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Interpolation Search - Technical Overview

1. Algorithm Description: Interpolation Search improves upon binary search for uniformly distributed data by estimating the position of the target value.

2. Steps of Interpolation Search:

• Start with low and high indices.
• Estimate the position of the target based on the values at low and high.
• If the target is found at the estimated position, return the index.
• If the target is less than the value at the estimated position, search the left half; otherwise, search the right half.

3. Time Complexity: O(log log n) on average, O(n) in the worst case when data is not uniformly distributed.

4. Space Complexity: O(1), as it operates in-place.

5. Stability: Interpolation Search is not a stable search algorithm.

6. Usage: Useful for searching in large, uniformly distributed datasets.