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Java-based LeetCode algorithm problem solutions, regularly updated
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**Time Complexity (Big O Time):**
1. The program uses a single loop that iterates through the elements of the `nums` array from left to right.
2. In each iteration, it performs constant time operations such as arithmetic, comparisons, and calls to `Math.max`. These operations do not depend on the size of the input array.
3. The loop runs until the second-to-last element of the array (i.e., `i < nums.length - 1`), so the number of iterations is at most `n - 1`, where `n` is the number of elements in the input array.
4. Therefore, the overall time complexity of the program is O(n), where `n` is the number of elements in the input array `nums`.
**Space Complexity (Big O Space):**
1. The space complexity of the program is O(1), which means it uses a constant amount of additional space regardless of the size of the input array `nums`. The program only uses a few integer variables (`length`, `maxLength`, `minJump`, and `i`) and does not use any additional data structures or memory that scales with the input size.
In summary, the time complexity of the provided program is O(n), and the space complexity is O(1), where `n` is the number of elements in the input array `nums`.
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