LeetCode 2875: Minimum Size Subarray in Infinite Array Solution
Master LeetCode problem 2875 (Minimum Size Subarray in Infinite Array), a medium challenge, with our optimized solutions in Java, C++, and Python. Explore detailed explanations, test your code in our interactive editor, and prepare for coding interviews.
2875. Minimum Size Subarray in Infinite Array
Problem Explanation
Explanation:
To solve this problem, we can use a sliding window approach. We will maintain two pointers start and end that represent the current window. We will keep expanding the window by incrementing the end pointer until the sum of elements within the window is less than or equal to the target. Once the sum exceeds the target, we will increment the start pointer to shrink the window while keeping track of the minimum window length found so far.
Algorithmic Idea:
- Initialize
startandendpointers to 0. - Iterate over the array using the
endpointer, expanding the window and updating the sum. - While the sum is greater than or equal to the target, update the minimum window length and increment the
startpointer to shrink the window. - Repeat steps 2 and 3 until the end of the array.
- Return the minimum window length if found, otherwise return -1.
Time Complexity:
The time complexity of this algorithm is O(n) where n is the number of elements in the input array.
Space Complexity:
The space complexity of this algorithm is O(1) as we are using a constant amount of extra space.
Solution Code
public int minSubArrayLen(int target, int[] nums) {
int n = nums.length;
int start = 0, end = 0, sum = 0, minLen = Integer.MAX_VALUE;
for (; end < n; end++) {
sum += nums[end];
while (sum >= target) {
minLen = Math.min(minLen, end - start + 1);
sum -= nums[start];
start++;
}
}
return minLen == Integer.MAX_VALUE ? -1 : minLen;
}Try It Yourself
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