🔥 Binary Search Coding Problems (Must for Interviews) 🔍💻

These are high-frequency interview problems based on Binary Search. Focus on logic + pattern recognition.

🧠 1️⃣ Basic Binary Search (Find Element Index)

Problem:
Given a sorted array, find the index of a target element.

Approach:

• Compare with middle
• Go left or right
• Repeat until found

👉 This is the foundation of all binary search problems.

🧠 2️⃣ First Occurrence of Element

Problem:
Find the first position of a target in a sorted array with duplicates.

Example:
Array:, Target = 2 → Output: index 1[1][2][3]

Insight:
👉 Don’t stop at first match
👉 Continue searching on the left side

🧠 3️⃣ Last Occurrence of Element

Problem:
Find the last position of a target.

Example:
Array: → Output: index 3[1][2][3]

Insight:
👉 Move towards the right side after finding match

🧠 4️⃣ Count Occurrences

Problem:
Count how many times a number appears.

Approach:
👉 count = last_index - first_index + 1

🧠 5️⃣ Search in Rotated Sorted Array

Problem:
Array is rotated:
Find target efficiently.[4][5][6][7][0][1][2]

Insight:
👉 One half is always sorted
👉 Decide which side to search

🧠 6️⃣ Find Minimum in Rotated Sorted Array

Problem:
Find smallest element in rotated array.

Example:
→ Output: 1[4][5][6][1][2][3]

Insight:
👉 Compare middle with rightmost element

🧠 7️⃣ Square Root using Binary Search

Problem:
Find integer square root of a number.

Example:
√25 → 5

Insight:
👉 Use binary search on range 1 to n

🧠 8️⃣ Peak Element Problem

Problem:
Find an element greater than its neighbors.

Insight:
👉 If mid < next → go right
👉 Else → go left

⚡️ Common Pattern

Binary search is not just for searching. It is used when:
• Data is sorted
• You need optimal solution (log n)
• You can eliminate half of search space

⚠️ Common Mistakes

❌ Wrong mid calculation
❌ Infinite loops
❌ Not updating bounds correctly
❌ Ignoring edge cases