Binary Search Visualizer

Target:

Speed:

SlowFast

Elements:

715

(10)

Mid Point

Boundaries

Target Value

Found

Out of Range

Operation Logs

No operations yet

Algorithm Info

Time Complexity: O(log n) - divides search space in half each iteration

Space Complexity: O(1) - uses constant extra space

Best Case: O(1) - target is the middle element

Worst Case: O(log n) - target is at the ends or not found

Prerequisite: Array must be sorted in ascending order

How it works: Compares target with middle element, then searches either left or right half, eliminating half the elements each time.

When to use: Large sorted datasets where O(log n) performance is crucial.

Implementation

function binarySearch(arr, target) {
  let left = 0;
  let right = arr.length - 1;
  
  while (left <= right) {
    // Find middle point
    const mid = Math.floor((left + right) / 2);
    
    // Check if target is at mid
    if (arr[mid] === target) {
      return mid; // Found!
    }
    
    // If target is greater, ignore left half
    if (arr[mid] < target) {
      left = mid + 1;
    }
    // If target is smaller, ignore right half
    else {
      right = mid - 1;
    }
  }
  
  return -1; // Not found
}