HARD Arrays & Hashing (with constraints)
41. First Missing Positive
📖 Problem
Given an unsorted integer array nums, return the smallest missing positive integer. You must implement an algorithm that runs in O(n) time and uses O(1) auxiliary space.
🧠 Visual Learning Aid
1 Model the input into the right structure
2 Choose the core technique and invariant
3 Execute step-by-step with a sample
4 Validate complexity and edge cases
JS/TS Refreshers
- •Array methods (`push`, `pop`, `shift`, `slice`)
- •Object/Map/Set usage patterns
- •Function parameter and return typing
Logical Thinking Concepts
- •Define invariants before coding
- •Check edge cases first (`[]`, single element, duplicates)
- •Estimate time/space before implementation
💡 Approach
- → First missing positive is in range [1, n+1] where n is array length
- → Use the array itself as a hash map by marking positions
- → Place each number in its correct position (number 1 at index 0, etc.)
- → Time: O(n), Space: O(1)
- → Using hash set: O(n) time, O(n) space
- → Sorting: O(n log n) time, O(1) space
🛠️ Hints & Pitfalls
Hints
- •First missing positive is in range [1, n+1] where n is array length
- •Use the array itself as a hash map by marking positions
- •Place each number in its correct position (number 1 at index 0, etc.)
Common Pitfalls
- •Time: O(n), Space: O(1)
- •Using hash set: O(n) time, O(n) space
- •Sorting: O(n log n) time, O(1) space
🧪 Test Cases
Hidden tests on submit: 5
Test Case 1
Not run Input:
firstMissingPositive(nums: number[]); Expected:
Computed from hidden reference Test Case 2
Not run Input:
firstMissingPositive([...test1]); Expected:
Computed from hidden reference Test Case 3
Not run Input:
firstMissingPositive([...test2]); Expected:
Computed from hidden reference 📝 Code Editor
📤 Output