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AI Features

Searching Algorithms: Summary

Explore key searching algorithms in this lesson by learning how linear search works for any dataset, while binary search requires sorted data but offers faster lookups. Understand when to apply each method based on data structure and performance needs to improve your problem-solving skills.

Having studied both search algorithms, the table below summarizes their key differences.

Feature

Linear Search

Binary Search

Data requirement

Works on ordered or unordered collections (e.g., arrays, lists)

Requires sorted data in an indexed structure (e.g., arrays, lists)

Time complexity

O(n) in the worst case

O(log n) in the worst case

Space complexity

O(1)

  • O(1) iterative

  • O(log n) recursive

How it works

Checks elements one by one from start to end

Repeatedly divides the search space in half

Best for

Small collections, unsorted data, single lookups

Large sorted collections, repeated lookups

Implementation

Simpler often has a single loop

Slightly more complex, uses variables such as low, high, and mid

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