LeetCode #53 Maximum Subarray

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Description


 

Find the contiguous subarray within an array (containing at least one number) which has the largest sum.

 Input 

[-2,1,-3,4,-1,2,1,-5,4]
 Output  

6 //the contiguous subarray [4,-1,2,1] has the largest sum = 6.

 

 

思路


  

  CLRS 第四章练习题 4.1-5,动态规划 5 mins 过,时间复杂度 O(n) 。

  未优化空间的版本:

class Solution {
public:
    int maxSubArray(vector<int>& nums) {
        // dp[i] is a state representing max contiguous sum where
        // the last element is A[i]
        vector<int> dp;
        dp.reserve(nums.size());
        dp.push_back(nums[0]);
        int subarray_max_sum = dp[0];
        
        for (int i = 1; i < nums.size(); ++i) {
            dp[i] = max(dp[i-1] + nums[i], nums[i]);
            if (subarray_max_sum < dp[i]) {
                subarray_max_sum = dp[i];
            }
        }
        
        return subarray_max_sum;
    }
};

 

  优化空间的版本:

class Solution {
public:
    int maxSubArray(vector<int>& nums) {
        int dp, sum;
        dp = nums[0];
        sum = nums[0];
        for (int i = 1; i < nums.size(); i++) {
            if (dp > 0) {
                dp += nums[i];
            }
            else dp = nums[i];
            if (dp > sum)
                sum = dp;
        }
        return sum;
    }
};

 

  用分治法再做了一遍。它的思路是: A[low..high] 的连续子数组A[i..j]的位置必然是下面三种情况之一:

  1.完全位于子数组 A[low..mid] 中,low <= i <= j <= mid

  2.完全位于子数组 A[mid+1..high] 中,mid+1 <= i <= j <= high

  3.跨越了中点 mid ,low <= i <= mid < j <= high

  前两个情况仍是最大子数组问题,只不过规模更小,所以可以递归求解。而最后一种情况加入了中点的限制,不易递归求解,所以线性扫描。

  算法时间复杂度是 O(n·lgn)

  

#include <iostream>
#include <limits.h>
#include <vector>
using namespace std;

class Solution {
public:
    int maxSubArray(vector<int>& nums) {
        int res = findMaxSubarray (nums, 0, nums.size()-1);
        nums.clear();
        vector<int>().swap(nums);
        return res;
    }
private:
    int findMaxSubarray (vector<int>& nums, const int& low, const int& high) {        
        if (low == high) return nums[low]; //base case: only one element
        else { 
            int mid =low + (high-low)/2;
            int left_sum = findMaxSubarray (nums, low, mid);
            int right_sum = findMaxSubarray (nums, mid + 1, high);
            int cross_sum = findMaxCrossingSubarray (nums, low, high);
            // chose the max case of them
            if (left_sum >= right_sum && left_sum >= cross_sum)
                return left_sum;
            else if (right_sum >= left_sum && right_sum >= cross_sum)
                return right_sum;
            else 
                return cross_sum;
        }
    }
    
    int findMaxCrossingSubarray (vector<int>& nums, const int& low, const int& high) {
        int left_sum = INT_MIN;
        int sum = 0;
        int mid = low + (high-low)/2;
        for (int i = mid; i >= low; --i) {
            sum += nums[i];
            if (left_sum < sum) 
                left_sum = sum;
        }
        
        int right_sum = INT_MIN;
        sum = 0;
        for (int i = mid+1; i <= high; ++i) {
            sum += nums[i];
            if (right_sum < sum)
                right_sum = sum;
        }
        return left_sum + right_sum;
    }
};

 

  

最后一点是经验之谈。用递归的话写起来很舒服,但是 BUG 不好改,出错的一般都是 segment fault (core dump) 。我发现了一种很好的办法去解决这种问题,由于每次发生段错误系统会产生 .core 文件记录发生的位置,所以我们在 gdb 调试时候把它带上就知道导致段错误的位置在哪、出错的数据是多少了。我的是 Ubuntu 系统,不像 Redhat 可以直接产生 core 文件,所以要先输入 ulimit -c unlimited 打开生成 core 文件的选项。举个例子,如下:

 

 

 

 

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