← Fuse Energy Interview Insights
This is a bigger problem than it looks at first glance.
Start by clarifying requirements and constraints, then propose a design using a dependency graph to track cell relationships. Explain how SET, GET, and SUM operations work, including dynamic updates via topological ordering or lazy evaluation. Finally, discuss trade-offs and potential optimizations.
Pro tip: Mention that you would use a directed acyclic graph (DAG) to detect and prevent circular dependencies, and consider lazy evaluation to avoid unnecessary recomputations. This shows awareness of real-world edge cases and performance.
Ask about expected operations, data types, range sizes, update frequency, and whether circular dependencies should be prevented. Confirm if SUM can reference other SUM cells.
Propose storing cell values in a hash map and maintaining a dependency graph where each cell tracks its dependents and dependencies. For ranges, consider storing them as objects that reference the range boundaries.
For SET, update the cell value and propagate changes to dependents. For GET, return the stored value. For SUM, compute the sum of referenced cells or ranges, and register dependencies.
Use topological sorting or lazy evaluation to recompute dependent cells when a value changes. Detect cycles to prevent infinite loops.
Compare eager vs. lazy evaluation, discuss time/space complexity, and suggest optimizations like caching or incremental updates for large ranges.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
I blanked for a second on what 'reasonable behavior' even means here.
Start by defining the dependency graph and the cycle detection problem, then explain how you would detect cycles (e.g., DFS with recursion stack) and handle them (e.g., reject the edit, show an error, or break the cycle). Emphasize trade-offs between eager detection on each edit versus lazy detection during evaluation, and discuss incremental algorithms for performance.
Pro tip: Mention that cycle detection should be integrated into the edit operation to prevent invalid states, and that you can use topological sorting to both detect cycles and determine evaluation order. Also, consider that in a spreadsheet, cycles might be allowed temporarily but flagged, and that user experience matters (e.g., highlighting the cycle).
Represent cells as nodes and dependencies as directed edges (e.g., A1 -> B1 if A1 depends on B1). Clarify that a cycle occurs when there is a directed cycle in this graph.
Use DFS with a recursion stack (or colors: white/gray/black) to detect cycles in O(V+E) time. Alternatively, use Kahn's algorithm for topological sorting, which also detects cycles.
Compare eager detection (on each edit) versus lazy detection (during evaluation). Eager detection prevents invalid states but may be slower; lazy detection is simpler but can lead to errors later.
Options: reject the edit with an error message, allow the cycle but mark affected cells as errors, or break the cycle by removing a dependency. Discuss trade-offs and user experience.
For large spreadsheets, use incremental cycle detection (e.g., only check affected subgraph) or maintain a topological order and update it efficiently. Mention that full re-computation may be acceptable for small graphs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.