The difference between linear and binary search is the difference between O(n) and O(log n) — which at scale means millions of operations vs 20.
🔍 Linear Search
function linearSearch(arr, target) {
for (let i = 0; i < arr.length; i++) {
if (arr[i] === target) return i;
}
return -1;
}
- Time: O(n) | Space: O(1) | Works on: unsorted ✅
🔍 Binary Search
function binarySearch(arr, target) {
let left = 0, right = arr.length - 1;
while (left <= right) {
const mid = Math.floor((left + right) / 2);
if (arr[mid] === target) return mid;
else if (arr[mid] < target) left = mid + 1;
else right = mid - 1;
}
return -1;
}
- Time: O(log n) | Space: O(1) | Requires: sorted array ⚠️
Why O(log n)? With 1,000,000 elements → at most 20 steps.
⚖️ Comparison
| Factor | Linear | Binary |
|---|---|---|
| Requires sorted | ❌ No | ✅ Yes |
| Time complexity | O(n) | O(log n) |
| Space complexity | O(1) | O(1) |
| Best for | Small/unsorted | Large sorted data |
⚠️ Critical Rule
Binary search on unsorted data gives wrong results with no error. Always sort first.
🎯 Interview Q&A
Q: Binary search on linked list?
A: O(n) to find mid makes it pointless. Use arrays.
Q: Find first occurrence in duplicates?
A: Modified binary search — continue left even after finding a match.
Part 6 of the Bitveen DSA Series. Originally published at bitveen.com