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Google·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Google SWE interview, second round. A tree traversal coding problem that looked simple on the surface but turned into a longer conversation about implementation choices than I expected.

Questions Asked (1)

Q1

Given two APIs, one that returns the children paths of a directory and one that deletes a file, implement a function that deletes an entire directory recursively.

Algorithms & Data StructuresTechnical Trade-offsAPI & Integrations
Author's notes

The core algorithm is just DFS, so I got through the implementation pretty fast.

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AI HintsAI Generated

Suggested Approach

Clarify the API contracts and edge cases first, then implement a recursive depth-first traversal that deletes children before the parent. Discuss iterative alternatives and trade-offs like stack depth, error handling, and performance.

Pro tip: Mention that you would confirm whether the delete API is idempotent and whether the children API returns files or only directories, as these details drastically affect the implementation and error handling.

1. Clarify API contracts and edge cases

Ask about the exact behavior of the children API (does it return files and directories? pagination?) and the delete API (does it delete empty directories? is it idempotent?). Also consider edge cases like empty directories, symlinks, and permission errors.

2. Choose traversal strategy

Decide between recursion and iteration. Recursion is simpler but may hit stack limits for deep directories; iteration with an explicit stack avoids that but is more complex. Discuss the trade-offs.

3. Implement the deletion logic

Write a function that, for a given path, fetches its children. For each child, if it's a directory, recursively delete it; if it's a file, delete it directly. Finally, delete the original directory (if the API supports it) or ensure it's empty.

4. Handle errors and edge cases

Add error handling for API failures (e.g., network issues, permission denied). Decide whether to fail fast or continue and report errors. Consider retries for transient errors.

5. Analyze complexity and optimize

Discuss time complexity (O(n) where n is number of files/directories) and space complexity (O(d) for recursion depth). Mention potential optimizations like parallel deletion or batching API calls if allowed.

Key Points to Mention

  • Depth-first traversal (post-order) to delete children before parent
  • Recursion vs iteration trade-offs (stack overflow risk, readability)
  • Error handling: idempotency, retries, partial failures
  • API call efficiency: batching, pagination, rate limits
  • Edge cases: empty directories, symlinks, permission issues
  • Time and space complexity analysis

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