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Java-based LeetCode algorithm problem solutions, regularly updated
**Time Complexity (Big O Time):**
The time complexity of this program is O(n), where n is the length of the input array `arr`. Here's why:
1. The first loop iterates through the entire array once (`for (int i = 1; i < arr.length; i++)`).
- Inside this loop, there are constant-time operations (assignments and comparisons) for each element of the array.
- Therefore, this part has a time complexity of O(n).
2. The second loop also iterates through the entire array once (`for (int j : arr)`).
- Inside this loop, there are constant-time operations (comparisons) for each element of the array.
- Therefore, this part also has a time complexity of O(n).
In summary, both loops together contribute to the linear time complexity O(n).
**Space Complexity (Big O Space):**
The space complexity of this program is O(1), which means it uses a constant amount of extra space. Regardless of the size of the input array, the program only uses a fixed number of variables (`count` and `majority`) to keep track of the majority element.
In summary, the time complexity is O(n), where n is the length of the input array, and the space complexity is O(1), indicating a constant amount of additional memory usage.