← Sealth Interview Insights

Sealth·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jul 2026

Summary

Interviewed for a Software Engineer role at Sealth and got a Morse code decoding problem that had two parts. The first part was straightforward enough, but the second part asking for all valid decodings without character separators took me a while to wrap my head around.

Questions Asked (2)

Q1

Given a Morse-to-letter mapping, implement a function that decodes a Morse-encoded string using explicit character and word separators.

Algorithms & Data Structures
Author's notes

Pretty clean once I understood the structure.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Clarify the exact separators (e.g., single space between Morse characters, triple space between words) and edge cases. Then implement a solution that splits the input by word separator, then by character separator, and maps each Morse code to its letter using a hash map. Discuss time and space complexity and test with examples.

Pro tip: Mention that you would validate the input and handle invalid Morse codes gracefully, and that you can optimize by using a trie if the mapping is large or if decoding streaming input.

1. Clarify requirements and edge cases

Ask about the exact separators (e.g., single space vs. triple space), whether the input is guaranteed valid, and if there are any constraints on the Morse code mapping. Confirm the expected output format.

2. Choose data structures

Use a hash map (dictionary) to store the Morse-to-letter mapping for O(1) lookups. Consider if a trie is more appropriate for prefix-based decoding or streaming scenarios.

3. Design the algorithm

Split the input string by the word separator (e.g., triple space) to get words. For each word, split by the character separator (e.g., single space) to get Morse codes, then map each code to its letter and concatenate.

4. Implement and test

Write clean code with clear variable names. Test with simple cases (single letter, single word, multiple words) and edge cases (empty string, invalid codes, extra spaces).

5. Analyze complexity and optimize

State time complexity O(n) where n is the length of the input string, and space complexity O(m) for the mapping and output. Discuss potential optimizations like using a trie for large mappings or streaming input.

Key Points to Mention

  • Use a hash map for O(1) Morse code lookups.
  • Handle word and character separators correctly (e.g., triple space vs. single space).
  • Consider edge cases: empty input, invalid Morse codes, multiple consecutive separators.
  • Time complexity: O(n) where n is the length of the input string.
  • Space complexity: O(m) for the mapping and O(k) for the output.
  • Potential optimization: use a trie for prefix-based decoding or streaming input.

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

Q2

Now extend the decoding: if there are no character separators inside each word, enumerate all possible decoded sentences that are valid given the Morse mapping.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

This is where I started sweating.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Treat the problem as a recursive backtracking search over the concatenated Morse string, where at each position you try every possible Morse code (1-4 symbols) that matches a prefix and recursively decode the remainder. Accumulate all valid decodings, pruning branches that cannot lead to a complete decode. Discuss complexity and potential optimizations like memoization or dynamic programming to avoid redundant work.

Pro tip: Mention that without separators the number of decodings can be exponential, so you should discuss pruning and memoization early to show you think about scalability, not just correctness.

1. Clarify the problem and constraints

Confirm that the input is a single string of dots and dashes representing multiple words with no separators, and that you need to output all possible sentences (sequences of words) that can be formed using the Morse mapping. Ask about expected output size and whether duplicates are possible.

2. Model as a recursive search

Define a recursive function that takes the remaining Morse string and returns all valid decodings. At each step, try every Morse code of length 1 to 4 that matches a prefix; if it maps to a letter, recurse on the rest and prepend the letter to each result.

3. Handle word boundaries and spaces

Since there are no character separators inside each word, but words are separated by spaces in the original Morse (or you need to infer word breaks), decide how to insert spaces. Typically, you can treat the entire string as one word and then split into words by trying all possible space insertions, or assume the input already has spaces between words and only decode within each word.

4. Optimize with memoization

Use a hash map to cache results for each suffix of the Morse string to avoid recomputing overlapping subproblems. This reduces time complexity from exponential to polynomial in the length of the string, though the output size can still be exponential.

5. Analyze complexity and trade-offs

Discuss the time and space complexity: worst-case O(4^n) without memoization, and with memoization O(n * L) where L is the number of valid decodings. Mention that the output itself can be exponential, so any algorithm must at least spend time proportional to the output size.

Key Points to Mention

  • Recursive backtracking with pruning: only explore prefixes that match a valid Morse code.
  • Memoization (dynamic programming) to avoid recomputing the same suffix multiple times.
  • Handling of word boundaries: if spaces are not given, you need to consider all possible splits into words, which multiplies the number of possibilities.
  • Complexity analysis: exponential worst-case due to output size, but memoization helps with repeated subproblems.
  • Edge cases: empty string, invalid Morse sequences, and Morse codes that are prefixes of others (e.g., '.-' and '.-..').
  • Potential ambiguity: some Morse codes are prefixes of others, so you must try all lengths at each position.

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