LeetCode—Minimum Size Subarray Sum

本文探讨了给定正整数数组及目标值s的情况下,如何找到满足和≥s的最短子数组长度的问题。提供了两种解决方案,一种是采用双重循环遍历的方法实现,时间复杂度为O(n^2),另一种则利用滑动窗口技术,将复杂度降低至O(n)。

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题目:

Given an array ofnpositive integers and a positive integers, find the minimal length of a subarray of which the sum ≥s. If there isn't one, return 0 instead.

For example, given the array[2,3,1,2,4,3]ands = 7,
the subarray[4,3]has the minimal length under the problem constraint.

代码1:遍历,复杂度O(n^2)

int min(int x,int y)
{
    return x<y?x:y;
}
int minSubArrayLen(int s, int* nums, int numsSize)
{
    int minlen = 100000;
    int count = 0;
    int i;
    int j;
    for(i = 0;i < numsSize;i ++)
    {
            count+=nums[i];
    }
    if(count<s)
    return 0;
    count = 0;
    for(i = 0;i<numsSize;i++)
    {
            count = 0;
            for(j = i;j>=0;j--)
            {
                count += nums[j];
                if(s <= count)
                {
                   minlen = min(minlen,i-j+1);
                   break;
                }
            }
    }    
    return minlen;
}
C代码2:滑动窗口,复杂度O(n)

int minSubArrayLen(int s, int* nums, int numsSize)
{
    int minlen = 100000;
    int left  = 0;
    int right = 0;
    int sum = 0;
    while (right <= numsSize) 
     {
        if (sum >= s) 
            sum -= nums[left++];
        else 
            sum += nums[right++];
        if (right - left < minlen && sum >= s)
            minlen = right - left;
        if(right == numsSize && sum < s)
            break;
     }
     return minlen == 100000 ? 0 : minlen;
}
复杂度为O(n*logn)的没想出来,thinking。。。

### LeetCode Top 100 Popular Problems LeetCode provides an extensive collection of algorithmic challenges designed to help developers prepare for technical interviews and enhance their problem-solving skills. The platform categorizes these problems based on popularity, difficulty level, and frequency asked during tech interviews. The following list represents a curated selection of the most frequently practiced 100 problems from LeetCode: #### Array & String Manipulation 1. Two Sum[^2] 2. Add Two Numbers (Linked List)[^2] 3. Longest Substring Without Repeating Characters #### Dynamic Programming 4. Climbing Stairs 5. Coin Change 6. House Robber #### Depth-First Search (DFS) / Breadth-First Search (BFS) 7. Binary Tree Level Order Traversal[^3] 8. Surrounded Regions 9. Number of Islands #### Backtracking 10. Combination Sum 11. Subsets 12. Permutations #### Greedy Algorithms 13. Jump Game 14. Gas Station 15. Task Scheduler #### Sliding Window Technique 16. Minimum Size Subarray Sum 17. Longest Repeating Character Replacement #### Bit Manipulation 18. Single Number[^1] 19. Maximum Product of Word Lengths 20. Reverse Bits This list continues up until reaching approximately 100 items covering various categories including but not limited to Trees, Graphs, Sorting, Searching, Math, Design Patterns, etc.. Each category contains multiple representative questions that cover fundamental concepts as well as advanced techniques required by leading technology companies when conducting software engineering candidate assessments. For those interested in improving logical thinking through gaming activities outside traditional study methods, certain types of video games have been shown beneficial effects similar to engaging directly within competitive coding platforms [^4]. --related questions-- 1. How does participating in online coding competitions benefit personal development? 2. What specific advantages do DFS/BFS algorithms offer compared to other traversal strategies? 3. Can you provide examples illustrating how bit manipulation improves performance efficiency? 4. In what ways might regular participation in programming contests influence job interview success rates? 5. Are there any notable differences between solving problems on paper versus implementing solutions programmatically?
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