Merge Sort Visualizer
Watch how Merge Sort uses divide-and-conquer to split the array into halves and merge them back in sorted order.
Time: O(n log n)
Space: O(n)
Stable: Yes
Divide & Conquer
Fast (500ms)Slow (3000ms)
Progress: Step 1 of 0Level 0 of 0 | Phase: start
640
341
252
123
224
115
906
Unsorted
Left Section
Right Section
Left Pointer
Right Pointer
Merging
Sorted
Current Step:
Click Start to begin the Merge Sort visualization
Algorithm Details
Best Case:
O(n log n)Average Case:
O(n log n)Worst Case:
O(n log n)Space:
O(n)Stable:Yes
In-place:No
When to Use Merge Sort
- ✓Large datasets requiring guaranteed O(n log n)
- ✓When stability is required
- ✓External sorting (data doesn't fit in memory)
- ✓Parallel processing applications
- ✗Memory-constrained environments
Real-world Applications
- •Database sorting operations
- •External sorting of large files
- •Parallel computing algorithms
- •Version control systems (like Git)
- •Inversion count problems