Root vertex in a derivation tree must belabeled by the start symbolTrue OFalse OInstantaneous descriptions can not be.designed for a Turing machineTrue OFalse OSame Power of two classes means bothclasses of Turing machines accept thesame languagesTrue OFalse O

Root vertex in a derivation tree must be labeled by the start symbol True False Instantaneous descriptions can not be .designed for a Turing machine True False O Same Power of two classes means both classes of Turing machines accept the same languages True False

Root vertex in a derivation tree must be labeled by the start symbol True False Instantaneous descriptions can not be .designed for a Turing machine True False O Same Power of two classes means both classes of Turing machines accept the same languages True False

EBK JAVA PROGRAMMING

9th Edition

ISBN:9781337671385

Author:FARRELL

Publisher:FARRELL

Chapter11: Advanced Inheritance Concepts

Section: Chapter Questions

Problem 19RQ

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implementing a simple binary search tree capable of storing and retrieving student information. The class should have private member variables (each separated by a tab): student's id number - an integer student's name - a string student's declared major The class should have private member functions as a minimum: openFile - opens the input file testFile - tests the input file has been opened properly readFile - reads in one student's information closeFile - close the input file insert - inserts the students information into the proper place in the tree structure search - search for the student id entered by the user inorder - traverses the tree structure prompt - prompts the user for a student id number validate - validate the user input value display - display the contents of the binary tree results - student id found or not found result The class should have public member functions class constructor (if needed) driver - order of execution The input file layout:student id…
implementing a simple binary search tree capable of storing and retrieving student information. The class should have private member variables (each separated by a tab): student's id number - an integer student's name - a string student's declared major The class should have private member functions as a minimum: openFile - opens the input file testFile - tests the input file has been opened properly readFile - reads in one student's information closeFile - close the input file insert - inserts the students information into the proper place in the tree structure search - search for the student id entered by the user inorder - traverses the tree structure prompt - prompts the user for a student id number validate - validate the user input value display - display the contents of the binary tree results - student id found or not found result The class should have public member functions class constructor (if needed) driver - order of execution The input file layout:student id…
Computer Science 1. Implement this recursive method to evaluate an arithmetic expression represented as a tree. If exp.isConstant is true, only the value instance variable is set, whereas if ! exp.isConstant, the value instance variables is not set and the others (operator, left, right) are set. private class ENode { // invariants: boolean isConstant; // true for leaf nodes, false for operator nodes int value; // only has a value if isConstant char operator; // if ! isConstant, can only be '+' or '*' ENode left; // null if isConstant, not null otherwise ENode right; // null if isConstant, not null otherwise}public static int evaluate(ENode exp) { // YOUR CODE HERE}
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The Min-priority Queue is an abstract data type (ADT) for maintaining a collection of elements,each with an associated value called a key. The ADT supports the following operations:• INSERT(Q,x): insert the element x into the queue Q.• MIN(Q): returns the element of Q with the smallest key.• EXTRACT-MIN (Q): removes and returns the element of Q with the smallest key.Implement in Java the Min-priority Queue ADT defined above using a) an array based binary heap b) a binary search tree. Observe that the ADT implementation operations should be in the form q.insert(x),q.min(), etc. Explain in the report your implementation, noting the running time (using bigOh notation) of each operation in both implementations. c) What are the worst-case running times of the three ADT operations when theunderlying BST is self-balancing? Briefly explain your answer. d) Implement an extension of BST that allows MIN and EXTRACT-MIN operations in O(1). Briefly describe your implementation in the report. Hint:…
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Draw a UML class diagram for the following code: class Node<E> { E data; Node<E> next; public Node(E data) { this.data = data; this.next = null; } } class Queue<E> { Node<E> front; Node<E> rear; public Queue() { front = null; rear = null; } public boolean isEmpty() { return front == null; } public void enqueue(E item) { Node<E> newNode = new Node<E>(item); if (isEmpty()) { front = newNode; rear = newNode; } else { rear.next = newNode; rear = newNode; } } public E dequeue() { if (isEmpty()) { System.out.println("Queue is empty."); return null; } else { E item = front.data; front = front.next; if (front == null) { rear = null; } return item; } } public void dequeueAll() {…
Prolog Depth-first based on the graph search template is not memory efficient because it keeps all active branches while searching for a goal. A more efficient search for graphs looks at one path only and exploits the Prolog built-in backtracking mechanism. Create a file searches.pl and incrementally add to it the following. arc(a, b). arc(a, f). arc(b, c). arc(b, d). arc(b, e). arc(f, g). arc(f, i). arc(i, j). arc(i, k). arc(j, e). arc(j, m). goal(d). goal(i). goal(m). (a) Implement dfs/2 (depth-first search) – this strategy takes a single path 1 as input and then expands that path with a new node until the goal is found, in which case the solution is returned in the second argument. Query your program with: ?- dfs([a], X). for each file in Tests and check you find the right solution.