UNI EDUCATION PRESENTATION

01

Non-lineardata structures

non-linear Data Structure

• A non-linear data structure is type in which data elements are not arranged sequentially; mainly, data elements are arranged in random order without forming a linear structure.
• Data elements are present at the multilevel, for example, tree and graphs.
• The non-linear data structure cannot be implemented directly, and it is implemented using the linear data structure like an array and linked list.

• The tree is a non-linear data structure that is comprised of various nodes. The nodes in the tree data structure are arranged in hierarchical order.
• It consists of a root node corresponding to its various child nodes, present at the next level. The tree grows on a level basis, and root nodes have limited child nodes depending on the order of the tree.
• For example, in the binary tree, the order of the root node is 2, which means it can have at most 2 children per node, not more than it

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tree

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Terminologies used in tree

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• Root node: The tree consists of a root node; it is the starting node of the tree from which any tree grows. The root node is present at level 0 in any tree.
• Child node: The child node is the node that comes after the root node, which has a parent node and has some ancestors. It is the node present at the next level of its parent node.
• Edge: Edges are nothing but the link between the parent node, and the children node is called the link or edge connectivity between two nodes.
• Siblings: The nodes having the same parent node is called siblings of each other.
• Leaf node: The leaf node is the node that does not have any child nodes. It is the termination point of any tree. It is also known as External nodes.

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graphs

• A Graph is a non-linear data structure consisting of vertices and edges.
• The vertices are sometimes also referred to as nodes and the edges are lines or arcs that connect any two nodes in the graph. More formally a Graph is composed of a set of vertices( V ) and a set of edges( E ). The graph is denoted by G(E, V).
• Vertices: Vertices are the fundamental units of the graph. Sometimes, vertices are also known as vertex or nodes. Every node/vertex can be labeled or unlabelled.
• Edges: Edges are drawn or used to connect two nodes of the graph.Edges can connect any two nodes in any possible way.

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One node is connected with another node with an edge in a graph. The graph is a non-linear data structure consisting of nodes and edges and is represented by G ( V, E ), where V stahe set of vertices and E stands for the set of edges. The g

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classification of graphs

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Unweighted Graph

• Where there is no value or weight associated with the edge.

Weighted Graph

• Graphs whose edges or paths have values. All the values seen associated with the edges are called weights. Edges value can represent weight/cost/length.
• Ex: To look for that shortest path to the office, the distance between two workstations in an office network.

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Directed graphs

• Also called a digraph
• where a set of nodes are or vertices connected together with each otherand edges have a direction from one vertex to another.

Undirected graphs

• It is set of nodes or vertices which are connected with no direction.

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