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(Efficient sorting)
An algorithm is O(n log n) if it processes all elements and does logarithmic work per element. Merge sort and heap sort have this complexity.
This is faster than O(n²) but slower than O(n). For sorting, O(n log n) is optimal for comparison-based algorithms.
Multiplying n by log n gives a growth rate between linear and quadratic.
