Searching Algorithms: Summary
Explore the fundamentals of searching algorithms by understanding how linear and binary searches operate, their performance trade-offs, and when to apply each method based on data characteristics. Gain insight into choosing the right search to efficiently locate elements within 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., arrays, List<T>) | Requires sorted data in an indexed structure (e.g., arrays, List<T>) |
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 | Simple; often just a single loop | Slightly more complex; uses variables such as low, high, and mid |