Heap Sort is a powerful and efficient sorting algorithm that uses a binary heap data structure to sort elements. Unlike simpler algorithms like Bubble Sort or Insertion Sort, Heap Sort guarantees a time complexity of O(n log n), making it suitable for large datasets. This makes it a valuable tool for Rust programmers who want […]
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Quick Sort is one of the most popular and efficient sorting algorithms used in programming. It follows the divide-and-conquer principle, which means it breaks the problem into smaller subproblems, solves them independently, and combines the results. Unlike simpler algorithms like Bubble Sort or Insertion Sort, Quick Sort is faster on average, especially for large datasets,
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Insertion Sort is a simple and intuitive sorting algorithm that works similarly to how people often sort playing cards in their hands. The algorithm builds a sorted portion of the array one element at a time by taking each element and inserting it into its correct position among the already sorted elements. It’s easy to
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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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Bubble Sort is one of the simplest sorting algorithms that every beginner should learn. It works by repeatedly comparing adjacent elements in an array and swapping them if they are in the wrong order. The largest elements “bubble up” to the end of the array with each pass, which is why it is called Bubble
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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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Breadth-First Search, or BFS, is a key algorithm used to traverse graphs or tree-like structures. Unlike Depth-First Search, which explores deeply before backtracking, BFS explores all neighbors of a node before moving to the next level. This makes BFS especially useful in finding the shortest path in unweighted graphs, level order traversal, and exploring networks.
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Depth-First Search, commonly known as DFS, is a fundamental graph traversal algorithm. It explores a graph by going as deep as possible along each branch before backtracking. DFS is widely used in areas like pathfinding, cycle detection, solving puzzles, and exploring networks. Understanding DFS helps beginners grasp the basic concepts of recursion, graph representation, and
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Exponential Search is a powerful search algorithm that combines the strengths of linear and binary search. It is designed for sorted arrays and starts by finding a range where the target element may exist, exponentially increasing the index at each step. Once the potential range is located, it performs a Binary Search to find the
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Fibonacci Search is a unique search algorithm that uses Fibonacci numbers to divide a sorted array into sections and find a target element. Unlike Binary Search, which splits the array in half, Fibonacci Search divides the array based on Fibonacci numbers, which can provide better performance in certain cases, especially when accessing elements is costly.
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