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Java-based LeetCode algorithm problem solutions, regularly updated
**Time Complexity (Big O Time):**
1. The program uses a single loop that iterates through the elements of the `nums` array. Let's assume there are 'n' elements in the array.
2. In each iteration of the loop, the program performs constant time operations such as subtraction, comparison, and taking the maximum value.
3. The loop iterates until the end of the array or until it determines that it's not possible to jump further.
4. In the worst case, the loop may iterate through all 'n' elements of the array.
5. Therefore, the 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.
2. The program uses a few integer variables (`sz` and `tmp`) to keep track of the array size and the jump value. These variables require constant space.
3. The space complexity does not depend on the size of the input array `nums`.
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`. The program efficiently checks if it's possible to jump to the end of the array using a single pass through the array.