No details shared about how it went, just that it came up.
Clarify that this is the Nested List Weight Sum problem, then propose a recursive DFS that passes the current depth down the call stack. At each element, if it's an integer, add value * depth to the running sum; if it's a list, recurse with depth + 1. Alternatively, use BFS with a queue to process level by level, multiplying by the level number.
Pro tip: Meta interviewers often care about clean, bug-free code and edge-case handling. Before coding, explicitly state that you'll treat the input as a tree where depth equals the level, and mention that you'll test with empty lists, nested empty lists, and negative numbers to show thoroughness.
Confirm that the input is a nested list of integers and that the weight is the depth (1-indexed). Ask about constraints like maximum depth or total elements to discuss complexity.
Decide between recursive DFS (simpler, uses call stack) and iterative BFS (avoids recursion depth issues). Explain the trade-offs briefly.
For DFS: define a helper function that takes the nested list and current depth. Iterate through elements; if integer, add to sum; if list, recurse with depth+1. For BFS: use a queue of (list, depth) and process level by level.
Write clean code with meaningful variable names. Handle base cases (empty list) and ensure the depth starts at 1. Use the provided NestedInteger interface.
Walk through a small example, then state time complexity O(N) where N is total number of integers and lists, and space complexity O(D) for recursion depth or O(N) for BFS queue.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.