) ; top S.push("P"); top char x = S.pop(); top = S.peek() ; top S. push("C"); top S.push("c"); top S.push("C"); top S.peek() ; top IIIn which scenarios would you prefer to use an array over a linked list, and vice versa?Write a program in Java to manipulate a Double Linked List: Count the number of nodes Insert a new node before the value 7 of Double Linked List Search an existing element in a Double linked list (the element of search is given by the user) Suppose List contained the following Test Data: Input the number of nodes : 4Input data for node 1 : 5Input data for node 2 : 6 Input data for node 3 : 7 Input data for node 4: 9