# Insert Interval
### Source
- leetcode: [Insert Interval | LeetCode OJ](https://leetcode.com/problems/insert-interval/)
- lintcode: [(30) Insert Interval](http://www.lintcode.com/en/problem/insert-interval/)
~~~
Given a non-overlapping interval list which is sorted by start point.
Insert a new interval into it,
make sure the list is still in order and non-overlapping
(merge intervals if necessary).
Example
Insert [2, 5] into [[1,2], [5,9]], we get [[1,9]].
Insert [3, 4] into [[1,2], [5,9]], we get [[1,2], [3,4], [5,9]].
~~~
### 題解
這道題看似簡單,但其實實現起來不那么容易,因為若按照常規思路,需要分很多種情況考慮,如半邊相等的情況。以返回新數組為例,首先,遍歷原數組肯定是必須的,以`[N]`代表`newInterval`, `[I]`代表當前遍歷到的`interval`, 那么有以下幾種情況:
1. `[N], [I]` <==> `newInterval.end < interval.start`, 由于 intervals 中的間隔數組已經為升序排列,那么遍歷到的下一個間隔的左邊元素必然也大于新間隔的右邊元素。
1. `[NI]` <==> `newInterval.end == interval.start`,這種情況下需要進行合并操作。
1. `[IN]` <==> `newInterval.start == interval.end`, 這種情況下也需要進行合并。
1. `[I], [N]` <==> `newInterval.start > interval.end`, 這意味著`newInterval`有可能在此處插入,也有可能在其后面的間隔插入。故遍歷時需要在這種情況下做一些標記以確定最終插入位置。
由于間隔都是互不重疊的,故其關系只可能為以上四種中的某幾個。1和4兩種情況很好處理,關鍵在于2和3的處理。由于2和3這種情況都將生成新的間隔,且這種情況一旦發生,**原來的`newInterval`即被新的合并間隔取代,這是一個非常關鍵的突破口。**
### Java
~~~
/**
* Definition of Interval:
* public classs Interval {
* int start, end;
* Interval(int start, int end) {
* this.start = start;
* this.end = end;
* }
*/
class Solution {
/**
* Insert newInterval into intervals.
* @param intervals: Sorted interval list.
* @param newInterval: A new interval.
* @return: A new sorted interval list.
*/
public ArrayList<Interval> insert(ArrayList<Interval> intervals, Interval newInterval) {
ArrayList<Interval> result = new ArrayList<Interval>();
if (intervals == null || intervals.isEmpty()) {
if (newInterval != null) {
result.add(newInterval);
}
return result;
}
int insertPos = 0;
for (Interval interval : intervals) {
if (newInterval.end < interval.start) {
// case 1: [new], [old]
result.add(interval);
} else if (interval.end < newInterval.start) {
// case 2: [old], [new]
result.add(interval);
insertPos++;
} else {
// case 3, 4: [old, new] or [new, old]
newInterval.start = Math.min(newInterval.start, interval.start);
newInterval.end = Math.max(newInterval.end, interval.end);
}
}
result.add(insertPos, newInterval);
return result;
}
}
~~~
### 源碼分析
源碼的精華在case 3 和 case 4的處理,case 2用于確定最終新間隔的插入位置。
之所以不在 case 1立即返回,有兩點考慮:一是代碼的復雜性(需要用到 addAll 添加數組部分元素);二是case2, case3, case 4有可能正好遍歷到數組的最后一個元素,如果在 case 1就返回的話還需要單獨做一判斷。
### 復雜度分析
遍歷一次,時間復雜度 O(n)O(n)O(n). 不考慮作為結果返回占用的空間 result, 空間復雜度 O(1)O(1)O(1).
### Reference
- [Insert Interval 參考程序 Java/C++/Python](http://www.jiuzhang.com/solutions/insert-interval/)
- Preface
- Part I - Basics
- Basics Data Structure
- String
- Linked List
- Binary Tree
- Huffman Compression
- Queue
- Heap
- Stack
- Set
- Map
- Graph
- Basics Sorting
- Bubble Sort
- Selection Sort
- Insertion Sort
- Merge Sort
- Quick Sort
- Heap Sort
- Bucket Sort
- Counting Sort
- Radix Sort
- Basics Algorithm
- Divide and Conquer
- Binary Search
- Math
- Greatest Common Divisor
- Prime
- Knapsack
- Probability
- Shuffle
- Basics Misc
- Bit Manipulation
- Part II - Coding
- String
- strStr
- Two Strings Are Anagrams
- Compare Strings
- Anagrams
- Longest Common Substring
- Rotate String
- Reverse Words in a String
- Valid Palindrome
- Longest Palindromic Substring
- Space Replacement
- Wildcard Matching
- Length of Last Word
- Count and Say
- Integer Array
- Remove Element
- Zero Sum Subarray
- Subarray Sum K
- Subarray Sum Closest
- Recover Rotated Sorted Array
- Product of Array Exclude Itself
- Partition Array
- First Missing Positive
- 2 Sum
- 3 Sum
- 3 Sum Closest
- Remove Duplicates from Sorted Array
- Remove Duplicates from Sorted Array II
- Merge Sorted Array
- Merge Sorted Array II
- Median
- Partition Array by Odd and Even
- Kth Largest Element
- Binary Search
- Binary Search
- Search Insert Position
- Search for a Range
- First Bad Version
- Search a 2D Matrix
- Search a 2D Matrix II
- Find Peak Element
- Search in Rotated Sorted Array
- Search in Rotated Sorted Array II
- Find Minimum in Rotated Sorted Array
- Find Minimum in Rotated Sorted Array II
- Median of two Sorted Arrays
- Sqrt x
- Wood Cut
- Math and Bit Manipulation
- Single Number
- Single Number II
- Single Number III
- O1 Check Power of 2
- Convert Integer A to Integer B
- Factorial Trailing Zeroes
- Unique Binary Search Trees
- Update Bits
- Fast Power
- Hash Function
- Count 1 in Binary
- Fibonacci
- A plus B Problem
- Print Numbers by Recursion
- Majority Number
- Majority Number II
- Majority Number III
- Digit Counts
- Ugly Number
- Plus One
- Linked List
- Remove Duplicates from Sorted List
- Remove Duplicates from Sorted List II
- Remove Duplicates from Unsorted List
- Partition List
- Two Lists Sum
- Two Lists Sum Advanced
- Remove Nth Node From End of List
- Linked List Cycle
- Linked List Cycle II
- Reverse Linked List
- Reverse Linked List II
- Merge Two Sorted Lists
- Merge k Sorted Lists
- Reorder List
- Copy List with Random Pointer
- Sort List
- Insertion Sort List
- Check if a singly linked list is palindrome
- Delete Node in the Middle of Singly Linked List
- Rotate List
- Swap Nodes in Pairs
- Remove Linked List Elements
- Binary Tree
- Binary Tree Preorder Traversal
- Binary Tree Inorder Traversal
- Binary Tree Postorder Traversal
- Binary Tree Level Order Traversal
- Binary Tree Level Order Traversal II
- Maximum Depth of Binary Tree
- Balanced Binary Tree
- Binary Tree Maximum Path Sum
- Lowest Common Ancestor
- Invert Binary Tree
- Diameter of a Binary Tree
- Construct Binary Tree from Preorder and Inorder Traversal
- Construct Binary Tree from Inorder and Postorder Traversal
- Subtree
- Binary Tree Zigzag Level Order Traversal
- Binary Tree Serialization
- Binary Search Tree
- Insert Node in a Binary Search Tree
- Validate Binary Search Tree
- Search Range in Binary Search Tree
- Convert Sorted Array to Binary Search Tree
- Convert Sorted List to Binary Search Tree
- Binary Search Tree Iterator
- Exhaustive Search
- Subsets
- Unique Subsets
- Permutations
- Unique Permutations
- Next Permutation
- Previous Permuation
- Unique Binary Search Trees II
- Permutation Index
- Permutation Index II
- Permutation Sequence
- Palindrome Partitioning
- Combinations
- Combination Sum
- Combination Sum II
- Minimum Depth of Binary Tree
- Word Search
- Dynamic Programming
- Triangle
- Backpack
- Backpack II
- Minimum Path Sum
- Unique Paths
- Unique Paths II
- Climbing Stairs
- Jump Game
- Word Break
- Longest Increasing Subsequence
- Palindrome Partitioning II
- Longest Common Subsequence
- Edit Distance
- Jump Game II
- Best Time to Buy and Sell Stock
- Best Time to Buy and Sell Stock II
- Best Time to Buy and Sell Stock III
- Best Time to Buy and Sell Stock IV
- Distinct Subsequences
- Interleaving String
- Maximum Subarray
- Maximum Subarray II
- Longest Increasing Continuous subsequence
- Longest Increasing Continuous subsequence II
- Graph
- Find the Connected Component in the Undirected Graph
- Route Between Two Nodes in Graph
- Topological Sorting
- Word Ladder
- Bipartial Graph Part I
- Data Structure
- Implement Queue by Two Stacks
- Min Stack
- Sliding Window Maximum
- Longest Words
- Heapify
- Problem Misc
- Nuts and Bolts Problem
- String to Integer
- Insert Interval
- Merge Intervals
- Minimum Subarray
- Matrix Zigzag Traversal
- Valid Sudoku
- Add Binary
- Reverse Integer
- Gray Code
- Find the Missing Number
- Minimum Window Substring
- Continuous Subarray Sum
- Continuous Subarray Sum II
- Longest Consecutive Sequence
- Part III - Contest
- Google APAC
- APAC 2015 Round B
- Problem A. Password Attacker
- Microsoft
- Microsoft 2015 April
- Problem A. Magic Box
- Problem B. Professor Q's Software
- Problem C. Islands Travel
- Problem D. Recruitment
- Microsoft 2015 April 2
- Problem A. Lucky Substrings
- Problem B. Numeric Keypad
- Problem C. Spring Outing
- Microsoft 2015 September 2
- Problem A. Farthest Point
- Appendix I Interview and Resume
- Interview
- Resume