Binary search is a highly efficient algorithm for finding an item in a sorted array or list. In this article, we will explore the recursive implementation of the binary search algorithm in Java. We'll begin by understanding the problem, followed by the original code, a stepbystep explanation, and practical examples.
Understanding the Problem
Binary search works by repeatedly dividing the search interval in half. If the value of the search key is less than the item in the middle of the interval, the search continues in the lower half. Otherwise, it continues in the upper half. The algorithm requires that the list be sorted prior to searching.
Here’s a simple implementation of recursive binary search in Java:
public class BinarySearch {
// Recursive binary search function
public static int binarySearch(int[] arr, int left, int right, int target) {
if (right >= left) {
int mid = left + (right  left) / 2;
// Check if the target is present at mid
if (arr[mid] == target) {
return mid;
}
// If target is smaller than mid, then search the left subarray
if (arr[mid] > target) {
return binarySearch(arr, left, mid  1, target);
}
// If target is greater than mid, then search the right subarray
return binarySearch(arr, mid + 1, right, target);
}
// Target is not present in the array
return 1;
}
public static void main(String[] args) {
int[] arr = {2, 3, 4, 10, 40};
int target = 10;
int result = binarySearch(arr, 0, arr.length  1, target);
if (result == 1) {
System.out.println("Element not found");
} else {
System.out.println("Element found at index: " + result);
}
}
}
Analyzing the Code

Function Definition: The
binarySearch
function takes four parameters:arr
: the sorted array to search through.left
: the starting index of the array/subarray.right
: the ending index of the array/subarray.target
: the element we are searching for.

Base Case: The recursion stops when the
right
index is less than theleft
index, which means the target is not found. In this case, it returns 1. 
Finding the Middle Index: The middle index (
mid
) is calculated. If the target matches the value atmid
, the index is returned. 
Recursive Calls: If the target is less than the value at
mid
, the function calls itself to search in the left half (left
tomid  1
). If greater, it searches in the right half (mid + 1
toright
). 
Main Method: The
main
method initializes a sample sorted array and specifies a target number to search for. It prints the result, indicating whether the element was found or not.
Practical Example
Let’s take an example of searching for the number 10
in the array {2, 3, 4, 10, 40}
. The binarySearch
function will:
 Calculate
mid
as index 2 (value4
).  Since
10
is greater than4
, it calls itself for the right subarray{10, 40}
.  Recalculate
mid
as index 3 (value10
), successfully finding the target at index3
.
Advantages of Recursive Binary Search
 Simplicity: The recursive approach is often more straightforward and easier to understand than its iterative counterpart.
 Less Code: Recursive functions generally require fewer lines of code.
 Functional Style: It aligns well with functional programming paradigms.
Conclusion
Recursive binary search is a powerful technique in computer science, especially for sorted datasets. By following the principles of divide and conquer, it provides an efficient way to locate values within a collection.
Additional Resources
 GeeksforGeeks  Binary Search  A comprehensive guide on binary search, including iterative and recursive implementations.
 Java Documentation  Official documentation for Java programming, which can help enhance your skills.
Whether you are a beginner or looking to refine your skills, understanding recursive binary search can greatly aid you in various programming tasks involving sorted data.