# First Bad Version
### Source
- lintcode: [(74) First Bad Version](http://www.lintcode.com/en/problem/first-bad-version/)
### Problem
The code base version is an integer start from 1 to n. One day, someonecommitted a bad version in the code case, so it caused this version and thefollowing versions are all failed in the unit tests. Find the first badversion.
You can call `isBadVersion` to help you determine which version is the firstbad one. The details interface can be found in the code's annotation part.
#### Example
Given n = `5`:
~~~
isBadVersion(3) -> false
isBadVersion(5) -> true
isBadVersion(4) -> true
~~~
Here we are 100% sure that the 4th version is the first bad version.
#### Note
Please read the annotation in code area to get the correct way to callisBadVersion in different language. For example, Java is`VersionControl.isBadVersion(v)`
#### Challenge
You should call *isBadVersion* as few as possible.
### 题解
基础算法中 [Binary Search](http://algorithm.yuanbin.me/zh-cn/basics_algorithm/binary_search.html) 的 lower bound. 找出满足条件的下界即可。
### Python
~~~
#class VersionControl:
# @classmethod
# def isBadVersion(cls, id)
# # Run unit tests to check whether verison `id` is a bad version
# # return true if unit tests passed else false.
# You can use VersionControl.isBadVersion(10) to check whether version 10 is a
# bad version.
class Solution:
"""
@param n: An integers.
@return: An integer which is the first bad version.
"""
def findFirstBadVersion(self, n):
lb, ub = 0, n + 1
while lb + 1 < ub:
mid = lb + (ub - lb) / 2
if VersionControl.isBadVersion(mid):
ub = mid
else:
lb = mid
return lb + 1
~~~
### C++
~~~
/**
* class VersionControl {
* public:
* static bool isBadVersion(int k);
* }
* you can use VersionControl::isBadVersion(k) to judge whether
* the kth code version is bad or not.
*/
class Solution {
public:
/**
* @param n: An integers.
* @return: An integer which is the first bad version.
*/
int findFirstBadVersion(int n) {
int lb = 0, ub = n + 1;
while (lb + 1 < ub) {
int mid = lb + (ub - lb) / 2;
if (VersionControl::isBadVersion(mid)) {
ub = mid;
} else {
lb = mid;
}
}
return lb + 1;
}
};
~~~
### Java
~~~
/**
* public class VersionControl {
* public static boolean isBadVersion(int k);
* }
* you can use VersionControl.isBadVersion(k) to judge whether
* the kth code version is bad or not.
*/
class Solution {
/**
* @param n: An integers.
* @return: An integer which is the first bad version.
*/
public int findFirstBadVersion(int n) {
int lb = 0, ub = n + 1;
while (lb + 1 < ub) {
int mid = lb + (ub - lb) / 2;
if (VersionControl.isBadVersion(mid)) {
ub = mid;
} else {
lb = mid;
}
}
return lb + 1;
}
}
~~~
### 源码分析
lower bound 的实现,这里稍微注意下lb 初始化为 0,因为 n 从1开始。ub 和 lb 分别都在什么条件下更新就好了。另外这里并未考虑 `n <= 0` 的情况。
### 复杂度分析
二分搜索,O(logn)O(\log n)O(logn).
- 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