Tesla·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Apr 2026

Summary

Tesla SWE interview, got a classic DP string decoding problem. Nothing too wild but the edge cases around zeros will trip you up if you're not careful.

Questions Asked (1)

Given a string of digits, return the number of distinct ways it can be decoded back into letters, where A=1, B=2, ..., Z=26 and numbers are concatenated without separators.

Algorithms & Data Structures

Author's notes

The base problem clicked pretty fast for me, standard bottom-up DP.

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AI HintsAI Generated

Suggested Approach

Use dynamic programming where dp[i] represents the number of ways to decode the first i characters. At each position, consider single-digit decoding (if the digit is 1-9) and two-digit decoding (if the two-digit number is 10-26), summing the valid ways. Optimize space by keeping only the last two dp values.

Pro tip: Clarify edge cases upfront, like leading zeros or invalid strings, and mention that you can optimize space to O(1) since only the previous two states are needed. This shows attention to detail and efficiency, which Tesla values.

1. Clarify the problem and edge cases

Confirm that the input is a non-empty string of digits, and discuss how to handle leading zeros, zeros in the middle, and invalid strings (e.g., '0' or '30').

2. Define the DP state and recurrence

Let dp[i] be the number of ways to decode the first i characters. Then dp[i] = (dp[i-1] if s[i-1] != '0') + (dp[i-2] if 10 <= int(s[i-2:i]) <= 26).

3. Initialize base cases

Set dp[0] = 1 (empty string) and dp[1] = 1 if the first character is not '0', else 0.

4. Iterate and compute

Loop from i = 2 to n, applying the recurrence and handling invalid cases by setting dp[i] = 0 when no valid decoding exists.

5. Optimize space and return result

Since dp[i] depends only on dp[i-1] and dp[i-2], use two variables to achieve O(1) space, then return the final count.

Key Points to Mention

Dynamic programming approach with optimal substructure and overlapping subproblems.
Handling of zeros: a zero cannot be decoded alone, and must be part of '10' or '20'.
Time complexity O(n) and space complexity O(1) after optimization.
Edge cases: empty string, leading zeros, invalid two-digit numbers (>26), and strings with no valid decoding.
The recurrence relation and how it avoids double-counting.
Potential follow-up: reconstruct the actual decoded strings if needed.

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