The core logic wasn't bad, nested loops to accumulate squares manually.
Start by clarifying the problem constraints and edge cases, then walk through a manual example to demonstrate understanding. Implement a solution using nested loops to compute the sum of squares for each sublist without built-in aggregation, and finally analyze time and space complexity.
Pro tip: Explicitly state that you're avoiding built-in sum to comply with the constraint, and mention that you're considering potential integer overflow, showing attention to detail and robustness.
Ask about input size, possible empty sublists, negative numbers, and whether the output should preserve order. Confirm that built-in sum is prohibited.
Explain that you'll iterate through each sublist, compute the sum of squares using a loop, and append the result to a flat list.
Write code with nested loops: outer loop over sublists, inner loop over elements, accumulating squares in a variable, then appending to result list.
State that time complexity is O(N) where N is total number of elements, and space complexity is O(M) for the output list where M is number of sublists (excluding input).
Walk through a sample input, including edge cases like empty sublists or negative numbers, to verify correctness.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.