Algorithms - Sort Techniques | Merge Sort.

📌 Merge Sort | Sorting Techniques Explained (Top-Down & Bottom-Up)

In this video, we explain Merge Sort, one of the most efficient and widely used sorting algorithms in computer science.
You’ll learn how merge sort works using both Top-Down (Recursive) and Bottom-Up (Iterative) approaches, how arrays are divided and merged, and why merge sort is preferred for large datasets.

🔹 Topics covered in this video:
• What is Merge Sort?
• Top-Down Merge Sort (recursive approach)
• Bottom-Up Merge Sort (iterative approach)
• Step-by-step merging process
• Time complexity analysis
• Best, average, and worst case scenarios
• When to use Merge Sort in real-world applications

🔹 Key Points:
• Divide and Conquer algorithm
• Consistent performance regardless of input order
• Efficient for large datasets
• Stable sorting algorithm
• Not in-place (requires extra memory)

📊 Time Complexity (Both Approaches):
• Best Case: O(n log n)
• Average Case: O(n log n)
• Worst Case: O(n log n)

📦 Space Complexity:
• O(n)

🔍 Top-Down vs Bottom-Up:
• Top-Down Merge Sort: Uses recursion to divide the array until single elements, then merges them back.
• Bottom-Up Merge Sort: Uses iteration to merge subarrays starting from size 1, avoiding recursion.

This video is perfect for students, beginners, and interview preparation, especially if you’re studying Data Structures & Algorithms and want to understand efficient sorting techniques in depth.

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