W Code - Pattern-Based DSA Learning Platform

Bhanu Bisht

Template

Binary Search Template: Pattern, Code & Cheat Sheet

The Binary Search pattern is one of the most frequently tested coding interview patterns. Divide search space in half for logarithmic time lookups. This template gives you a reusable code skeleton, pseudocode, and implementation in multiple languages so you can solve 14+ problems using this single mental model.

Difficulty: Easy | Time Complexity: O(log n) | Space Complexity: O(1)

When to Use This Template

Use the Binary Search template when you see these signals in a problem:

1.Sorted array search — Problems asking to sorted array search

2.Boundary finding — Problems asking to boundary finding

3.Optimization problems — Problems asking to optimization problems

Prerequisites: Arrays basics, Sorting

Problem count on W Code: 14 problems across Easy, Medium, and Hard difficulty levels.

If the problem does not match these signals, consider alternative patterns.

Pseudocode Template

function binarySearch(arr, target):
    left = 0
    right = length(arr) - 1
    
    while left <= right:
        mid = left + (right - left) / 2
        
        if arr[mid] == target:
            return mid
        else if arr[mid] < target:
            left = mid + 1
        else:
            right = mid - 1
    
    return -1

Python Implementation

python
def binary_search(arr: list, target: int) -> int:
    left, right = 0, len(arr) - 1
    
    while left <= right:
        mid = left + (right - left) // 2
        if arr[mid] == target:
            return mid
        elif arr[mid] < target:
            left = mid + 1
        else:
            right = mid - 1
    
    return -1

Java Implementation

java
public int binarySearch(int[] arr, int target) {
    int left = 0, right = arr.length - 1;
    
    while (left <= right) {
        int mid = left + (right - left) / 2;
        if (arr[mid] == target) return mid;
        else if (arr[mid] < target) left = mid + 1;
        else right = mid - 1;
    }
    
    return -1;
}

C++ Implementation

cpp
int binarySearch(vector<int>& arr, int target) {
    int left = 0, right = arr.size() - 1;
    
    while (left <= right) {
        int mid = left + (right - left) / 2;
        if (arr[mid] == target) return mid;
        else if (arr[mid] < target) left = mid + 1;
        else right = mid - 1;
    }
    
    return -1;
}

Variations & Adaptations

The Binary Search pattern has several variations you should master:

Variation 1: Classic Search

This variation is useful when the problem specifically requires classic search. Adapt the main template by modifying the core loop/recursion logic accordingly.

Variation 2: Lower Bound / Upper Bound

This variation is useful when the problem specifically requires lower bound / upper bound. Adapt the main template by modifying the core loop/recursion logic accordingly.

Variation 3: Search in Rotated Array

This variation is useful when the problem specifically requires search in rotated array. Adapt the main template by modifying the core loop/recursion logic accordingly.

Variation 4: Binary Search on Answer

This variation is useful when the problem specifically requires binary search on answer. Adapt the main template by modifying the core loop/recursion logic accordingly.

Common Mistakes & Edge Cases

When implementing Binary Search, watch out for:

1.Off-by-one errors — Carefully handle boundary conditions in loops

2.Missing base case — Ensure recursion terminates properly

3.Integer overflow — Use appropriate data types for large inputs

4.Empty input — Handle null/empty arrays, strings, or graphs

5.Single element — Test with minimal inputs

Edge cases to always test:

•Empty input → expected output

•Single element → correct result

•All same elements → no infinite loop

•Maximum constraints → within time limit

Step-by-Step Problem Solving Guide

1.Identify the pattern: Does the problem involve Sorted array search, Boundary finding, Optimization problems?

2.Choose the template: Select the variation from above that best fits

3.Define variables: Map problem-specific entities to template variables

4.Implement the core logic: Fill in the template skeleton

5.Handle edge cases: Add boundary checks

6.Verify with examples: Trace through sample inputs

7.Analyze complexity: Confirm O(log n) time and O(1) space

Frequently Asked Questions

What problems can I solve with the Binary Search template?

The Binary Search template applies to 14+ problems including: Sorted array search, Boundary finding, Optimization problems. Look for problems that involve divide search space in half for logarithmic time lookups..

What is the time complexity of Binary Search?

The typical time complexity is O(log n) with space complexity of O(1). Some variations may differ.

What should I learn before Binary Search?

Prerequisites include: Arrays basics, Sorting. Make sure you are comfortable with these concepts first.

How do I recognize a Binary Search problem in an interview?

Key signals: the problem involves sorted array search; the problem involves boundary finding; the problem involves optimization problems. Practice identifying these cues by solving at least 10 problems using this pattern.

Practice 14+ Binary Search problems on W Code with instant feedback and AI-powered hints. Start your free practice now!

Start Learning Free