Sorting Algorithms

Rust Program to Implement Merge Sort

Rust Program to Implement Merge Sort

Merge Sort is a powerful and efficient sorting algorithm that uses the divide-and-conquer approach to sort arrays. Unlike simple algorithms like Insertion or Bubble Sort, Merge Sort splits the array into smaller parts, sorts them individually, and then merges the sorted parts back together. This approach ensures a consistent performance, making it suitable for larger

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Rust Program to Implement Selection Sort

Rust Program to Implement Selection Sort

Selection Sort is a fundamental sorting algorithm that helps beginners understand how to organize data step by step. Unlike Bubble Sort, which repeatedly swaps adjacent elements, Selection Sort finds the smallest element in the array and places it in its correct position. It then repeats this process for the remaining elements until the entire array

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Scala Program to Implement Tim Sort

Scala Program to Implement Tim Sort

Tim Sort is a modern and highly efficient sorting algorithm that combines the best features of Merge Sort and Insertion Sort. It was originally designed for real-world data that often contains partially ordered sequences, making it faster than traditional algorithms in many practical scenarios. Tim Sort works by breaking the array into small sections called

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Scala Program to Implement Counting Sort

Scala Program to Implement Counting Sort

Counting Sort is a simple yet powerful sorting algorithm that works differently from comparison-based methods like Quick Sort or Merge Sort. Instead of comparing elements, it counts the number of occurrences of each element and uses this information to place elements in their correct position. This approach makes Counting Sort extremely fast for sorting integers

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Scala Program to Implement Shell Sort

Scala Program to Implement Shell Sort

Shell Sort is a fascinating sorting algorithm that bridges the gap between simple algorithms like Insertion Sort and more advanced ones like Quick Sort. It works by first comparing elements far apart and gradually reducing the gap between them, which allows the algorithm to move values closer to their final position faster. This approach reduces

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