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Understanding Time Complexity and Space Complexity
- Time complexity measures how the runtime of an algorithm increases as the input size grows.
- Space complexity measures how much memory an algorithm needs in relation to the input size.
- Examples such as O(1) and O(n) illustrate constant and linear time/space complexity.
- Understanding these complexities helps optimize code for efficiency and scalability.
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