- insert algorithms 
- find index algorithms

- bulit in sort method
- string sort method

- by using recursive implement fibonacci
- by using recursive implement binary_search algorithms

- Time Complexity

- Space Complexity

- Average Time Complexity

- Worst-case Time Complexity

- Bio-O Notation
examples)
> O(logn) - Size and log Proportion of Input : binary search algorithms.
> O(n) - Size and Proportion of Input : linear search algorithms.
> O(nlogn) - Merge sort algorithms.
> O(n2) - insert sort algoritms.

1. Node
2. LinkedList

1. getAt() - certain element reference
2. traverse() - list traversal
3. getLenth()- get lenth
4. insertAt(pos, newNode) - insert element
5. popAt(pos) - delete element
6. concat(L) - merge list to list

Methods

1. push(x) - Insert data element at last index
2. pop() - Return & delete data element at last index
3. is_Empty() - Check Stack (boolean)
4. peek() - Return data element at last index

Stack Application Examples.

1. Convet infix notation to postfix notation

2. Calculate postfix notation

Methods

1. enqueue(x) - Insert data element at last index
2. dequeue() - Return & delete data element at first index
3. is_Empty() - Check Stack (boolean)
4. peek() - Return data element at first index
5. size() - Check how to many data counts
6. isFull() - Check to data is full

Stack Application Examples.

1. CircularQueue
2. PriorityQueue

1. nodes - edges
2. root node - internal node - leaf node
3. parents node - childs node
4. Level of node
5. Degree of node
6. depth(height) of tree
7. subtrees

size()- node counts

depth() - depth of tree

traversal() - tree traversal

1. in-order Traversl

order : left subtree -> self -> right subtree

1. pre-order traversal

order : self -> left subtree -> right subtree

1. post-order traversal

order : left subtree -> right subtree -> self

1. Breadth first traversal

1. binary trees

• Level of all nodes is lower below 2.
• Can define recursive.

1. full binary trees

• Filled with nodes at all level
• Height = k, nodes = 2**k -1

1. complete binary trees

• Height = k
• Up to level k - 2, all nodes is full binary tree with two children
• At level k - 1, a binary tree with nodes sequentially filled from the left

1. init() - Create empty heap
2. insert(item) - Insert new data item
3. remove() - Max data(root node) return & remove
4. maxHeapify() - Use recursive algorithms to remove data

node number : m

1. left child number : 2 * m
2. right child number : 2 * m + 1
3. parent node number : m /// 2

1. Prioirity Queue
2. Heap Sort