How do you solve Sum of Digits in Base K on LeetCode?

Sum of Digits in Base K (LeetCode #1837) 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: Understanding how to convert between bases is crucial.

What is the brute force solution for Sum of Digits in Base K?

The brute force approach for Sum of Digits in Base K is Brute Force, with O(log(n)) time complexity and O(log(n)) space complexity. The brute force approach involves repeatedly dividing the number by the base and collecting the remainders, which represent the digits in the new base. We then sum these digits to get the final result. The optimal Optimal Solution approach improves this to O(log(n)).

What algorithm or data structure is used to solve Sum of Digits in Base K?

Sum of Digits in Base K uses the following concepts: Math. The recommended patterns to study are: Math, Base Conversion.

What are the interview tips for Sum of Digits in Base K?

Explain your thought process clearly while coding. Consider edge cases, such as small values for n and k. Practice converting numbers between bases to build intuition.

What are common mistakes when solving Sum of Digits in Base K?

Not handling the division correctly when converting bases. Forgetting to sum the digits properly.

#1837

Sum of Digits in Base K

Easy

MathMathBase Conversion

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

💡

Intuition

Time O(log(n))Space O(1)

The optimal solution is similar to the brute force but focuses on summing the digits directly during the conversion process, avoiding the need to store them in a list.

⚙️

Algorithm

4 steps

1Step 1: Initialize sum to 0.
2Step 2: While n is greater than 0, add n % k to sum.
3Step 3: Divide n by k.
4Step 4: Return the sum.

solution.py8 lines

1# Full working Python code
2
3def sum_of_digits(n, k):
4    total_sum = 0
5    while n > 0:
6        total_sum += n % k
7        n //= k
8    return total_sum

ℹ

Complexity note: The time complexity remains O(log(n)) due to the same division process, but the space complexity improves to O(1) since we do not store the digits.

1Understanding how to convert between bases is crucial.
2Summing digits can often be done in a single pass.

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