Merge Sort is a classic divide-and-conquer algorithm used to sort elements efficiently. It works by recursively splitting the array into smaller subarrays, sorting them, and then merging the sorted subarrays back together.
⚡ Key Concepts
- Divide: Split the array into two halves.
- Conquer: Recursively sort each half.
- Combine: Merge the sorted halves into a single sorted array.
📊 Time Complexity
- Best Case: ⌦(n log n)
- Average Case: ⌦(n log n)
- Worst Case: ⌦(n log n)
🧠 Why Use Merge Sort?
- Stable sorting algorithm (preserves the order of equal elements)
- Efficient for large datasets
- Works well with linked lists
📌 Step-by-Step Example
- Split the array into individual elements.
- Merge pairs of elements by comparing and combining them.
- Repeat the merge process until the entire array is sorted.
🧩 Practical Applications
- Sorting large datasets in databases
- External sorting for files that don’t fit in memory
- Implementing in programming languages like Python or Java
For a deeper dive into algorithm analysis, check our guide on Big O Notation. 📚