Not too bad once you realize it's just a set lookup.
Start by clarifying the input format and edge cases, then propose a solution that builds a set of all existing ids and checks each block's parentId against that set. Emphasize that this approach is O(n) time and space, and discuss potential optimizations or alternative data structures.
Pro tip: Mention that you would handle duplicate ids gracefully (e.g., by using a set) and that you would consider the case where a block's parentId references itself, which should not be considered a root.
Ask about the input format (array of objects), whether ids are unique, and how to handle null or missing parents. Confirm that a root is defined as parentId null or not in the set of existing ids.
Propose building a set of all existing ids for O(1) lookups. Then iterate through the blocks and collect those whose parentId is null or not in the set.
State that the time complexity is O(n) and space complexity is O(n) due to the set. Discuss if sorting or other structures could help, but note that this is optimal for unsorted input.
Consider empty input, duplicate ids, self-referencing parentId, and missing parentId property. Write clean code with meaningful variable names and comments.
Walk through a few test cases: normal case, missing parent, null parent, empty list, and duplicate ids. Ensure the output matches expectations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Clarify the data structure representing the block hierarchy (e.g., parent pointers or adjacency list) and then propose an algorithm that traces from the target block up to the root, reversing the path. Discuss time and space complexity, and mention trade-offs between different representations.
Pro tip: Always ask about the expected frequency of queries and updates; if queries are frequent, precomputing paths or using a parent pointer with path compression can be more efficient. Also, consider edge cases like invalid block IDs or cycles.
Ask how the block hierarchy is stored: parent pointers, adjacency list, or a tree structure. Confirm if it's a tree (single parent) or a DAG, and whether block IDs are unique.
If parent pointers exist, walk upward from the target to the root, collecting IDs, then reverse. If only children lists, perform DFS from root to target, tracking the path.
Consider invalid block ID, root block (path is just itself), and cycles (if not a tree). Discuss error handling and assumptions.
For upward traversal: O(d) time and O(d) space, where d is depth. For DFS: O(n) time and O(d) space in worst case. Mention that if many queries, precomputing paths or using binary lifting can reduce query time.
Compare parent pointers vs. adjacency list: parent pointers give O(d) query but require updates if tree changes; adjacency list may need O(n) traversal. Suggest caching or memoization if queries are repeated.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.