How do you solve Rabbits in Forest on LeetCode?

Rabbits in Forest (LeetCode #781) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Rabbits that give the same answer can be grouped together, leading to fewer total rabbits.

What is the brute force solution for Rabbits in Forest?

The brute force approach for Rabbits in Forest is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach considers each rabbit's answer and assumes the worst-case scenario for each. It calculates the total number of rabbits by simply adding the answers and accounting for potential duplicates. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Rabbits in Forest?

Rabbits in Forest uses the following concepts: Array, Hash Table, Math, Greedy. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Rabbits in Forest?

Always clarify the problem statement and constraints before jumping into coding. Think about edge cases, such as all rabbits giving the same answer. Discuss your thought process with the interviewer to demonstrate your understanding.

What are common mistakes when solving Rabbits in Forest?

Failing to account for the possibility of multiple rabbits giving the same answer. Not using integer division correctly when calculating groups.

#781

Rabbits in Forest

Medium

ArrayHash TableMathGreedyHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(n)

💡

Intuition

Time O(n)Space O(n)

The optimal approach uses a HashMap to count how many rabbits gave the same answer. It then calculates the minimum number of rabbits needed based on these counts, ensuring we account for groups of rabbits that share the same color.

⚙️

Algorithm

3 steps

1Step 1: Create a HashMap to count occurrences of each answer.
2Step 2: For each unique answer, calculate the minimum number of rabbits needed using the formula: (count + answer) // (answer + 1) * (answer + 1).
3Step 3: Sum these values to get the total number of rabbits.

solution.py10 lines

1# Full working Python code
2
3def minRabbits(answers):
4    from collections import Counter
5    count = Counter(answers)
6    total_rabbits = 0
7    for answer, cnt in count.items():
8        total_rabbits += (cnt + answer) // (answer + 1) * (answer + 1)
9    return total_rabbits
10

ℹ

Complexity note: This complexity is efficient because we traverse the answers array once to build the count, and then we iterate through the unique answers, which is much smaller than n in most cases.

1Rabbits that give the same answer can be grouped together, leading to fewer total rabbits.
2Understanding how to group answers helps in minimizing the total count.

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