Merge Sort is a highly efficient sorting algorithm that excels in handling large datasets and maintaining the original order of elements. It utilizes a divide-and-conquer approach, breaking down an array into sub-arrays and merging them in sorted order. Its time complexity of O(n log n) makes it a reliable choice for sorting, especially in applications like database management and e-commerce, where data volume and stability are critical.
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Merge Sort is a sorting algorithm that uses the divide and conquer method to efficiently sort arrays
Breaking down an array into smaller sub-arrays
Merge Sort divides an array into smaller sub-arrays to make sorting more manageable
Merging sub-arrays in sorted order
After sorting the sub-arrays, Merge Sort merges them in a sorted order
Merge Sort has a time complexity of O(n log n) and is stable, meaning identical elements maintain their relative positions after sorting
Merge Sort's time complexity of O(n log n) is more efficient than simpler algorithms like Bubble Sort and Insertion Sort
Merge Sort requires more memory due to its use of sub-arrays
The choice of sorting algorithm depends on factors such as dataset size and the need to preserve the order of elements
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Definition of Time Complexity
Metric for algorithm efficiency; measures relationship between input size and execution time.
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Merge Sort Time Complexity
O(n log n); due to logarithmic operations per element, leading to n log n total operations.
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Merge Sort Performance Consistency
Time complexity remains O(n log n) in all cases, including pre-sorted arrays.
