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

    Example:

    1. Input: s = 7, nums = [2,3,1,2,4,3]
    2. Output: 2
    3. Explanation: the subarray [4,3] has the minimal length under the problem constraint.

    Follow up:

    If you have figured out the O(n) solution, try coding another solution of which the time complexity is O(n log n).


    题意

    给定一个正整数s和一个正整数数组nums,要求在nums中找到一个最短的连续子序列,使其和大于等于s。

    思路

    滑动窗口法(Two Pointers):连续子数组问题很容易想到使用滑动窗口来解题。用left和right分别指向窗口的左端点和右端点,如果当前窗口内的整数和小于s,则将右端点右移来拉长窗口;如果当前窗口内的整数和大于等于s,判断其长度是否比当前结果小,是则记录,并将左端点右移来缩短窗口。重复以上步骤就能得到一个长度最短且整数和大于等于s的窗口。最坏情况下左右端点都走了一遍数组,所以时间复杂度为209. Minimum Size Subarray Sum (M) - 图1%3DO(N)#card=math&code=O%282N%29%3DO%28N%29&height=20&width=112)。

    二分查找:新建sum数组,209. Minimum Size Subarray Sum (M) - 图2,则问题转化为在数组sum中求一个连续子数组,使其末首之差大于等于s。从左向右遍历,每次固定左端点i,在右半边子数组中利用二分法找到值大于等于209. Minimum Size Subarray Sum (M) - 图3的元素sum[j],判断长度并记录。时间复杂度为209. Minimum Size Subarray Sum (M) - 图4%0A#card=math&code=O%28NlogN%29%0A&height=20&width=77)。


    代码实现 - 滑动窗口1

    1. class Solution {
    2. public int minSubArrayLen(int s, int[] nums) {
    3. if (nums.length == 0) {
    4. return 0;
    5. }
    6. int ans = 0;
    7. int left = 0, right = 0;
    8. int sum = nums[0];
    9. while (right < nums.length) {
    10. if (sum < s && right < nums.length - 1) {
    11. sum += nums[++right];
    12. } else if (sum >= s) {
    13. ans = ans == 0 ? right - left + 1 : Math.min(ans, right - left + 1);
    14. sum -= nums[left++];
    15. } else {
    16. break; // 当右端点已经在数组的末尾且sum仍比s小时,可以直接跳出
    17. }
    18. }
    19. return ans;
    20. }
    21. }

    代码实现 - 滑动窗口2

    1. class Solution {
    2. public int minSubArrayLen(int s, int[] nums) {
    3. int ans = Integer.MAX_VALUE;
    4. int sum = 0;
    5. int left = 0;
    6. for (int right = 0; right < nums.length; right++) {
    7. sum += nums[right];
    8. while (sum >= s) {
    9. ans = Math.min(ans, right - left + 1);
    10. sum -= nums[left++];
    11. }
    12. }
    13. return ans == Integer.MAX_VALUE ? 0 : ans;
    14. }
    15. }

    代码实现 - 二分查找

    1. class Solution {
    2. public int minSubArrayLen(int s, int[] nums) {
    3. if (nums.length == 0) {
    4. return 0;
    5. }
    6. int ans = Integer.MAX_VALUE;
    7. int[] sum = new int[nums.length];
    8. for (int i = 0; i < nums.length; i++) {
    9. sum[i] = i == 0 ? nums[i] : sum[i - 1] + nums[i];
    10. // 先处理掉特殊情况
    11. if (sum[i] >= s) {
    12. ans = Math.min(ans, i + 1);
    13. }
    14. }
    15. // 二分查找符合条件的点
    16. for (int i = 0; i < nums.length; i++) {
    17. int target = s + sum[i];
    18. int left = i + 1, right = nums.length - 1;
    19. while (left < right) {
    20. int mid = (right - left) / 2 + left;
    21. if (sum[mid] < target) {
    22. left = mid + 1;
    23. } else {
    24. ans = Math.min(ans, mid - i);
    25. right = mid;
    26. }
    27. }
    28. if (sum[right] >= target) {
    29. ans = Math.min(ans, right - i);
    30. }
    31. }
    32. return ans == Integer.MAX_VALUE ? 0 : ans;
    33. }
    34. }