Algorithm and data structure
  • Algorithm and data structure
  • Break Away: Programming And Coding Interviews & Cracking coding interview
    • System design and scalability
    • Performance and Complexity
    • Big O Notation
    • Sorting trade-off
    • Selection sort
    • Bubble sort
    • Insertion sort
    • Shell sort
    • Merge sort
    • Quick sort
    • Binary search
    • Recursion
    • Binary tree
    • Breadth First Traversal
    • Depth First Pre-Order
    • Binary search tree
    • Stack
    • Queue
    • Linked list
    • Doubly linked list
    • String
    • Pointer and array
    • Bit manipulation
    • General programming problems
    • Priority queue
    • Balanced binary search tree
    • Binary heap
    • Heap sort
    • Graphs
    • Topological sort
  • Leetcode
    • 1. Two Sum
    • 2. Add Two Numbers
    • 3. Longest Substring Without Repeating Characters
    • 4. Median of Two Sorted Arrays
    • 5. Longest Palindromic Substring
    • 6.ZigZag Conversion
    • 7. Reverse Integer
    • 8. String to Integer (atoi)
    • 9. Palindrome Number
    • 11. Container With Most Water
    • 12. Integer to Roman
    • 13. Roman to Integer
    • 14. Longest Common Prefix
    • 15. 3Sum
    • 16. 3Sum Closest
    • 17. Letter Combinations of a Phone Number
    • 18. 4Sum
    • 19. Remove Nth Node From End of List
    • 20. Valid Parentheses
    • 21. Merge Two Sorted Lists
    • 22. Generate Parentheses
    • 23. Merge k Sorted Lists
    • 24. Swap Nodes in Pairs
    • 25. Reverse Nodes in k-Group
    • 26. Remove Duplicates from Sorted Array
    • 27. Remove Element
    • 28. Implement strStr()
    • 29. Divide Two Integers
    • 30. Substring with Concatenation of All Words
    • 31. Next Permutation
    • 32. Longest Valid Parentheses
    • 33. Search in Rotated Sorted Array
    • 34. Find First and Last Position of Element in Sorted Array
    • 35. Search Insert Position (Easy)
    • 36. Valid Sudoku
    • 37. Sudoku Solver
    • 38. Count and Say
    • 39. Combination Sum
    • 40. Combination Sum II
    • 41. First Missing Positive
    • 43. Multiply Strings
    • 45. Jump Game II
    • 46. Permutations (Medium)
    • 47. Permutations II (Medium)
    • 48. Rotate Image
    • 49. Group Anagrams
    • 50. Pow(x, n)
    • 51. N-Queens
    • 52. N-Queens II
    • 53. Maximum Subarray
    • 54. Spiral Matrix
    • 55. Jump Game
    • 56. Merge Intervals
    • 57. Insert Interval
    • 58. Length of Last Word
    • 59. Spiral Matrix II
    • 61. Rotate List
    • 62. Unique Paths
    • 63. Unique Paths II
    • 64. Minimum Path Sum
    • 66. Plus One
    • 67. Add Binary
    • 69. Sqrt(x)
    • 70. Climbing Stairs
    • 73. Set Matrix Zeroes
    • 74. Search a 2D Matrix
    • 75. Sort Colors
    • 76. Minimum Window Substring
    • 77. Combinations
    • 78. Subsets
    • 79. Word Search
    • 80. Remove Duplicates from Sorted Array II
    • 81. Search in Rotated Sorted Array II
    • 82. Remove Duplicates from Sorted List II
    • 83. Remove Duplicates from Sorted List
    • 84. Largest Rectangle in Histogram
    • 86. Partition List
    • 88. Merge Sorted Array
    • 89. Gray Code
    • 90. Subsets II
    • 92. Reverse Linked List II
    • 94. Binary Tree Inorder Traversal (Medium)
    • 95. Unique Binary Search Trees II
    • 96. Unique Binary Search Trees
    • 98. Validate Binary Search Tree
    • 100. Same Tree (Easy)
    • 101. Symmetric Tree
    • 102. Binary Tree Level Order Traversal
    • 103. Binary Tree Zigzag Level Order Traversal
    • 104. Maximum Depth of Binary Tree
    • 105. Construct Binary Tree from Preorder and Inorder Traversal
    • 106. Construct Binary Tree from Inorder and Postorder Traversal
    • 107. Binary Tree Level Order Traversal II (Easy)
    • 108. Convert Sorted Array to Binary Search Tree
    • 109. Convert Sorted List to Binary Search Tree
    • 110. Balanced Binary Tree
    • 111. Minimum Depth of Binary Tree
    • 112. Path Sum
    • 113. Path Sum II
    • 114. Flatten Binary Tree to Linked List
    • 116. Populating Next Right Pointers in Each Node
    • 117. Populating Next Right Pointers in Each Node IIㄟˋ大
    • 118. Pascal's Triangle
    • 119. Pascal's Triangle II
    • 120. Triangle
    • 121. Best Time to Buy and Sell Stock
    • 122. Best Time to Buy and Sell Stock II
    • 123. Best Time to Buy and Sell Stock III
    • 125. Valid Palindrome
    • 654. Maximum Binary Tree
    • 127. Word Ladder
    • 129. Sum Root to Leaf Numbers
    • 130. Surrounded Regions (Medium)
    • 131. Palindrome Partitioning
    • 133. Clone Graph
    • 134. Gas Station
    • 136. Single Number
    • 137. Single Number II
    • 138. Copy List with Random Pointer
    • 139. Word Break
    • 141. Linked List Cycle
    • 143. Reorder List
    • 144. Binary Tree Preorder Traversal
    • 145. Binary Tree Postorder Traversal
    • 147. Insertion Sort List
    • 148. Sort List
    • 151. Reverse Words in a String
    • 152. Maximum Product Subarray
    • 153. Find Minimum in Rotated Sorted Array
    • 154. Find Minimum in Rotated Sorted Array II
    • 155. Min Stack
    • 160. Intersection of Two Linked Lists
    • 164. Maximum Gap
    • 169. Majority Element (Easy)
    • 173. Binary Search Tree Iterator
    • 174. Dungeon Game (Hard)
    • 189. Rotate Array
    • 198. House Robber (Easy)
    • 199. Binary Tree Right Side View (Medium)
    • 203. Remove Linked List Elements
    • 206. Reverse Linked List
    • 213. House Robber II (Medium)
    • 215. Kth Largest Element in an Array (Medium)
    • 222. Count Complete Tree Nodes
    • 226. Invert Binary Tree
    • 230. Kth Smallest Element in a BST
    • 232. Implement Queue using Stacks
    • 234. Palindrome Linked List (Easy)
    • 235. Lowest Common Ancestor of a Binary Search Tree
    • 236. Lowest Common Ancestor of a Binary Tree
    • 237. Delete Node in a Linked List
    • 240. Search a 2D Matrix II
    • 242. Valid Anagram
    • 257. Binary Tree Paths
    • 283. Move Zeroes
    • 337. House Robber III (Medium)
    • 347. Top K Frequent Elements
    • 349. Intersection of Two Arrays
    • 409. Longest Palindrome (Easy)
    • 437. Path Sum III
    • 442. Find All Duplicates in an Array
    • 449. Serialize and Deserialize BST
    • 450. Delete Node in a BST
    • 543. Diameter of Binary Tree
    • 572. Subtree of Another Tree
    • 653. Two Sum IV - Input is a BST
    • 654. Maximum Binary Tree
    • 700. Search in a Binary Search Tree
    • 701. Insert into a Binary Search Tree
    • 783. Minimum Distance Between BST Nodes
    • 876.Middle of the Linked List
    • 942. DI String Match
  • Notes of algorithms
    • Binary Tree traversal
    • 廣度優先搜尋 (Breadth-first Search)
    • Divide and Conquer
    • Linked list: Insert Node
    • Dynamic programming
    • 深度優先搜尋 (Depth-first Search)
    • Lowest Common Ancestor (LCA)
    • Asymptotic notation
    • Binary search tree
    • AVL Tree (Height Balanced BST)
    • Linked list: Split the list
    • Linked list: Traverse the list
    • Linked list: Delete node
    • Heap sort
    • Cartesian tree
  • C++
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On this page
  • 1.Insertion sort
  • 2.Procedures
  • 3.Example code (Java)
  • 4.Complexity
  • 5.Insertion sort v.s bubble sort
  1. Break Away: Programming And Coding Interviews & Cracking coding interview

Insertion sort

1.Insertion sort

  • Start with a sorted sub-list of size 1

  • Insert the next element into the sorted sub-list at the time right position. Now the sorted sub-list has 2 elements.

  • By inserting into a sorted sub-list at every step the sub-list soon grows to be the entire list

  • 將每一個元素與右邊的元素比較, 一旦右邊的比較小, 則開始swap (跟bubble sort很像)

2.Procedures

  • Insertion sort first assumes a sorted list of size 1 and inserts additional elements in the right position

3.Example code (Java)

  • Insertion method

public static void insertionSort(int[] listToSort) {
    //Go up to the second to last element
    for (int i = 0; i < listToSort.length - 1; i++) {
        //Consider everything uptil the ith element sorted
        //Bubble the element element outside the sorted sub-list to the right position
        for (int j = i + 1; j > 0; j--) {
            if (listToSort[j] < listToSort[j - 1]) {
                swap(listToSort, j, j - 1);
            } else {
                //If no swap was performed the element has been moved to the right position so break out the loop
                break;
            }
        }
        print(listToSort);
    }
}
  • Swap

    public static void swap(int[] listToSort, int iIndex, int jIndex) {
        int temp = listToSort[iIndex];
        listToSort[iIndex] = listToSort[jIndex];
        listToSort[jIndex] = temp;
    }

4.Complexity

  • Complexity of Bubble sort is O(N^2)

  • Checking "N" elements for each of "N" selected elements

  • It's adaptive sort

  • It takes O(1) extra space, it sorts in space (No extra space)

    • 因為用原本的list儲存 (in-place 演算法)

  • It is a stable sort:

    • As entities bubble to the correct position in the sub-list that is sorted. The list the original order of entities are maintained for equal elements.

  • It makes O(N^2) comparisons and O(N^2) swaps (與Bubble sort相同)

    • 比較複雜度是O(N^2)

    • 交換次數是O(N^2)

5.Insertion sort v.s bubble sort

  1. Bubble sort requires an additional pass over all elements to ensure that the list is fully sorted.

  2. Bubble sort has to do "N" comparisons at every step. Insertion sort can stop comparison elements when the right position in the sorted list is found.

  3. Bubble sort performs poorly with modern hardware because of the number of writes and swaps that it performs. Results in cache misses so has greater overhead than insertion sort.

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Last updated 6 years ago