Logic Visualizer | Python

Binary Search Algorithm Visual

This visual representation explains the logic and flow of the binary search algorithm, which is used to search for a specific element in a sorted array. The code snippet illustrates how the algorithm divides the array into smaller subarrays and


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Prompt

def binary_search(arr, low, high, x):
    while low <= high:
        mid = (low + high) // 2
        
        if arr[mid] == x:
            return mid
        
        elif arr[mid] < x:
            low = mid + 1
        
        else:
            high = mid - 1
    
    return -1

Answer

Visual Representation: Binary Search Algorithm

def binary_search(arr, low, high, x):
    while low <= high:
        mid = (low + high) // 2
        
        if arr[mid] == x:
            return mid
        
        elif arr[mid] < x:
            low = mid + 1
        
        else:
            high = mid - 1
    
    return -1

The above code represents the binary search algorithm, which is used to search for a specific element x in a sorted array arr. Here is a step-by-step breakdown of the logic behind the code:

  1. Input Parameters: The function binary_search takes in four parameters: arr (the sorted array to be searched), low (the lower index of the array to search in), high (the higher index of the array to search in), and x (the element to be searched for).

  2. While Loop: The code uses a while loop that continues until low becomes greater than high.

  3. Midpoint Calculation: At each iteration of the loop, the code calculates the mid point by finding the average of low and high and then performing integer division using // operator.

  4. Element Comparison: The code checks if the element at index mid in the array arr matches the target element x. If it does, the function returns the index mid, indicating that the element has been found.

  5. Divide and Conquer: If the element at index mid is less than x, it means the target element x is present in the right half of the array. In this case, the low pointer is updated to mid + 1 to search in the right subarray.

  6. Shifting Indices: If the element at index mid is greater than x, it means the target element x is present in the left half of the array. In this case, the high pointer is updated to mid - 1 to search in the left subarray.

  7. Element Not Found: If the loop completes without finding the target element, the function returns -1, indicating that the element was not found in the array.

By visually representing the binary search algorithm, it becomes easier to comprehend the flow of logic and the decision-making process involved in finding the target element in a sorted array.

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Description

This visual representation explains the logic and flow of the binary search algorithm, which is used to search for a specific element in a sorted array. The code snippet illustrates how the algorithm divides the array into smaller subarrays and uses comparisons to efficiently find the target element. Understanding the binary search algorithm is crucial for efficient search operations on sorted data.