Binary Search algorithm in Java, Kotlin, Swift, C#, Python3

Binary Search Examples.md

Problem

Given an array of integers nums which is sorted in ascending order, and an integer target, write a function to search target in nums. If target exists, then return its index. Otherwise, return -1.

You must write an algorithm with O(log n) runtime complexity.

Example 1:

Input: nums = [-1,0,3,5,9,12], target = 9
Output: 4
Explanation: 9 exists in nums and its index is 4

Example 2:

Input: nums = [-1,0,3,5,9,12], target = 2
Output: -1
Explanation: 2 does not exist in nums so return -1

Constraints:

• 1 <= nums.length <= 10^4
• -10^4 < nums[i], target < 10^4
• All the integers in nums are unique.
• nums is sorted in ascending order.

binary_search.cs

public class Solution
{
	public static int Search(int[] nums, int target)
	{
		if (nums.Length >= 1)
		{
			int low = 0;
			int high = nums.Length - 1;

			while (low <= high)
			{
				int mid = (low + high) / 2;
				if (nums[mid].Equals(target)) return mid;
				if (nums[mid] < target) low = mid + 1;
				else high = mid - 1;
			}
		}
		return -1;
	}
}

binary_search.java

class Solution {
	int search(int[] nums, int target) {

        if (nums.length >= 1) {
            int low = 0;
            int high = nums.length - 1;

            while (low <= high) {
                int mid = (low + high) / 2;

                if (nums[mid] == target) return mid;
                else if (nums[mid] < target) low = mid + 1;
                else high = mid - 1;
            }
        }

        return -1;
    }
}

binary_search.kt

class Solution {
	
	companion object {
		
		fun search(nums: IntArray, target: Int): Int {

            if (nums.isNotEmpty()) {
                var low = 0
                var high = nums.size - 1

                while (low <= high) {
                    val mid = (low + high) / 2

                    if (nums[mid] == target) return mid
                    else if (nums[mid] < target) low = mid + 1
                    else high = mid - 1
                }
            }

            return -1
        }
	}
}

binary_search.py

class Solution:
	
	@staticmethod
    def search(nums: List[int], target: int) -> int:
        if len(nums) >= 1:
            low, high = 0, len(nums) - 1

            while low <= high:
                mid = (low + high) // 2
                if nums[mid] == target:
                    return mid
                elif nums[mid] < target:
                    low = mid + 1
                else:
                    high = mid - 1

        return -1

binary_search.swift

class Solution {
	
	class func search(_ nums: [Int], _ target: Int) -> Int {
        
        guard !nums.isEmpty else { return -1 }
        
        var low = 0, high = nums.count - 1
        while (low <= high) {
            let mid = (low + high) / 2
            
            if nums[mid] == target { return mid }
            else if nums[mid] < target { low = mid + 1 }
            else { high = mid - 1 }
        }
        
        return -1
    }
}