← Anthropic Interview Insights

Anthropic·Software Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say
May 2026

Summary

Interviewed for a software engineering role at Anthropic and got a file system grouping problem. Pretty standard coding round, nothing too wild, but the parsing step tripped me up more than I expected.

Questions Asked (1)

Q1

You're given a list of strings describing directory contents, where each string encodes a root path followed by filenames and their contents. Group all file paths that share identical content, returning only groups of two or more files.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

The problem looks clean on the surface but parsing that input format took me longer than I'd like to admit.

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AI HintsAI Generated

Suggested Approach

Clarify the input format and edge cases, then propose a hash map solution that maps content to a list of file paths. Traverse the directory structure, read each file's content, and group paths by content hash, returning groups with size >= 2.

Pro tip: Mention that you would use a cryptographic hash (e.g., SHA-256) of file contents to save memory and avoid storing large contents in the map, and discuss the trade-off between collision risk and memory efficiency.

1. Clarify Input and Edge Cases

Ask questions to understand the exact format of the input strings, whether paths are absolute or relative, and how to handle empty files, duplicate paths, or missing files.

2. Choose Data Structures

Select a hash map to group file paths by content. Use the file content (or its hash) as the key and a list of paths as the value.

3. Traverse and Read Files

Parse the input to extract file paths and contents. If the input is a directory tree, perform a traversal (e.g., DFS) to read each file's content.

4. Group and Filter

Insert each file path into the map under its content key. After processing all files, filter the map to keep only groups with two or more paths.

5. Analyze Complexity and Trade-offs

Discuss time and space complexity (O(N) where N is total content size), and trade-offs between hashing and direct content comparison, including collision handling.

Key Points to Mention

  • Use a hash map with content as key and list of paths as value.
  • Consider using a cryptographic hash of content to reduce memory usage.
  • Handle edge cases: empty files, duplicate paths, symbolic links, and permission errors.
  • Time complexity: O(N) where N is total size of all file contents; space complexity: O(N) for storing contents or hashes.
  • Trade-off: hashing is faster and more memory-efficient but introduces collision risk; direct comparison is exact but slower and more memory-intensive.
  • Return only groups with two or more files, and ensure paths are unique within a group.

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