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Undergraduate Programming Assignment Help

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Implementation of Binary Search Algorithm in Python

def binary_search(arr, target): low = 0 high = len(arr) - 1 while low <= high: mid = (low + high) // 2 if arr[mid] == target: return mid elif arr[mid] < target: low = mid + 1 else: high = mid - 1 return -1 # Example usage arr = [1, 3, 5, 7, 9, 11, 13, 15] target = 7 result = binary_search(arr, target) if result != -1: print(f"Element found at index {result}") else: print("Element not found")

Binary search is an efficient algorithm for finding a target value within a sorted array. It works by repeatedly dividing the search interval in half, which makes it significantly faster than linear search for large datasets. This efficiency helps students understand how algorithms can optimize performance in real-world applications.

By implementing binary search, students learn about algorithmic complexity. Binary search has a time complexity of O(log n), which demonstrates how algorithm efficiency improves with better design.

Learning binary search introduces students to the concept of divide-and-conquer algorithms. It provides a solid foundation for understanding more complex algorithms and data structures used in computer science.

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