Searching Algorithms: Summary
Explore the key differences between linear and binary search algorithms and understand their appropriate use cases. Learn how linear search works on any data and why binary search offers faster lookups on sorted data. Gain insight into the trade-offs and decision criteria for selecting the best search method based on your data structure and performance needs.
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 | Requires sorted data in an indexed structure |
Time complexity | O(n) in the worst case | O(log n) in the worst case |
Space complexity | O(1) |
|
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 |
Quick rule: If the data is unsorted or the collection is very small, Linear Search is usually enough. If the data is sorted and fast lookup matters, Binary Search is the better choice.
Visual comparison: How performance changes as input size grows
The chart below illustrates how the number of comparisons grows for each algorithm as the input size increases.