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TikTok·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

TikTok software engineer interview with two coding problems back to back. Pretty standard algorithmic stuff but the island problem tripped me up more than I expected.

Questions Asked (2)

Q1

Given a list of intervals, merge all overlapping intervals and return the result.

Algorithms & Data Structures
Author's notes

Sorted by start time first which is the obvious move, then iterated through comparing end times.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem (e.g., whether intervals are inclusive, if input is sorted, and expected output format). Then propose sorting intervals by start time and merging in a single pass, explaining the O(n log n) time and O(n) space complexity. Walk through an example to demonstrate correctness.

Pro tip: Mention edge cases like empty input, single interval, and intervals that are adjacent but not overlapping (e.g., [1,2] and [2,3]) to show thoroughness. Also, discuss how you would handle large inputs or streaming data if relevant.

1. Clarify requirements

Ask about input format, whether intervals are sorted, inclusivity of endpoints, and expected output. Confirm if the result should be sorted.

2. Outline approach

Propose sorting intervals by start time, then iterating and merging overlapping intervals into a result list. Explain why sorting is necessary.

3. Detail algorithm

Describe the merge condition: if the current interval's start <= last merged interval's end, update the end to the max of both ends; otherwise, add the current interval to the result.

4. Analyze complexity

State time complexity O(n log n) due to sorting, and space complexity O(n) for the output (or O(1) extra if sorted in-place and output not counted).

5. Test with examples

Walk through a sample input like [[1,3],[2,6],[8,10],[15,18]] to show the merging process and verify edge cases.

Key Points to Mention

  • Sorting intervals by start time is crucial for efficient merging.
  • Merge condition: overlap if current.start <= lastMerged.end.
  • When merging, update end to max(lastMerged.end, current.end).
  • Time complexity: O(n log n) due to sorting; space complexity: O(n) for output.
  • Handle edge cases: empty list, single interval, non-overlapping intervals, and adjacent intervals.
  • If input is already sorted, time complexity reduces to O(n).

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

Q2

Given a 2D grid, count the number of distinct islands where two islands are considered the same if one can be translated to match the other.

Algorithms & Data Structures
Author's notes

This one hurt a bit.

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AI HintsAI Generated

Suggested Approach

Use DFS/BFS to find each island, then normalize its shape by translating it to a canonical form (e.g., relative coordinates from the top-left cell). Store these normalized shapes in a set to count distinct islands.

Pro tip: Mention that you can optimize by using a hash of the normalized shape (like a string of relative coordinates) to avoid storing large coordinate lists, and discuss trade-offs between different normalization methods.

1. Identify and Traverse Islands

Iterate through the grid; when you find an unvisited '1', perform DFS/BFS to collect all cells of that island, marking them visited.

2. Normalize Island Shape

Translate the island's coordinates so that the minimum row and column are 0, making the shape invariant to translation.

3. Store and Compare Shapes

Convert the normalized coordinates into a canonical representation (e.g., sorted list or string) and insert into a set to track unique shapes.

4. Count Distinct Islands

After processing all islands, the size of the set gives the number of distinct islands.

5. Analyze Complexity

Discuss time and space complexity: O(R*C) for traversal, and O(R*C) for storing shapes in the worst case.

Key Points to Mention

  • DFS/BFS for island traversal
  • Translation invariance via relative coordinates
  • Canonical representation (e.g., sorted list of coordinates or string)
  • Using a set to deduplicate shapes
  • Time and space complexity analysis
  • Handling edge cases (empty grid, no islands, all water)

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