style: Apply proper Java formatting to BinarySearch

- Fixed line length to meet style guidelines
- Applied proper JavaDoc formatting
- Corrected indentation and spacing
- Ensured compliance with project formatting standards

Author: ghorpadeire

src/main/java/com/thealgorithms/searches/BinarySearch.java

@@ -4,38 +4,32 @@
 
 /**
  * Binary Search Algorithm Implementation
- * 
- * Binary search is one of the most efficient searching algorithms for finding a target 
- * element in a SORTED array. It works by repeatedly dividing the search space in half,
- * eliminating half of the remaining elements in each step.
- * 
- * IMPORTANT: This algorithm ONLY works correctly if the input array is sorted 
- * in ascending order.
- * 
- * Algorithm Overview:
- * 1. Start with the entire array (left = 0, right = array.length - 1)
- * 2. Calculate the middle index
- * 3. Compare the middle element with the target:
- *    - If middle element equals target: Found! Return the index
- *    - If middle element is less than target: Search the right half
- *    - If middle element is greater than target: Search the left half
- * 4. Repeat until element is found or search space is exhausted
- * 
- * Performance Analysis:
- * - Best-case time complexity: O(1) - Element found at middle on first try
- * - Average-case time complexity: O(log n) - Most common scenario
- * - Worst-case time complexity: O(log n) - Element not found or at extreme end
- * - Space complexity: O(1) - Only uses a constant amount of extra space
- * 
- * Example Walkthrough:
- * Array: [1, 3, 5, 7, 9, 11, 13, 15, 17, 19]
- * Target: 7
- * 
- * Step 1: left=0, right=9, mid=4, array[4]=9 (9 > 7, search left half)
- * Step 2: left=0, right=3, mid=1, array[1]=3 (3 < 7, search right half)
- * Step 3: left=2, right=3, mid=2, array[2]=5 (5 < 7, search right half)
- * Step 4: left=3, right=3, mid=3, array[3]=7 (Found! Return index 3)
- * 
+ *
+ * <p>Binary search is one of the most efficient searching algorithms for finding a target element
+ * in a SORTED array. It works by repeatedly dividing the search space in half, eliminating half of
+ * the remaining elements in each step.
+ *
+ * <p>IMPORTANT: This algorithm ONLY works correctly if the input array is sorted in ascending
+ * order.
+ *
+ * <p>Algorithm Overview: 1. Start with the entire array (left = 0, right = array.length - 1) 2.
+ * Calculate the middle index 3. Compare the middle element with the target: - If middle element
+ * equals target: Found! Return the index - If middle element is less than target: Search the right
+ * half - If middle element is greater than target: Search the left half 4. Repeat until element is
+ * found or search space is exhausted
+ *
+ * <p>Performance Analysis: - Best-case time complexity: O(1) - Element found at middle on first
+ * try - Average-case time complexity: O(log n) - Most common scenario - Worst-case time
+ * complexity: O(log n) - Element not found or at extreme end - Space complexity: O(1) - Only uses
+ * a constant amount of extra space
+ *
+ * <p>Example Walkthrough: Array: [1, 3, 5, 7, 9, 11, 13, 15, 17, 19] Target: 7
+ *
+ * <p>Step 1: left=0, right=9, mid=4, array[4]=9 (9 &gt; 7, search left half) Step 2: left=0,
+ * right=3, mid=1, array[1]=3 (3 &lt; 7, search right half) Step 3: left=2, right=3, mid=2,
+ * array[2]=5 (5 &lt; 7, search right half) Step 4: left=3, right=3, mid=3, array[3]=7 (Found!
+ * Return index 3)
+ *
  * @author Varun Upadhyay (https://github.com/varunu28)
  * @author Podshivalov Nikita (https://github.com/nikitap492)
  * @see SearchAlgorithm
@@ -44,22 +38,20 @@
 class BinarySearch implements SearchAlgorithm {
 
     /**
-     * Generic method to perform binary search on any comparable type.
-     * This is the main entry point for binary search operations.
-     * 
+     * Generic method to perform binary search on any comparable type. This is the main entry point
+     * for binary search operations.
+     *
      * @param <T> The type of elements in the array (must be Comparable)
      * @param array The sorted array to search in (MUST be sorted in ascending order)
      * @param key The element to search for
      * @return The index of the key if found, -1 if not found
-     * 
      * @throws NullPointerException if array is null
-     * 
-     * Example Usage:
-     * <pre>
+     *     <p>Example Usage:
+     *     <pre>
      * Integer[] numbers = {1, 3, 5, 7, 9, 11};
      * int result = BinarySearch.find(numbers, 7);
      * // result will be 3 (index of element 7)
-     * 
+     *
      * int notFound = BinarySearch.find(numbers, 4);
      * // notFound will be -1 (element 4 does not exist)
      * </pre>
@@ -70,30 +62,27 @@ public <T extends Comparable<T>> int find(T[] array, T key) {
         if (array == null || array.length == 0) {
             return -1;
         }
-        
+
         // Delegate to the core search implementation
         return search(array, key, 0, array.length - 1);
     }
 
     /**
-     * Core recursive implementation of binary search algorithm.
-     * This method divides the problem into smaller subproblems recursively.
-     * 
-     * How it works:
-     * 1. Calculate the middle index to avoid integer overflow
-     * 2. Check if middle element matches the target
-     * 3. If not, recursively search either left or right half
-     * 4. Base case: left > right means element not found
-     * 
+     * Core recursive implementation of binary search algorithm. This method divides the problem
+     * into smaller subproblems recursively.
+     *
+     * <p>How it works: 1. Calculate the middle index to avoid integer overflow 2. Check if middle
+     * element matches the target 3. If not, recursively search either left or right half 4. Base
+     * case: left &gt; right means element not found
+     *
      * @param <T> The type of elements (must be Comparable)
      * @param array The sorted array to search in
      * @param key The element we're looking for
      * @param left The leftmost index of current search range (inclusive)
      * @param right The rightmost index of current search range (inclusive)
      * @return The index where key is located, or -1 if not found
-     * 
-     * Time Complexity: O(log n) because we halve the search space each time
-     * Space Complexity: O(log n) due to recursive call stack
+     *     <p>Time Complexity: O(log n) because we halve the search space each time Space
+     *     Complexity: O(log n) due to recursive call stack
      */
     private <T extends Comparable<T>> int search(T[] array, T key, int left, int right) {
         // Base case: Search space is exhausted
@@ -107,21 +96,21 @@ private <T extends Comparable<T>> int search(T[] array, T key, int left, int rig
         // So we use: left + (right - left) / 2 which is mathematically equivalent
         // but prevents overflow
         int median = (left + right) >>> 1; // Unsigned right shift is faster division by 2
-        
+
         // Get the value at middle position for comparison
         int comp = key.compareTo(array[median]);
 
         // Case 1: Found the target element at middle position
         if (comp == 0) {
             return median; // Return the index where element was found
-        } 
+        }
         // Case 2: Target is smaller than middle element
         // This means if target exists, it must be in the LEFT half
         else if (comp < 0) {
             // Recursively search the left half
             // New search range: [left, median - 1]
             return search(array, key, left, median - 1);
-        } 
+        }
         // Case 3: Target is greater than middle element
         // This means if target exists, it must be in the RIGHT half
         else {
@@ -130,4 +119,4 @@ else if (comp < 0) {
             return search(array, key, median + 1, right);
         }
     }
-}
+}