The height of a specific node in a tree data structure is the number of edges on the longest path from that node to a leaf node.
Yes a simple exp is the link list. struct node { int data; struct node *link; }
A binary tree is a data structure where each node has at most two children, while a heap is a specialized binary tree with specific ordering properties. In a binary tree, the structure is more flexible and can be balanced or unbalanced, while a heap follows a specific order, such as a min-heap where the parent node is smaller than its children. Functionally, a heap is commonly used for priority queues and efficient sorting algorithms, while a binary tree is more versatile for general tree-based operations.
In a linked list data structure, the head is the starting point that points to the first node in the list. It is significant because it allows for traversal of the list by providing access to the first element, enabling operations such as insertion, deletion, and searching.
The height of a binary search tree is the maximum number of edges from the root node to a leaf node. It represents the longest path from the root to a leaf in the tree.
To determine the height of a binary tree, you can start at the root node and recursively calculate the height of the left and right subtrees. The height of the tree is the maximum height of the left and right subtrees, plus one for the root node. This process continues until you reach the leaf nodes, which have a height of 0.
binary tree is a specific tree data structure where each node can have at most 2 children nodes. In a general Tree data structure nodes can have infinite children nodes.
Traversal simply means moving from one node to the next. Generally one searches by traversing the list, comparing each node's data with a given datum, either to return a pointer to a single matching node, or to return a list of matching nodes (copied from the list being searched), or simply to collect data about the matching nodes (such as a count of all the matching nodes).
A null tree.
It is exactly what it sounds like: a structure which contains a reference to itself. A common occurrence of this is in a structure which describes a node for a linked list. Each node needs a reference to the next node in the chain. struct linked_list_node { int data; struct linked_list_node *next; // <- self reference };
A primary data structure is a data structure that is created without the use of other data structures, whereas a secondary data structure relies on a primary data structure. A data structure is an organized collection of data elements.[NOTE: Be careful not to confuse the term data structure with the term data type. It is a common mistake. This answer addresses dat structures. Often people who ask about primary data structures or primitive data structures are really asking about primitve data types.]Here is an example where an array is a primary data structure and a binary tree is a secondary data structure based on the array:An array is a primary data structure -- it is a set of sequentially numbered data elements, such as an array of integers or an array of names -- name0, name, name2, ...A binary tree is a data structure where each element (called a node) has a data component and pointers to it's left and right sub-trees. [Think of a directory of folders, but each folder can only have two sub-folders.] We can create an and store an array of nodes to set up the tree in languages like C++ or Java.The root of the tree could be node 1 in the array, it would point to nodes 2 and 3. node 2 would point to nodes 4 and 5, while node 3 would point to nodes 6 and 7 .. and so on. generally node n point to nodes 2n and 2n+1. (You can start with node 0, but the math is a little easier if you start with node 1.)The binary tree in this case is the secondary data structure, while the undelying array is the primary data structure.
Heterogeneous Linked List is a linked list data-structure that contains or is capable of storing data for different datatypes.void pointer is basically used in these types of linked list as we are not sure of which type of data needs to be stored
Yes a simple exp is the link list. struct node { int data; struct node *link; }
In a basic decision tree, a leaf node represents a final output or decision based on the input data, while a decision node splits the data based on specific criteria. A node that does not make decisions or lead to further splits, such as an unconnected or isolated point without any branches, is NOT considered a valid node in this format. Essentially, any structure that does not contribute to the decision-making process or data segmentation is not part of a basic decision tree.
A header node, or head node, is a node that marks the start of a series of nodes, usually as part of a list or queue structure. The head node is often a sentinal that holds no data of its own. Sentinels are used to simplify algorithms by ensuring that a list can never be empty, even when it has no data.
Physical data structure: This is the physical equipment involved in the network eg router, cabling etc). Logical data structure: This is how the information flows internally and externally (the transfer of information from one node to another on the network).
A binary tree is a data structure consisting of binary nodes. A binary node is a data structure with two branches, each of which may hold a reference to another binary node. These branches are known as the left and right branches respectively. Since the nodes maintain references to every other node in the tree, it is only necessary to keep track of the root node.
DATA STRUCTURES AS ITS NAME IMPLIES DATA MEANS "VALUE' AND STRUCTURE MEANS THE WAY IT IS ORGANISED AND THE WAY IT IS ARRANGED INTO MATHEMATICAL AND LOGICAL WAY. Just like array...array helps you to store elements without declaring multiples variable eg: num[100] can store 100 variables which are integers. Here if you are not using array and want to store data in 100 variables then you must declare 100 unique variables names. This can be done effectively using data structures.