The hashing part clicked pretty fast for me: SHA the file contents for leaves, then for directories sort children by name and hash the concatenation of name+child_hash pairs.
Start by clarifying the requirements and constraints, then outline the Merkle tree design where each file's hash is a leaf and each folder's hash is derived from its children's hashes. Explain how to build the tree from a root path and how to diff two trees by recursively comparing hashes to identify added, modified, and removed files. Discuss trade-offs like hash function choice, handling of empty directories, and performance considerations.
Pro tip: Emphasize that the diff should be efficient by only traversing subtrees where hashes differ, and mention that you would handle edge cases like symlinks, permissions, and large files with streaming hashing.
Ask about expected directory sizes, file types, symlink handling, and whether the tree needs to be persisted or just used for diffing. Confirm the API contract: constructor takes a root path, diff returns a list of relative paths with change types.
Define leaf nodes as files with their content hash (e.g., SHA-256), and internal nodes as folders with a hash computed from the sorted hashes of their children. Explain how to build the tree recursively from the root path.
Recursively compare two trees: if hashes match, skip; if a leaf differs, mark as modified; if a node exists in one but not the other, mark all files under it as added or removed. Collect relative paths and change types.
Discuss handling of empty directories, symlinks, permission errors, and large files (streaming hashing). Mention optimizations like caching hashes and parallelizing file reads.
Compare Merkle tree approach to other methods (e.g., timestamp-based, full content comparison) and justify why Merkle tree is efficient for large directories. Mention potential improvements like using BLAKE3 for speed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.