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Sorting is arranging data in a particular order (ascending or descending). It's like organizing books on a shelf alphabetically — you put them in order so they're easier to find.
Why Sort?
- Searching: Binary search requires sorted data
- Display: Show data in order (newest first, alphabetical, etc.)
- Analysis: Easier to find patterns in sorted data
- Efficiency: Some algorithms work better on sorted data
Common Sorting Algorithms:
- Bubble Sort: Simple but slow (O(n²))
- Quick Sort: Fast average case (O(n log n))
- Merge Sort: Consistent performance (O(n log n))
- Heap Sort: Good worst case (O(n log n))
- Insertion Sort: Fast for small arrays (O(n²))
Choosing an Algorithm:
- Small data: Any algorithm works
- Large data: Need O(n log n) algorithms
- Stability: Some algorithms preserve relative order of equal elements
- Memory: Some algorithms use extra space, others sort in-place
FAQ
What's the fastest sorting algorithm?
For general-purpose sorting, Quick Sort or Merge Sort (both O(n log n)). The best choice depends on your data and constraints.
Why not always use the fastest algorithm?
Sometimes simpler algorithms are better for small data, or you need stability, or memory constraints matter.