Merge Sort Time Complexity

Merge Sort Time Complexity

Blog Article

Sorting algorithms play a crucial role in computer science, affecting performance across countless applications. Among them, merge sort stands out for its consistent performance and divide-and-conquer approach. It splits the array into halves, sorts them, and merges the results efficiently. While its space usage might be higher than in-place sorts, it offers predictable behavior even with large datasets. Understanding merge sort time complexity is essential for choosing the right algorithm—it operates in O(n log n) time in the best, worst, and average cases, making it reliable and scalable.