This was a lot to hold in your head at once.
Start by clarifying assumptions about path syntax and return types, then propose a tree-based data structure where each node represents a path segment. Walk through each operation's logic and failure conditions, analyze time/space complexity, and outline unit tests covering edge cases.
Pro tip: Explicitly state your assumptions about path normalization (e.g., trailing slashes, '.' and '..') and error handling (e.g., exceptions vs. error codes) before diving into the design—this shows you think about real-world robustness and API design.
Define path syntax (e.g., absolute paths starting with '/', segments separated by '/', no empty segments except root), return types (e.g., boolean for create/remove, value or null for get), and error handling strategy (exceptions or error codes).
Select a tree where each node stores a value and a map of child segments to nodes. Justify why a tree (or trie) is ideal for hierarchical paths, enabling efficient traversal and operations.
For each operation, describe the traversal logic and how to check failure conditions: create (parent exists, path doesn't exist), set (path exists), get (path exists), remove (path exists, no children).
Analyze time complexity as O(k) where k is the number of path segments, and space complexity as O(total number of nodes). Discuss trade-offs vs. alternatives like hash maps.
List test cases covering edge cases: root operations, deep paths, invalid paths, create with missing parent, set on missing path, remove with children, and concurrent modifications if applicable.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.