Snowflake·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

Snowflake software engineer coding round, one question, nothing too wild. Started with a naive solution and worked up to something cleaner by the end.

Questions Asked (1)

Determine whether a given number is a 'happy number'.

Algorithms & Data Structures

Author's notes

Came up with the linear space solution pretty quick, tracking visited numbers in a set.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Clarify the definition of a happy number and then implement a cycle detection algorithm to avoid infinite loops. Use either a hash set to track seen numbers or Floyd's cycle-finding algorithm for O(1) space. Discuss time and space complexity and potential optimizations.

Pro tip: Mention that all unhappy numbers eventually enter a cycle containing 4, so you can hardcode that to simplify detection. Also, highlight that the sum of squares operation can be optimized by precomputing squares of digits 0-9.

1. Clarify the problem

Confirm that a happy number is one that eventually reaches 1 when repeatedly replacing it with the sum of the squares of its digits. Ensure you understand the input constraints and expected output.

2. Choose a cycle detection method

Decide between using a hash set to detect repeats or Floyd's tortoise and hare algorithm for constant space. Explain the trade-offs.

3. Implement the sum of squares function

Write a helper function that computes the sum of the squares of the digits of a number. Optimize by using modulo and division.

4. Apply cycle detection

Repeatedly apply the sum of squares function and check for termination at 1 or detection of a cycle. Return true if 1 is reached, false otherwise.

5. Analyze complexity and edge cases

Discuss time and space complexity, and consider edge cases like 1, single-digit numbers, and very large numbers.

Key Points to Mention

Definition of a happy number and the process of summing squares of digits.
Cycle detection using a hash set (O(n) space) or Floyd's algorithm (O(1) space).
Time complexity: O(log n) per iteration, and number of iterations is bounded.
Space complexity: O(1) with Floyd's, O(n) with hash set.
Optimization: precompute squares of digits 0-9.
Edge cases: 1 is happy, 0 is unhappy, and numbers that quickly enter the 4-cycle.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.