I started with a node class holding a name, type, parent pointer, and a map of children by name.
Clarify requirements and constraints first, then design a tree-based data structure with nodes representing folders and tables. Implement operations using recursive traversal or parent pointers, and discuss trade-offs between simplicity and efficiency.
Pro tip: Proactively discuss how you would handle edge cases like moving a folder into its own descendant or deleting non-empty folders, and mention potential optimizations like caching or indexing for large workspaces.
Ask about expected scale, concurrency needs, and whether operations should be atomic. Confirm node types and root initialization.
Choose a tree structure where each node has an ID, type, name, and children list (for folders) or data (for tables). Consider parent pointers for efficient moves.
Write methods for insert (add child to folder), list (return children of a folder), delete (remove node and its subtree), and move (change parent, ensuring no cycles).
Discuss time/space complexity of each operation and alternatives (e.g., adjacency list vs. nested sets). Mention potential optimizations like lazy deletion or path compression.
Walk through test cases: inserting into root, listing empty folder, deleting non-empty folder, moving folder into itself, and moving across different parents.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.