Snapchat·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jul 2026

Summary

Snapchat SWE interview with a classic dynamic programming problem. Pretty standard coding round, nothing too surprising, but the edge cases around zeros will trip you up if you're not careful.

Questions Asked (1)

Given a string of digits, count the total number of ways to decode it into letters using the mapping where '1' maps to 'A', '2' to 'B', and so on up to '26' mapping to 'Z'. Substrings like '06' or '30' are invalid.

Algorithms & Data Structures

Author's notes

The base logic clicked pretty fast for me, single digit or two digit, build up a dp array.

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AI HintsAI Generated

Suggested Approach

Use dynamic programming where dp[i] represents the number of ways to decode the substring s[0..i-1]. For each position, consider one-digit and two-digit decodings, checking validity (1-9 for one-digit, 10-26 for two-digit), and sum the valid ways. Optimize space by keeping only the last two dp values.

Pro tip: Clarify edge cases upfront, such as empty string, leading zeros, and strings with zeros in the middle, to show thoroughness. Also, mention that you can optimize space to O(1) by using two variables, which demonstrates awareness of efficiency.

1. Define the DP state

Let dp[i] be the number of ways to decode the first i characters of the string. Initialize dp[0] = 1 (empty string) and dp[1] = 1 if the first character is not '0', else 0.

2. Identify transitions

For each i from 2 to n, dp[i] = 0. If the current digit s[i-1] is between '1' and '9', add dp[i-1]. If the two-digit number s[i-2..i-1] is between 10 and 26, add dp[i-2].

3. Handle invalid cases

If the string is empty or starts with '0', return 0. Also, if any '0' is encountered, it must be part of a valid two-digit number (10 or 20), otherwise the decoding is invalid.

4. Optimize space

Since dp[i] depends only on dp[i-1] and dp[i-2], use two variables to store these values and update iteratively, achieving O(1) space.

5. Return the result

After iterating through the string, return the final dp value, which represents the total number of valid decodings.

Key Points to Mention

Dynamic programming approach with overlapping subproblems and optimal substructure.
Time complexity O(n) and space complexity O(1) with optimization.
Handling of edge cases: empty string, leading zeros, zeros in the middle, and invalid two-digit numbers.
The importance of checking both one-digit and two-digit decodings at each step.
Clarifying the problem constraints and assumptions with the interviewer before coding.
Potential follow-up: how to reconstruct all possible decodings (backtracking) if asked.

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