Introduction to Binary Search in Ruby | CodeSignal Learn

Introduction to Binary Search in Ruby | CodeSignal Learn

Introduction to Binary Search

Welcome to today's lesson! We're diving into Binary Search, a clever technique for locating specific elements within a sorted list. By repeatedly dividing the search interval in half, we can efficiently find the targeted item. Think of it as flipping through a dictionary — rather than going page by page, you'd start in the middle, then narrow down the section in half until you find your desired word.

Understanding Binary Search

Binary Search begins at the midpoint of a sorted list, halving the search area at each step until it locates the target. For example, if you are looking for the number 8 in a sorted list ranging from 1 to 10, you would start at 5 . Since 8 is larger than the midpoint, you narrow the search to the second half of the list, leaving you with numbers 6 to 10 . In this new sublist, the middle number is 8, and thus, you've found your target. This efficient approach significantly reduces the number of comparisons needed compared to a linear search.

Coding Binary Search in Ruby

Let's see how Binary Search can be implemented in Ruby, taking a recursive approach. This process involves a function calling itself — with a base case in place to prevent infinite loops — and a recursive case to solve smaller parts of the problem. Ruby def binary_search(arr, start, end_index, target) return -1 if start > end_index # Base case mid = start + (end_index - start) / 2 # Find the midpoint return mid if arr[mid] == target # Target found if arr[mid] > target # If the target is less than the midpoint binary_search(arr, start, mid - 1, target) # Search the left half else binary_search(arr, mid + 1, end_index, target) # Search the right half end end In this Ruby code, the base case is defined first. If the start index is greater than the end_index, it indicates the search area is exhausted, resulting in a -1 return. The code then locates the midpoint. If the midpoint equals our target, it’s returned. Depending on whether the target is less or more than the midpoint, the search continues within the left or right half, respectively.

Analyzing the Time Complexity of Binary Search

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Implementing Binary Search Iteratively

You can also implement the Binary Search algorithm iteratively using a while loop. Here is the Ruby code for the iterative approach. def binary_search_iterative(arr, target) start = 0 end_index = arr.length - 1 while start <= end_index mid = start + (end_index - start) / 2 return mid if arr[mid] == target if arr[mid] < target start = mid + 1 else end_index = mid - 1 end end -1 end Instead of dividing the array recursively, this code uses a while loop, which continues until the start index is equal to or less than the end_index . The middle element is found the same way as in the recursive approach. If the target is equal to this middle element, we have found our target. On the other hand, if the target is greater than the middle element, we adjust the start index to be one position after the middle index. However, if the target is less than the middle element, we adjust the end_index to be one position before the middle index.

Ruby

def binary_search_iterative(arr, target)
  start = 0
  end_index = arr.length - 1

  while start <= end_index
    mid = start + (end_index - start) / 2
    return mid if arr[mid] == target

    if arr[mid] < target
      start = mid + 1
    else
      end_index = mid - 1
    end
  end
  -1
end