Searching Algorithms: Summary
Explore the fundamental concepts of searching algorithms in Go by understanding the differences between linear and binary search. Learn when to apply each method based on data sorting and size, and grasp the impact of these algorithms on performance as input grows. This lesson helps you decide the right search approach to efficiently locate targets within data collections.
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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., slices, arrays) | Requires sorted data in an indexed structure (e.g., slices, arrays) |
Time complexity | O(n) in the worst case | O(log n) in the worst case |
Space complexity | O(1) |
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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 just a single for loop | Slightly more complex; uses variables such as low, high, and mid |