Skip to main content

2. Linear Search

in middle | | Worst Case | O(n) | Element at last position or not found | | Space Complexity | O(1) | No extra space needed |

Visualization:

Best Case (1 comparison):
[15, 25, 30, ...] → Found immediately!

Average Case (n/2 comparisons):
[10, 25, 30, 15, ...] → Found in middle

Worst Case (n comparisons):
[10, 25, 30, 40, 35, 15] → Found at end
or
[10, 25, 30, 40, 35, 20] → Not found (checked all)

2.4 Advantages and Disadvantages

Advantages:

  • Simple to implement
  • Works on unsorted arrays
  • No preprocessing required
  • Works well for small datasets
  • No extra memory needed

Disadvantages:

  • Slow for large datasets
  • Inefficient compared to other algorithms
  • Time complexity increases linearly

When to Use:

  • Small datasets (n < 100)
  • Unsorted data
  • When simplicity is priority
  • When data changes frequently
Back to top