What is the complexity analysis of different searching algorithms?

What is the complexity analysis of different searching algorithms?

The complexity analysis of searching algorithms typically involves evaluating their time and space complexity. For example, linear search has a time complexity of O(n), while binary search has a time complexity of O(log n). Would you like to know more about a specific algorithm?

Can you explain how binary search works?

Sure! Binary search works on sorted arrays. It repeatedly divides the search interval in half. If the target value is less than the middle element, it narrows the interval to the lower half; otherwise, it narrows it to the upper half. This process continues until the target is found or the interval is empty.

What about the space complexity of these algorithms?

The space complexity of linear search is O(1) since it uses a constant amount of space. Binary search also has a space complexity of O(1) for the iterative version, but the recursive version has a space complexity of O(log n) due to the call stack.

Are there any other searching algorithms I should know about?

Yes, there are several other searching algorithms, such as interpolation search, exponential search, and jump search. Each has its own use cases and complexities. Would you like details on any specific one?