I started with a recursive DFS and it felt right pretty quickly.
Model the problem as a tree where each node (group) aggregates data from its children. Use a post-order traversal (DFS) to compute the total employee count and overdue days for each group by summing the values from its children and adding its own direct employees. Alternatively, use memoization or iterative topological order to avoid recursion depth issues.
Pro tip: Clarify assumptions early: ask whether the group hierarchy is guaranteed to be a tree (no cycles) and whether employee data is keyed by group. Also, mention that you'd handle large trees by using an iterative approach to avoid stack overflow, showing awareness of production constraints.
Parse the parent-to-children mapping to build the tree structure. Organize the employee list by group, aggregating direct counts and overdue days per group.
Decide between recursive DFS (post-order) or iterative BFS/DFS with reverse topological order. Consider tree depth and potential recursion limits.
For each group, initialize totals with its direct employees. Then, for each child, add the child's aggregated totals to the parent's totals.
Check for groups with no employees, employees in non-existent groups, and ensure all groups are processed. Validate that totals match expected sums.
Discuss time and space complexity (O(N + M) where N is groups and M is employees). Suggest optimizations like memoization or parallel processing if needed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.