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Classic problem but I still fumbled the explanation a bit.
Use a hash map to group strings by a canonical key that is identical for all anagrams, such as the sorted string or a character count signature. Iterate through the input array, compute the key for each string, and append the string to the corresponding group. Finally, return the values of the hash map as a list of lists.
Pro tip: Discuss the trade-offs between sorting each string (O(k log k) per string) and using a character count array (O(k) per string) as the key, and mention that the character count approach can be more efficient for long strings or large alphabets.
Ask clarifying questions about input constraints, such as string length, character set, and whether the output order matters. Confirm that anagrams are case-sensitive and that empty strings are considered anagrams of each other.
Decide on a method to generate a unique key for each anagram group. Common approaches are sorting the string or using a character frequency count. Explain why the key must be identical for all anagrams.
Outline the steps: initialize a hash map, iterate over each string, compute its key, and add the string to the list associated with that key. Mention that the map's values will be the final groups.
State the time and space complexity. For sorting approach: O(n * k log k) time, O(n * k) space. For counting approach: O(n * k) time, O(n * k) space. Discuss trade-offs.
Consider edge cases like empty input, single string, strings with repeated characters, and Unicode characters. Walk through a small example to verify correctness.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
The problem itself is fine, BFS and grab the last node per level, or DFS going right child first while tracking depth.
Use BFS level-order traversal, recording the last node at each level to get the right-side view. Clearly define the TreeNode structure, implement the solution, and write test cases covering edge cases like empty tree, single node, skewed tree, and balanced tree.
Pro tip: Mention that DFS with depth tracking can also solve this in O(n) time and O(h) space, showing you understand trade-offs. Also, proactively discuss how you'd test the solution, including edge cases, to demonstrate thoroughness.
Confirm the problem: return values visible from the right side, top to bottom. Define the TreeNode class with val, left, right.
Decide between BFS (level-order) and DFS (pre-order with depth). Explain why BFS is straightforward: process each level, take the last node.
Write code for BFS using a queue. For each level, iterate through all nodes, and after the loop, add the last node's value to the result.
Create test cases: empty tree, single node, left-skewed, right-skewed, balanced tree, and a tree where right side is not just the rightmost path.
State time complexity O(n) and space complexity O(w) where w is max width for BFS, or O(h) for DFS.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.