Spent the first couple minutes just re-reading the problem because I kept second-guessing what 'depth' meant.
Clarify the problem and edge cases, then propose a recursive DFS solution that tracks depth, and optionally an iterative BFS alternative. Discuss time and space complexity, and consider follow-up optimizations like handling large inputs or avoiding recursion depth issues.
Pro tip: Mention that you can solve it in one pass with O(n) time and O(d) space, where d is the maximum depth, and note that an iterative solution avoids stack overflow for deeply nested lists.
Confirm the definition of depth (starting at 1), input format (nested list of integers), and output (weighted sum). Ask about edge cases like empty lists or negative numbers.
Propose a recursive depth-first search (DFS) that passes the current depth to each element. Alternatively, suggest an iterative breadth-first search (BFS) using a queue that stores (element, depth) pairs.
Trace the algorithm on a small example, such as [[1,1],2,[1,1]], to demonstrate correctness and how depth is tracked.
State that both approaches run in O(n) time, where n is the total number of integers, and O(d) space for recursion stack or queue, where d is the maximum depth.
Mention handling empty lists, very deep nesting (prefer iterative to avoid stack overflow), and potential follow-ups like modifying the list in place or handling large inputs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.