The basic parsing part I got through fine.
Start by modeling cells as nodes in a directed graph where edges represent dependencies, then discuss how to propagate updates using topological sorting or depth-first traversal with cycle detection. Emphasize the trade-offs between eager and lazy evaluation, and how to handle cycles gracefully.
Pro tip: Mention that you would use a topological sort to ensure dependencies are updated in the correct order, and that you would detect cycles to prevent infinite loops—this shows you understand both correctness and robustness.
Represent each cell as a node and each formula as directed edges from dependencies to dependents. This graph captures the relationships needed for updates.
Before evaluating, check for cycles using DFS or Kahn's algorithm. If a cycle exists, mark affected cells as errors to avoid infinite recursion.
Decide between eager (recompute immediately on change) and lazy (recompute on read) evaluation. Discuss trade-offs: eager gives immediate consistency but may waste computation; lazy is efficient but can cause stale reads.
For eager updates, perform a topological sort of the affected subgraph and recompute cells in order. For lazy, mark dependents as dirty and recompute on demand.
Consider incremental updates, caching, and batching to improve performance. Handle errors like circular references and invalid formulas.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.