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Oscar Health·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Phone screen for a software engineer role at Oscar Health. Two coding questions, both string manipulation flavored, and the second one had a follow-up that turned the whole thing into a mini word-break problem.

Questions Asked (2)

Q1

You're given a mapping of characters to Morse code. Write a function that converts an input string of lowercase English letters into its Morse code representation.

Algorithms & Data Structures
Author's notes

Pretty straightforward, just iterate through the string and concatenate the codes.

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AI HintsAI Generated

Suggested Approach

Clarify the exact Morse code mapping and output format (e.g., spaces between letters, handling of unmapped characters). Then implement a straightforward solution using a hash map for O(1) lookups, iterating through the input string and building the result. Discuss time and space complexity and consider edge cases like empty input or invalid characters.

Pro tip: Mention that you would precompute the Morse code mapping as a constant outside the function to avoid rebuilding it on every call, and that you'd use a StringBuilder for efficient string concatenation in languages like Java/C#.

1. Clarify requirements

Ask about the exact Morse code mapping, expected output format (e.g., spaces between letters), and how to handle non-lowercase or unmapped characters.

2. Choose data structure

Use a hash map (dictionary) to store the character-to-Morse mapping for O(1) lookups. Alternatively, an array indexed by character code if the alphabet is limited.

3. Iterate and build output

Loop through each character in the input string, look up its Morse code, and append it to a result builder, adding a space separator between letters.

4. Handle edge cases

Consider empty input, characters not in the mapping (e.g., digits, punctuation), and ensure the output format matches expectations (e.g., no trailing space).

5. Analyze complexity

State that time complexity is O(n) where n is the input length, and space complexity is O(n) for the output (or O(1) excluding output).

Key Points to Mention

  • Hash map for O(1) character lookups
  • StringBuilder or equivalent for efficient string concatenation
  • Time complexity O(n) and space complexity O(n)
  • Handling of spaces between Morse code letters
  • Edge cases: empty string, invalid characters
  • Precomputing the mapping as a constant to avoid repeated initialization

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

Q2

Given a Morse code string (no delimiters), generate all possible original strings that could have produced it.

Algorithms & Data Structures
Author's notes

This is where it got interesting.

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AI HintsAI Generated

Suggested Approach

Model the problem as a backtracking search over the Morse string, where at each position you try all possible Morse code lengths (1 to 4) that map to a valid letter. Use a dictionary mapping Morse sequences to letters, and recursively build strings until the entire input is consumed. This generates all possible original strings efficiently.

Pro tip: Clarify with the interviewer whether the Morse code mapping is the standard one (where each letter maps to a unique sequence) and whether the output should be sorted or deduplicated. Also, mention that the number of solutions can be exponential, so you might want to discuss pruning or output limits.

1. Understand the problem and constraints

Confirm the Morse code mapping (e.g., standard ITU) and that the input string contains only dots and dashes with no delimiters. Ask about output format, duplicates, and maximum input length.

2. Choose the right data structure

Build a hash map from Morse code strings to their corresponding letters (e.g., '.-' -> 'A'). This allows O(1) lookup for each possible Morse code segment.

3. Design a recursive backtracking algorithm

Define a recursive function that takes the current index in the Morse string and the current decoded string. At each step, try all possible Morse code lengths (1 to 4) starting at the current index; if the segment exists in the map, recurse with the updated index and appended letter.

4. Handle base case and collect results

When the index reaches the end of the Morse string, add the current decoded string to the result list. Ensure that the recursion explores all valid segmentations.

5. Analyze complexity and optimize if needed

Discuss time complexity: O(4^n) in the worst case, where n is the length of the Morse string, but pruning reduces it. Mention potential optimizations like memoization if only the count is needed, or iterative BFS/DP for generating all strings.

Key Points to Mention

  • Backtracking/recursion is the natural approach for generating all combinations.
  • Use a hash map for O(1) Morse-to-letter lookup.
  • The branching factor is at most 4 (since Morse codes are 1-4 characters long).
  • Time complexity is exponential in the worst case, but often much less due to invalid segments.
  • Space complexity is O(n) for recursion depth plus output storage.
  • Consider edge cases: empty string, invalid Morse sequences, and duplicate letters (though standard Morse is unique).

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