I spent too long on the happy path and almost forgot to address cycle detection until they nudged me.
Clarify requirements and edge cases, then design a data structure that tracks task dependencies and readiness. Use a priority queue (min-heap) keyed by deadline for ready tasks, and update readiness when subtasks complete. Implement add_task and process_next with careful handling of parent-child relationships and deadline ordering.
Pro tip: Discuss how you would handle dynamic updates to deadlines and the trade-offs between eager vs lazy readiness checks, showing awareness of real-world scalability.
Ask about task dependencies, deadline updates, and concurrency. Confirm that a parent can have multiple subtasks and that subtasks may have their own subtasks (recursive).
Choose a min-heap for ready tasks ordered by deadline. Use a hash map to store tasks and their subtask lists, and track incomplete subtask counts per parent.
Insert the task into the map. If it has no incomplete subtasks, push it into the heap. Otherwise, increment the parent's incomplete subtask count and store the relationship.
Pop the earliest-deadline ready task from the heap. When a task completes, decrement its parent's incomplete count; if it reaches zero, push the parent into the heap.
State time complexities: O(log n) for heap operations, O(1) for map lookups. Discuss alternatives like topological sort or event-driven updates, and how to handle deadline changes.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.