Question

Fill in the blanks in each of the following: a. A self-_____ class is used to form dynamic data structures that can grow and shrink at execution time b. The _____ operator is used to dynamically allocate memory and construct an object; this operator returns a pointer to the object. c. A(n)_____ is a constrained version of a linked list in which nodes can be inserted and deleted only from the start of the list and node values are returned in last-in, first-out order. d. A function that does not alter a linked list, but looks at the list to determine whether it is empty, is an example of a(n)_____ function. e. A queue is referred to as a(n)_____ data structure, because the first mnodes inserted are the first nodes removed. f. The pointer to the next node in a linked list is referred to as a(n) _____. g. The _____ operator is used to destroy an object and release dynamically allocated memory. h. A(n)_____ is a constrained version of a linked list in which nodes can be inserted only at the end of the list and deleted only from the start of the list. i. A(n) _____ is a nonlinear, two-dimensional data structure that contains nodes with two or more links. j. A stack is referred to as a(n)_____ data structure, because the last node inserted is the first node removed. k. The nodes of a(n)_____ tree contain two link members. l. The first node of a tree is the _____ node. m. Each link in a tree node points to a(n) _____ or _____ of that node. n. A tree node that has no children is called a(n) _____ node. o. The four traversal algorithms we mentioned in the text for binary search trees are _____, _____, _____ and ______.

Short answer

The completed blanks are: a) Self-Referential, b) new, c) Stack, d) Predicate, e) FIFO, f) Link, g) delete, h) Queue, i) Tree, j) LIFO, k) Binary, l) Root, m) Child or Subtree, n) Leaf, o) Inorder, Preorder, Postorder, Level-order.

Step-by-step solution

Recognize Self-Defined Class

The blank space for 'a' pertains to a class known for working with dynamic structures. Answer: Self-Referential

Identify Memory Allocation Operator

In 'b', the term refers to allocation of memory for object construction. Answer: new

Constrained Linked List Type

A 'c' refers to a structure where elements follow a Last-In-First-Out order. Answer: Stack

Function Type that Checks List

For 'd', the function checks, but does not change, the list. Answer: Predicate

Queue Characteristic

In 'e', the structure processes elements in a First-In-First-Out manner. Answer: FIFO

Node Link in List

For 'f', this pointer directs to the subsequent node in a list. Answer: Link

Memory Deallocation Operator

The term in 'g' is an operator responsible for releasing memory. Answer: delete

Constrained List Type

In 'h', this structure only permits insertion at one end and removal at the other. Answer: Queue

Description of a Tree Structure

For 'i', this describes a data structure with nodes having multiple links. Answer: Tree

Stack Data Structure Type

The 'j' describes a Last-In-First-Out structure. Answer: LIFO

Tree with Two Links

In 'k', each node contains two link members. Answer: Binary

Initial Tree Node

The 'l' term refers to the start node of a tree. Answer: Root

Tree Node Links

In 'm', the links reference a node's Offspring. Answer: Child or Subtree

Tree Node Without Children

For 'n', such a node is characterized by having no descendants. Answer: Leaf

Binary Tree Traversal Methods

The 'o' response includes specific strategies for traversing a tree. Answer: Inorder, Preorder, Postorder, Level-order

Key concepts

Dynamic Data Structures

Dynamic data structures are a pivotal concept in C++ programming. They allow a program to manage data efficiently during runtime by growing and shrinking as needed. Unlike static data structures, such as arrays, that need a predefined size, dynamic data structures can expand or contract, offering flexibility.

This adaptability is achieved using self-referential classes. These are classes whose objects, or instances, contain references to other objects of the same class. This characteristic enables the creation of complex and changing structures like linked lists or binary trees that better manage storage in applications where data size changes unpredictably.

An example of this is a stack, a constrained linked list, where items are added and removed in a last-in, first-out (LIFO) manner. Similarly, a queue allows insertion at the end and deletion from the front, following a first-in, first-out (FIFO) order.

Memory Management in C++

Proper memory management in C++ is crucial to prevent resource leaks and ensure efficient application performance. This is done through dynamic memory allocation and deallocation. Memory is allocated with the `new` operator, which constructs an object or array, and returns a pointer to the newly allocated memory.

Once the memory's purpose is complete, the `delete` operator is employed to deallocate it. This releases the memory back to the system, avoiding memory leaks which could degrade performance.

Efficient memory handling requires careful tracking of allocated memory, especially in large-scale applications. C++ provides tools such as smart pointers in the Standard Library to automate some aspects of memory management, minimizing the risk of leaks and errors. Properly understanding and applying these principles and tools enables the development of robust, efficient C++ applications.

Linked Lists

Linked lists are a fundamental dynamic data structure composed of nodes connected via pointers. Each node typically contains data and a pointer to the next node, forming a chain. This structure allows for efficient insertion and deletion, unlike arrays which require elements to be shifted.

There are variations of linked lists, such as singly linked lists, where each node points to the next; doubly linked lists, with nodes that point both to the next and previous nodes; and circular linked lists, where the last node links back to the first, creating a circle.

A significant aspect of linked lists is traversal. A methodical approach is required to navigate through the nodes, often utilizing a `current` pointer to iterate from the head to the desired element or position. Employing linked lists effectively requires an understanding of these traversal methods and other list operations like insertion and deletion.

Binary Trees

Binary trees are a type of dynamic data structure that organizes data in a hierarchical manner. Each tree node contains a value and two pointers: left and right. The top node is known as the root, and nodes without children are called leaf nodes.

Binary trees are efficient for various operations such as searching, insertion, and deletion because they allow data to be quickly navigated using comparisons, reducing the need for sequential checks.

There are several traversal algorithms for binary trees, which define the order in which nodes are visited. These include inorder traversal (left subtree, root, right subtree), preorder traversal (root, left subtree, right subtree), postorder traversal (left subtree, right subtree, root), and level-order traversal (visits nodes level by level from root to leaves).

Understanding these traversal techniques, along with the general structure and operation of binary trees, is essential for leveraging their efficiency and power in problem-solving and application development.