How do you solve H-Index II on LeetCode?

H-Index II (LeetCode #275) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(log n) time complexity and O(1) space complexity. Key insight: The h-index is determined by the number of papers that have at least h citations.

What is the brute force solution for H-Index II?

The brute force approach for H-Index II is Brute Force, with O(n) time complexity and O(1) space complexity. The brute force approach checks each possible h-index by counting how many papers meet the criteria for each h. This is straightforward but inefficient for larger datasets. The optimal Optimal Solution approach improves this to O(log n).

What algorithm or data structure is used to solve H-Index II?

H-Index II uses the following concepts: Array, Binary Search. The recommended patterns to study are: Binary Search, Array.

What are the interview tips for H-Index II?

Always clarify the constraints and requirements of the problem before diving into coding. Think about the properties of the data (like being sorted) that can help optimize your solution. Practice explaining your thought process as you code, as it helps clarify your understanding.

What are common mistakes when solving H-Index II?

Not recognizing that the problem requires a logarithmic time solution. Confusing the conditions for counting papers that meet the h-index criteria.

#275

H-Index II

Medium

ArrayBinary SearchBinary SearchArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n)	O(log n)
Space	O(1)	O(1)

💡

Intuition

Time O(log n)Space O(1)

Using binary search takes advantage of the sorted nature of the citations array. We can efficiently find the maximum h-index by narrowing down the search space.

⚙️

Algorithm

5 steps

1Step 1: Initialize left pointer to 0 and right pointer to the length of citations minus one.
2Step 2: While left pointer is less than or equal to right pointer, calculate the mid-point.
3Step 3: Check if the number of papers (n - mid) is at least mid + 1.
4Step 4: If true, move the left pointer to mid + 1. Else, move the right pointer to mid - 1.
5Step 5: The left pointer will point to the maximum h-index after the loop.

solution.py11 lines

1# Full working Python code
2
3def hIndex(citations):
4    left, right = 0, len(citations) - 1
5    while left <= right:
6        mid = (left + right) // 2
7        if citations[mid] >= mid + 1:
8            left = mid + 1
9        else:
10            right = mid - 1
11    return right + 1

ℹ

Complexity note: This complexity is achieved because we are using binary search, which divides the search space in half with each iteration.

1The h-index is determined by the number of papers that have at least h citations.
2The sorted nature of the citations array allows for efficient searching using binary search.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.