Grokking Algorithm Complexity and Big-O
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Logarithmic Time and Space: O(log n)
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Logarithmic Time Complexity O(\log n) and Logarithmic Space Complexity O(\log n) occur in algorithms that repeatedly reduce the problem size by a constant factor (often halving). This type of complexity is common in algorithms that use recursive division, such as finding powers or performing binary searches.

Key Characteristics

In an algorithm with O(\log n) time and space complexity:

  • Time Complexity: The runtime grows logarithmically as the input size increases, due to dividing the problem in each step.

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