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feat: refactored docs structure
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---
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title: '704. Binary Search'
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description: 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
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icon: dot
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topics:
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- { name: "Array", slug: "array" }
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- { name: "Binary Search", slug: "binary-search" }
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video: "s4DPM8ct1pI"
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issue: "https://github.com/prdlk/leetcode/issues/58"
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sidebar:
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label: 'Binary Search'
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badge: 'Easy'
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---
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::::warning
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You must write an algorithm with O(log n) runtime complexity.
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::::
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### Example 1:
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- Input: `nums = [-1,0,3,5,9,12], target = 9`
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- Output: `4`
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- Explanation: `9` exists in `nums` and its index is `4`
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### Example 2:
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- Input: `nums = [-1,0,3,5,9,12], target = 2`
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- Output: `-1`
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- Explanation: `2` does not exist in `nums` so return `-1`
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### Constraints:
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- `1 <= nums.length <= 10^4`
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- `-10^4 < nums[i], target < 10^4`
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- All the integers in `nums` are unique.
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- `nums` is sorted in ascending order.
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## Approach
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```mermaid
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flowchart TD
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S(["search(nums, target)"]) --> I["left = 0, right = n - 1"]
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I --> W{"left <= right?"}
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W -- no --> E(["return -1"])
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W -- yes --> M["mid = left + floor((right - left) / 2)"]
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M --> Q{"nums[mid] vs target"}
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Q -- equal --> R(["return mid"])
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Q -- "nums[mid] < target" --> L["left = mid + 1"]
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L --> W
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Q -- "nums[mid] > target" --> H["right = mid - 1"]
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H --> W
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```
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## Solution
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```js
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/**
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* @param {number[]} nums
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* @param {number} target
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* @return {number}
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*/
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var search = function(nums, target) {
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let left = 0;
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let right = nums.length - 1;
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while(left <= right) {
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const mid = left + Math.floor((right - left) / 2);
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if (nums[mid] === target) {
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return mid;
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} else if(nums[mid] < target){
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left = mid + 1;
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} else if (nums[mid] > target) {
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right = mid - 1;
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}
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}
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return -1;
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};
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```
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