【LeetCode】53. Maximum Subarray (2 solutions)
Maximum Subarray
Find the contiguous subarray within an array (containing at least one number) which has the largest sum.
For example, given the array [−2,1,−3,4,−1,2,1,−5,4], the contiguous subarray [4,−1,2,1] has the largest sum = 6.
解法一:
如果当前子串和小于等于0,则归零重新开始累加。记录最大子串和。
注意:ret需要初始化为INT_MIN(以防所有都为负)。
因此需要定义为long long类型。以防INT_MIN加上一个负数溢出。
class Solution {
public:
int maxSubArray(int A[], int n) {
long long ret = INT_MIN;
long long cur = INT_MIN;
for(int i = ; i < n; i ++)
{
if(cur + A[i] > A[i])
cur += A[i];
else
cur = A[i];
ret = max(ret, cur);
}
return ret;
}
};

或者初始化为第一个值
class Solution {
public:
int maxSubArray(vector<int>& nums) {
int ret = nums[];
int cur = nums[];
for(int i = ; i < nums.size(); i ++)
{
cur = max(nums[i], cur+nums[i]);
ret = max(ret, cur);
}
return ret;
}
};

解法二:分治法。将数组分成两段A1,A2之后,就分解成为子问题了:
1、最大子串在A1中;
2、最大子串在A2中;
3、最大子串是A1后缀+A2前缀。
class Solution {
public:
int maxSubArray(int A[], int n) {
if(n == )
return A[];
else
{
int mid = n/;
//divide into [0~mid-1], [mid~n-1]
int ret1 = maxSubArray(A, mid);
int ret2 = maxSubArray(A+mid, n-mid);
int left = mid-;
int ret3_1 = A[mid-];
int temp = A[mid-];
left --;
while(left >= )
{
temp += A[left];
ret3_1 = max(ret3_1, temp);
left --;
}
int right = mid;
int ret3_2 = A[mid];
temp = A[mid];
right ++;
while(right < n)
{
temp += A[right];
ret3_2 = max(ret3_2, temp);
right ++;
}
return max(max(ret1, ret2), ret3_1+ret3_2);
}
}
};

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