Basic terminology Unit in data structures
- 1. BASIC TERMINOLOGY Dr R Tamilselvi Associate Professor&Head, Department of AI&DS/IT, VET Institute of Arts and Science College.
- 2. BASIC TERMINOLOGY ◦ In linear data structure data is organized in sequential order and in non-linear data structure data is organized in random order. A tree is a very popular non- linear data structure used in a wide range of applications. ◦ Tree is a non-linear data structure which organizes data in hierarchical structure and this is a recursive definition. ◦ In tree data structure, every individual element is called as Node. Node in a tree data structure stores the actual data of that particular element and link to next element in hierarchical structure. ◦ In a tree data structure, if we have N number of nodes then we can have a maximum of N- 1 number of links.
- 3. Terminology: ◦In a tree data structure, we use the following terminology 1. Root 2. Edge 3. Parent 4. Child 5. Siblings 6. Leaf 7. Internal Nodes 8. Degree 9. Level 10.Height 11.Depth 12.Path 13.Sub Tree
- 4. Root In a tree data structure, the first node is called as Root Node. Every tree must have a root node. We can say that the root node is the origin of the tree data structure. In any tree, there must be only one root node. We never have multiple root nodes in a tree. Edge In a tree data structure, the connecting link between any two nodes is called as EDGE. In a tree with 'N' number of nodes there will be a maximum of 'N-1' number of edges.
- 5. Parent In a tree data structure, the node which is a predecessor of any node is called as PARENT NODE. In simple words, the node which has a branch from it to any other node is called a parent node. Parent node can also be defined as "The node which has child / children". Child In a tree data structure, the node which is descendant of any node is called as CHILD Node. In simple words, the node which has a link from its parent node is called as child node. In a tree, any parent node can have any number of child nodes. In a tree, all the nodes except root are child nodes.
- 6. Siblings In a tree data structure, nodes which belong to same Parent are called as SIBLINGS. In simple words. Leaf In a tree data Structure, the node which does not have a child is called as LEAF. , the leaf nodes are also called as External Nodes. External node is also a node with no child. In a tree, leaf node is also called as 'Terminal' node.
- 7. Internal Nodes In a tree data structure, the node which has at least one child is called as INTERNAL Node. The root node is also said to be Internal Node if the tree has more than one node. Internal nodes are also called as 'Non- Terminal' nodes. Degree In a tree data structure, the total number of children of a node is called as DEGREE of that Node. The highest degree of a node among all the nodes in a tree is called as 'Degree of Tree'
- 8. Level In a tree data structure, the root node is said to be at Level 0 and the children of root node are at Level 1 and the children of the nodes which are at Level 1 will be at Level 2 and so on... In simple words, in a tree each step from top to bottom is called as a Level and the Level count starts with '0' and incremented by one at each level (Step). Height In a tree data structure, the total number of edges from leaf node to a particular node in the longest path is called as HEIGHT of that Node. In a tree, height of the root node is said to be height of the tree. In a tree, height of all leaf nodes is '0’.
- 9. Depth In a tree data structure, the total number of edges from root node to a particular node is called as DEPTH of that Node. In simple words, the highest depth of any leaf node in a tree is said to be depth of that tree. In a tree, depth of the root node is '0’. Path In a tree data structure, the sequence of Nodes and Edges from one node to another node is called as PATH between that two Nodes. Length of a Path is total number of nodes in that path. In below example the path A - B - E - J has length 4.
- 10. Sub Tree In a tree data structure, each child from a node forms a subtree recursively. Every child node will form a subtree on its parent node.
- 11. THANK YOU